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Conferences, Lectures, & Seminars
Events for October
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ECE Seminar: Unlocking the Future: Designing Next-Generation AI Chips with AI Algorithms
Tue, Oct 01, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Sung Kyu Lim, Motorola Solutions Foundation Professor, Georgia Institute of Technology
Talk Title: Unlocking the Future: Designing Next-Generation AI Chips with AI Algorithms
Abstract: Data, chips, and algorithms form the backbone of the AI revolution, demanding hardware as sophisticated as orchestrating a bustling city. In this technological realm, GPUs and high-bandwidth memory are essential yet frequently strained by the immense volume of data traffic. By employing 2.5D and 3D IC architectures through heterogeneous integration, we can greatly enhance energy efficiency and reduce latency in data transfers. A key component of this advancement is the automation of design and simulation for heterogeneous AI chips, where powerful algorithms take the lead, rather than humans. This remarkable capability hinges on advanced electronic design automation (EDA) tools. At Georgia Tech, my research team merges AI-driven and traditional algorithms to bolster EDA capabilities, specifically engineered for developing cutting-edge heterogeneous AI chips. In my talk, I will spotlight these innovations and address the ongoing challenges in AI chip design and EDA.
Biography: Prof. Sung Kyu Lim earned his Ph.D. in Computer Science from UCLA in 2000. Since 2001, he has been a faculty member at the School of Electrical and Computer Engineering at the Georgia Institute of Technology. His research explores the architecture, design, and electronic design automation (EDA) of 2.5D and 3D integrated circuits, contributing to over 400 published papers. He received the Best Paper Awards from the IEEE Transactions on CAD in 2022 and the ACM Design Automation Conference in 2023. He is an IEEE Fellow and served as a program manager at DARPA's Microsystems Technology Office from 2022 to 2024.
Host: Dr. Peter Beerel, pabeerel@usc.edu
More Info: (USC NetID login required to join seminar)
Webcast: https://usc.zoom.us/j/98539005883?pwd=naX0FZKrFLJwk7umPV6nneLbvRzZQF.1Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132 - LOCATION CHANGE
WebCast Link: https://usc.zoom.us/j/98539005883?pwd=naX0FZKrFLJwk7umPV6nneLbvRzZQF.1
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
Event Link: (USC NetID login required to join seminar)
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MHI - Physics Joint Seminar Series, Haocun Yu, Tuesday, October 1st at 2pm in EEB 248 & Zoom
Tue, Oct 01, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Haocun Yu, Marie-Curie Postdoctoral Fellow - University of Vienna
Talk Title: Using Quantum Optics to Illuminate the Universe's Mysteries
Series: MHI Physics Joint Seminar Series
Abstract: Advanced quantum techniques are revolutionizing our ability to observe and understand the universe. From employing squeezing in LIGO detectors to demonstrate human-scale macroscopic quantum phenomena, to utilizing photon-counting methods for measuring Earth's rotation and detecting dark matter, I will discuss how quantum optical applications enhance precision measurements, interface quantum mechanics and gravity, and offer new insights into fundamental questions about the nature of our universe.
Biography: Haocun Yu is a Marie-Cuire Postdoctoral Fellow at the University of Vienna working with Prof. Philip Walther. She completed her Ph.D. in physics in MIT LIGO group working with Prof. Nergis Mavalvala, working on quantum techniques and phenomena for gravitational-wave detectors. Her research interests lie in using various quantum techniques and precision sensing methods for fundamental physics. Her work has been recognized with honors including the MIT Martin Deutsch Award, APS Carl E. Anderson Dissertation Award, and Boeing Quantum Creators Prize. She is enthusiastic about continuing interdisciplinary work that advances quantum technologies and addresses intriguing fundamental questions about our world.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
Webcast: https://usc.zoom.us/j/92584409725More Information: Haocun Yu New Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132 - Location Change
WebCast Link: https://usc.zoom.us/j/92584409725
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute, ISE 651 Seminar Class
Tue, Oct 01, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Joao P. Hespanha, UC Santa Barbara
Talk Title: Koopman Operator, Entity-Based Systems, and Video Games
Host: Dr. Johannes Royset
More Information: Flyer 651 Dr. Joao P Hespanha 10.1.24.png
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Wed, Oct 02, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ji-Xin Cheng, Ph.D., Moustakas Chair Professor in Photonics and Optoelectronics; Professor of Biomedical Engineering. Professor of Electrical & Computer EnProfessor of Chemistry & Professor of Physics Boston University
Talk Title: Seeing the unseen using molecular fingerprints
Abstract: Spectrochemical imaging, using intrinsic fingerprint spectroscopic signals from molecules as a contrast mechanism, opens a new window for understanding life at the molecular level and also enables molecule-based precision diagnosis of diseases. Yet, the intrinsic spectroscopic signal, especially the vibrational signals from chemical bonds, is weaker than the fluorescence signal from a dye by many orders of magnitude. Detecting such weak signal from a tight focus (i.e., a small volume of ~1 femtoliter) under a microscope is extremely challenging and was considered nearly impossible. Ji-Xin Cheng devoted his career to overcoming such daunting barrier through developing advanced chemical microscopes over the past 25 years. In this lecture, Cheng will tell his journey of serendipity-driven innovation, scientific discovery, clinical translation, and entrepreneurship in the growing field of chemical imaging.
Biography: Ji-Xin Cheng attended University of Science and Technology of China (USTC) from 1989 to 1994. From 1994 to 1998, he carried out his PhD study on bond-selective chemistry at USTC. As a graduate student, he worked as a research assistant at Universite Paris-sud (France) on vibrational spectroscopy and the Hong Kong University of Science and Technology (HKUST) on quantum dynamics theory. After postdoctoral training on ultrafast spectroscopy at HKUST, he joined Sunney Xie’s group at Harvard University as a postdoc, where he spearheaded the development of CARS microscopy that allows high-speed vibrational imaging. Cheng joined Purdue University in 2003 as Assistant Professor in Weldon School of Biomedical Engineering and Department of Chemistry, promoted to Associate Professor in 2009 and Full Professor in 2013. He joined Boston University as the Inaugural Theodore Moustakas Chair Professor in Photonics and Optoelectronics in summer 2017.
Among his honors, Cheng is the recipient of the 2024 Raman Innovation Award at the International Conference of Raman Spectroscopy (ICORS, Rome), the 2024 Analytical Chemistry Spectrochemical Analysis Award from American Chemical Society, the 2024 Charles Delisi Award from Boston University College of Engineering, the 2024 Biophotonics Technology Innovator Award from International Society for Optics and Photonics (SPIE), the 2022 Boston University Innovator of Year, the 2020 Pittsburgh Spectroscopy Award from the Spectroscopy Society of Pittsburgh, the 2019 Ellis R. Lippincott Award from Optica, Society for Applied Spectroscopy, and Coblentz Society, the 2016 Research Award from Purdue University College of Engineering, and the 2015 Craver Award from Coblentz Society.
Host: Qifa Zhou
Location: Corwin D. Denney Research Center (DRB) - 145
Audiences: Everyone Is Invited
Contact: Carla Stanard
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When does human-centered AI (fail to) scale?
Wed, Oct 02, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Angel Hwang (she/her), Assistant Professor, USC Annenberg School for Communication and Journalism
Talk Title: When does human-centered AI (fail to) scale?
Abstract: State-of-the-art AI systems are built and deployed at the societal scale, increasing the need to consider sociotechnical factors for implementing systems of such magnitude. In contrast, individual user experience has long been the core of designing and developing user-friendly technologies. Through a series of experiments and case studies, I examine challenges and breakdowns as one extends individual-centered approaches to design societal-scale AI systems.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Angel Hsing-Chi Hwang (she/her) is an Assistant Professor at USC Annenberg School for Communication and Journalism. Her research explores the societal impact of AI-powered technologies on work practices. In her past and present work, she focuses on how practitioners design, build, and/or apply AI to facilitate group interaction, produce creative content, and balance everyday wellness.
Host: CAIS
More Info: https://cais.usc.edu/events/usc-cais-seminar-with-dr-angel-hwang/
Location: Montgomery Ross Fisher Building (school Of Social Work) (MRF) - 102
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
Event Link: https://cais.usc.edu/events/usc-cais-seminar-with-dr-angel-hwang/
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AME Seminar
Wed, Oct 02, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Andres Jared Goza, University of Illinois Urbana-Champaign
Talk Title: Lighting the fuse to enable metamaterials for passive, adaptive flow control
Abstract: Unsteady flow control is challenging in many engineering domains. Active techniques are costly, energy-intensive, and heavy, while passive approaches often lack robustness in handling complex flow dynamics. Metamaterials are structures with engineered architecture, allowing for catered response behaviors to stimuli. These structures offer a transformative potential for flow control by flow-metamaterial interaction, FMI. FMI could allow engineers to leverage architected structures to passively and adaptively produce desired flow responses.
To capitalize on this potential, however, we must first identify which classes of metamaterials are most promising for different flow scenarios, and understand how to align the key metamaterial behaviors with the relevant flow length- and timescales to enable favorable flow-structure interplay. This understanding must account for the behavior of the fully coupled flow-metamaterial system, which will generally yield dynamics with distinct time/length scales from those of the constituent flow/structure systems. Obtaining this understanding requires a suite of computational tools capable of predicting and understanding the flow-structure interplay between the targeted complex flows and modern architected structures.
We present some a-la-carte results on these various challenges and opportunities. We discuss some key metamaterial classes promising for certain flow behaviors. We share some ongoing development of high-fidelity and resolvent computational tools within an immersed boundary framework, currently without flow-structure interplay but being designed to enable robust, versatile computations between flows and a wide range of metamaterials. Finally, for simplified flow-metamaterial configurations, we discuss efforts to synthesize appropriate dimensionless parameters, expressed in terms of key intrinsic properties of the separate flow/structure systems, that govern the FMI system's behavior.
*Andres is grateful for funding from AFOSR to perform the presented work.
Biography: Andres is an Assistant Professor at UIUC. He uses computational techniques to study flow-structure interaction, particularly when the structure has some heterogeneous properties that make the coupled behavior more complex. He is interested in developing high-fidelity and analysis techniques to simulate and understand these dynamics. He also has two young children that bring fun regular surprises, and enjoys running, cycling, squash, and bouldering.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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Civil and Environmental Department Seminar Series
Thu, Oct 03, 2024 @ 02:00 PM - 03:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Jerome Hajjar, PhD, Northeastern University
Talk Title: Urban Engineering: New Strategies for a Resilient and Sustainable Future
Host: Dr. Burcin Becerik
More Information: Jerome F. Hajjar announcement.pdf
Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Salina Palacios
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Oct 04, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Sanjay Kumar, M.D, Ph.D., Chancellor Professor and Director of the California Institute for Quantitative Biosciences at UC Berkeley (QB3-Berkeley
Talk Title: Tales from the fourth dimension: Incorporating the element of time into biomaterial paradigms
Abstract: It is increasingly accepted that cell and extracellular matrix structure and mechanics can drive biology and disease, influencing everything from metabolism to stem cell differentiation to tumor progression. While significant progress has been made in developing culture technologies that mimic the complex physical microenvironment of tissue, many of these platforms are comparatively static in nature. There remains a need to understand how cell-matrix dynamics influence cell behavior. For example, how do cells remodel the carefully constructed matrices in which we place them, and how does this remodeling drive the biology we observe? And how does the time-dependent dissipation of cell-imposed stresses influence force-based signaling? While the answers are far from clear, I will describe efforts our team has made to attack these challenging problems, ranging from the use of proteomics to characterize the matrisome of invasive tumor cells ensconced within 3D matrices to to development and application of viscoelastic matrices to probe effects of stress relaxation on stem cell lineage commitment.
Biography: Sanjay Kumar, M.D., Ph.D., is Chancellor Professor and Director of the California Institute for Quantitative Biosciences at UC Berkeley (QB3-Berkeley). His primary appointment is in the Department of Bioengineering (which he chaired from 2019-22), with joint appointments in the UC Berkeley Department of Chemical and Biomolecular Engineering, the UCSF Department of Bioengineering and Therapeutic Sciences, and Lawrence Berkeley National Laboratory. Dr. Kumar earned his B.S. in Chemical Engineering at the University of Minnesota (1996) and his M.D. and Ph.D. in Molecular Biophysics from Johns Hopkins University (2003). He then completed postdoctoral training at Boston Children’s Hospital and Harvard Medical School. Dr. Kumar has co-authored >100 peer-reviewed publications and mentored >30 graduate students and postdoctoral fellows. He and his group have been recognized with the Presidential Early Career Award for Scientists and Engineers (PECASE), The NIH Director’s New Innovator Award, The Beckman Young Investigator Award, the NSF CAREER Award, and the Stem Cells Young Investigator Award. Dr. Kumar is an elected fellow of AAAS, AIMBE, and BMES, and he is a member of the BMES Board of Directors.
Host: Peter Wang
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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CSC/CommNetS-MHI Seminar: Laurent Lessard
Mon, Oct 07, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Laurent Lessard, Associate Professor, Mechanical and Industrial Engineering } Northeastern University
Talk Title: An automatic system to detect equivalence between iterative algorithms
Series: CSC/CommNetS-MHI Seminar Series
Abstract: Large-scale optimization problems in machine learning, signal processing, multi-agent systems, and imaging have fueled ongoing interest in iterative optimization algorithms. New optimization algorithms are regularly proposed in order to capture more complicated models, reduce computational burdens, or obtain stronger performance and convergence guarantees. But how can we be sure a recently proposed algorithm is novel? Algorithms can be written in different equivalent ways that are not always obvious, and with optimization being increasingly prevalent across different applications, popular algorithms are routinely "re-discovered". In this talk, we present a framework for reasoning about equivalence of iterative algorithms. Our framework is based on concepts from control theory and linear systems theory and can identify equivalence for a variety of algorithm classes: (a) single-oracle algorithms such as gradient-based methods, (b) multi-oracle algorithms such as distributed optimization algorithms, primal-dual methods, and operator-splitting methods, and (c) algorithms that use different but related oracles, such as subdifferentials, proximal operators, and Fenchel conjugates. Our work is a promising step towards an integrated and principled methodology for analyzing and designing control systems that use optimization algorithms "in the loop".
Biography: Laurent Lessard is an Associate Professor of Mechanical and Industrial Engineering at Northeastern University, Boston, USA, and a core faculty member of the Experiential Institute for AI. He received a B.A.Sc. in Engineering Science from the University of Toronto, and the M.S. and Ph.D. in Aeronautics and Astronautics at Stanford University. His research interests include: decentralized control, robust control, optimization, and machine learning. Before joining Northeastern, he was a Charles Ringrose Assistant Professor of Electrical and Computer Engineering at the University of Wisconsin–Madison. Prior to that, he was an LCCC Postdoc in the Department of Automatic Control at Lund University, Sweden, and a postdoctoral researcher in the Berkeley Center for Control and Identification at the University of California, Berkeley. Laurent is a recipient of the Hugo Schuck best paper award and the NSF CAREER award. He is also a Senior Member of IEEE.
Host: Dr. Lars Lindemann, llindema@usc.edu
More Information: 2024.10.07 CSC Seminar - Laurent Lessard.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Epstein Institute, ISE 651 Seminar Class
Tue, Oct 08, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Zvi Galil, Professor of Computing at Georgia Tech, former Dean of Georgia Tech College of Computing, former Dean of Columbia School of Engineering and Applied Science, and former President Tel Aviv University
Talk Title: Georgia Tech's Revolutionary Online Program and the Future of Online Learning in Higher Education
Host: Dr. Randy Hall
More Information: FLYER 651 Zvi Galil 10.8.24.png
Location: TCC 450- access elevator under stairs at Student Union
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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Identifying Critical Scenarios for Automated Driving Safety Validation
Wed, Oct 09, 2024 @ 10:30 AM - 11:30 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Adam Molin, Denso
Talk Title: Identifying Critical Scenarios for Automated Driving Safety Validation
Abstract: Verification and Validation (V&V) processes play a vital role in ensuring the safety and reliability of automated driving. Scenario-based testing in simulation has emerged as an effective approach for identifying critical scenarios that challenge the capabilities of automated driving systems. This presentation aims to explore the methodology to automatically find unknown critical test cases using specification-guided scenario-based testing. The talk will discuss the limitations of current techniques and how these can be overcome by the usage of generative AI for synthesizing critical scenarios.
This lecture satisfies the requirements for CSCI 591: Research Colloquium.
Host: Prof. Jyo Deshmukh
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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AAI-CCI-MHI Seminar on CPS
Wed, Oct 09, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Shai Revzen, Associate Professor Department of Electrical & Computer Science University of Michigan
Talk Title: More legs are different: the surprising simplicity of multi-legged locomotion
Series: EE598 Seminar Series
Abstract: Most of the animals that move with legs in the world do so with six or more legs, yet humans have focused primarily on bipeds and quadrupeds in designing legged robots. This talk will present some theoretical and experimental results that suggest that multi-legged robots with six or more legs exhibit some surprising properties that challenge our anthropocentric intuitions about locomotion. Modeling multi-legged motion fairly accurately, at single percentage points of relative error, turns out to be much easier than naively expected. This is both due to event-selected hybrid systems resolving multi-contact collisions in a smooth way, and due to the surprisingly high accuracy of geometric mechanics models on dry friction problems to which they shouldn't really apply. Together our results suggest that modeling and learning how to move with many legs might be much easier than has previously been thought.
Biography: Shai Revzen is an Associate Professor of Electrical Engineering and Computer Science in the University of Michigan's College of Engineering, and holds a courtesy faculty appointment in the Department of Ecology and Evolutionary Biology. He received his PhD in Integrative Biology doing research in the PolyPEDAL Lab at the University of California at Berkeley, and did his postdoctoral work in the GRASP Laboratory of the University of Pennsylvania. Prior to his academic work, Shai spent a decade in the tech industry, rising to Chief Architect R&D of the convergent systems division of Harmonic Lightwaves (HLIT). He is currently co-founder and Chief Science Officer of Acculine Medical, and General Manager of his consulting company, Izun, Inc. In his spare time he does martial arts and studies for a JD Law degree at Wayne State University.
Host: Feifei Qian
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Ariana Perez
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AME Seminar
Wed, Oct 09, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Rahul Panat, Carnegie Mellon University
Talk Title: Printed 3D Microelectronics: Process Development, Materials Science, and Devices Applications
Abstract: In this research, we develop a printed microelectronics technique based on droplet-based nanoparticle printing using the Aerosol Jet (AJ) technology. A balance between inertia forces and surface forces for the microdroplets (each containing nanoparticles), along with rapid solvent evaporation are used to create highly complex 3D microarchitectures of metals and polymers without auxiliary support and with near-fully dense truss members. Highly intricate 3-D micro-lattices, pillars, interconnects, and spirals are demonstrated. We then use these structures to: (i) study fundamental material science, and (ii) demonstrate device applications with extraordinary performance that cannot be achieved by any other method. For (i), a temperature-gradient-driven mass transport is shown as a new mechanism of 4D printing. For (ii), novel 3D geometry of electrodes enables detection of pathogen antibodies and antigens in 10-12 seconds at femtomolar sensitivities - the fastest detection of disease biomarkers yet reported! This technology is validated through human trials. In addition, the 3D microarchitectures in our lab enable fully customizable brain-computer interfaces (BCIs) that record electrical signals between neurons at densities of thousands of electrodes/cm2, which is 5-10× the current state-of-the-art BCI technologies. The technology was validated through animal testing via recording of the action potentials from the mouse brain. We also demonstrated the printing of high-capacity Li-ion batteries and thin flexible robotic skins with embedded sensors. Lastly, our ongoing work on creating manufacturing digital twins of the AJ printing process is also discussed.
Biography: Prof. Panat is Professor. He is courtesy faculty in the Materials Science and Engineering and the Robotics Institute at CMU. He is also the Associate Director of Research at the Manufacturing Futures Institute at CMU, which is focused on bringing the latest advances in digital technologies to advanced manufacturing. Prof. Panat completed his PhD in Theoretical and Applied Mechanics from the University of Illinois at Urbana in 2004. He joined Intel Corporation’s R&D unit in Chandler, AZ, where he worked for 10 years on microprocessor materials and manufacturing R&D - specifically on 3D heterogeneous integration. At Intel, Dr. Panat led a team of engineers that developed the fabrication process for world’s first halogen-free IC chip. He was part of a team that introduced the first Si chip with a billion transistors. He returned to academia in 2014 and joined CMU in fall 2017. His research is focused on microscale 3D printing and its applications to biomedical engineering, stretchable electronics, and Li-ion batteries. He has obtained > $7.5 million in research funding from US Intelligence agencies, US Air Force, US Army, ARPA-H, National Institutes of Health (NIH), Department of Energy (DOE), National Science Foundation (NSF), and industry. Prof. Panat is recipient of several awards, including MRS gold medal, Mavis Memorial Award, an award at Intel for his work on the halogen-free chip, Struminger Teaching Fellowship, and the Russell V. Trader chair professorship at CMU.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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CSC/CommNetS-MHI Seminar: Verena Häberle
Mon, Oct 14, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Verena HaÌberle, PhD student, Automatic Control Laboratory | ETH Zurich, Switzerland
Talk Title: Virtual Power Plant Control for Dynamic Ancillary Services Provision
Series: CSC/CommNetS-MHI Seminar Series
Abstract: This presentation focuses on innovative control strategies for dynamic virtual power plants (DVPPs) aimed at providing dynamic ancillary services efficiently. The first part highlights the importance of heterogeneity among distributed energy resources in reliably delivering services like fast frequency and voltage control across various power and energy levels. A "divide-and-conquer" approach, along with dynamic participation factors and local matching controllers, is proposed. The second part introduces a closed-loop strategy incorporating data-driven techniques to adapt ancillary services to local grid conditions. Structural encoding of dynamic ancillary services and a "perceive-and-optimize" strategy ensure stable and optimal performance while meeting grid-code and device-level requirements. Numerical case studies and hardware experiments validate the effectiveness of these approaches, promising improved grid stability and efficiency.
Biography: Verena Häberle is a Ph.D. student at the Automatic Control Laboratory, ETH Zurich, Switzerland, working under the supervision of Prof. Florian Dörfler since June 2020. She earned both her B.Sc. and M.Sc. degrees in Electrical Engineering and Information Technology from ETH Zurich in 2018 and 2020, respectively. Since Sept 2024, she is a visiting student researcher with the Netlab group at the California Institute of Technology (CALTECH), supervised by Prof. Steven Low. Her research focuses on dynamic ancillary services provision, control design for dynamic virtual power plants, and data-driven converter control for future power systems.
Host: Dr. Lars Lindemann, llindema@usc.edu
More Information: 2024.10.14 CSC Seminar - Verena Häberle.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Six Sigma Green Belt for Process Improvement Tue, Oct 15, 2024 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: USC Viterbi School of Engineering's Six Sigma Green Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Green Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's green belt exam (administered on the final day of the course).
Host: USC Viterbi Corporate and Professional Programs
Audiences: Six Sigma Green Belt Students
Contact: VASE Executive Education
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Epstein Institute, ISE 651 Seminar Class
Tue, Oct 15, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Szu Hui Ng, Associate Professor and Head of the Department of Industrial Systems Engineering and Management, University of Singapore
Talk Title: Dynamic Simulation Optimization of Chlorine Dosage in Drinking Water Distribution Systems
Host: Dr. Qiang Huang
More Information: FLYER 651 Dr. Szu Hui Ng 10.15.24.png
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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Modeling Human Motion Behaviors and 3D Environment from Real-World Capture
Tue, Oct 15, 2024 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Andrew Feng , Associate Director - Geospatial Research, USC-ICT
Talk Title: Modeling Human Motion Behaviors and 3D Environment from Real-World Capture
Abstract: Synthesizing believable human motions based on input conditions is an essential task that will find many applications in gaming, simulation, and virtual reality. Various conditional inputs can be utilized to drive the motion synthesis process such as speech, music, action categories, and natural language text descriptions. Generating motions from text prompts or speech audios requires modeling of both languages and motions, which is especially challenging as the model needs to learn a cross-modal mapping to produce motion sequences. Another challenge in learning the motion synthesis model is that the cross-modal mapping may not be deterministic. For instance, there may be multiple viable gesture motions for the same speech utterance that are all plausible. The first part of this talk will cover our research in leveraging discrete latent space learning and recent generative modeling methods to address such challenges. Our proposed method models the motion segments as discrete codes and learns the underlying data distributions for these motion units. Therefore it does not suffer from the over-smoothed or damped animations caused by the deterministic mapping of the regression models in previous methods. Modeling the real world environment from multi-view images remain significant challenges in computer vision and graphics. The resulting models need to retain both accurate visual appearances and geometry to be valuable for digital twins, simulation, or scan-to-BIM applications. 3D Gaussian Splatting (3DGS) has recently advanced the field to be a viable method for novel view synthesis and real-time rendering. The second part of the talk will cover our recent research work in 3DGS for revising the training and densification strategy to improve the radiance field and geometry reconstructions.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Andrew Feng is currently the Associate Director of Geospatial Research at USC-ICT. He leads the Terrain Research group at ICT focusing on geospatial R&D initiatives in support of the Army’s One World Terrain project. Previously, he was a research scientist working on gesture synthesis, character animation and automatic 3D avatar generation. His research work involves applying machine learning techniques to solve computer graphics problems such as 3D model reconstructions, semantic segmentations, and animation synthesis. He received his Ph.D. and M.S. degree in computer science from the University of Illinois at Urbana-Champaign.
Host: Jonathan Gratch, Research Professor
Location: Olin Hall of Engineering (OHE) - 100c
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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Six Sigma Green Belt for Process Improvement
Wed, Oct 16, 2024 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: USC Viterbi School of Engineering's Six Sigma Green Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Green Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's green belt exam (administered on the final day of the course).
Host: USC Viterbi Corporate and Professional Programs
Audiences: Six Sigma Green Belt Students
Contact: VASE Executive Education
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USC CAIS Seminar with Dr. Frederic Reamer
Wed, Oct 16, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Frederic Reamer, Professor Emeritus, School of Social Work - Rhode Island College
Talk Title: USC CAIS Seminar with Dr. Frederic Reamer
Abstract: Artificial intelligence (AI) is becoming increasingly prevalent in the behavioral health professions. AI is being used to conduct client risk assessments; assist people in crisis; strengthen prevention efforts; document clinical services; identify systemic biases in the delivery of services; provide professional education and clinical supervision; and predict practitioner burnout and service outcomes, among other uses.
This webinar will examine cutting-edge ethical issues related to behavioral health practitioners’ use of AI; apply relevant ethical standards; and outline key elements of a strategy for practitioners’ ethical use of AI. Join Dr. Frederic Reamer as he examines ethical issues and risks related to informed consent and client autonomy; privacy and confidentiality; transparency; potential client misdiagnosis; client abandonment; client surveillance; plagiarism, dishonesty, fraud, and misrepresentation; algorithmic bias and unfairness; and use of evidence-based AI tools.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Register for Zoom webinar: https://usc.zoom.us/webinar/register/WN_DC48EaIORMy9ePEE86IGiA
Biography: Frederic G. Reamer has been on the faculty of the School of Social Work, Rhode Island College since 1983. His research and teaching have addressed a wide range of human service issues, including mental health, health care, criminal justice, public welfare, and professional ethics. Dr. Reamer received his Ph.D. (social work) from the University of Chicago. He has served as a social worker in correctional and mental health settings.
He serves as Associate Editor of the National Association of Social Workers Encyclopedia of Social Work (Oxford University Press and National Association of Social Workers). Since 2012, Dr. Reamer has served as the ethics instructor in the Providence (RI) Police Department Training Academy. Dr. Reamer has conducted extensive research on professional ethics. He has published 25 books and more than 190 journal articles, book chapters, and encyclopedia articles.
Dr. Reamer is the recipient of awards such as the NASW Mit Joyner Presidential Award, NASW Social Work Pioneer Award, and NASW Excellence in Ethics Award.
Host: CAIS
More Info: https://cais.usc.edu/events/usc-cais-seminar-with-dr-frederic-reamer/
Webcast: https://usc.zoom.us/webinar/register/WN_DC48EaIORMy9ePEE86IGiALocation: Zoom Webinar
WebCast Link: https://usc.zoom.us/webinar/register/WN_DC48EaIORMy9ePEE86IGiA
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
Event Link: https://cais.usc.edu/events/usc-cais-seminar-with-dr-frederic-reamer/
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A.V. Balakrishnan Awards Ceremony - Dr. Earl H. Dowell
Wed, Oct 16, 2024 @ 02:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Earl H. Dowell, William Holland Hall Professor of the Pratt School of Engineering, Duke University
Talk Title: Fluid Structural Thermal Interaction (FSTI) in Hypersonic Flow
Abstract: When flowing fluids and deformable structures interact, they may become unstable (flutter) and if the system is nonlinear this may lead to limit cycle oscillations and even chaotic dynamics. Physical phenomena of interest include wind induced oscillations of long span bridges and tall buildings, internal flows in nuclear reactors and gas turbines, blood flow through arteries and airflow over human tongues. However historically and even today much of the progress is driven by aerospace applications including high performance flight vehicles be they aircraft, jet engines, launch vehicles, missiles or rotorcraft. Current interest in FSTI in hypersonic flow is high and will be the subject of this talk. Both experimental and theoretical (computational) work will be discussed.
Event Program
Reception 2:00PM - 2:30PM
Remarks 2:35PM - 3:15PM
Awardee Lecture 3:15PM - 4:00PM
Award Presentation 4:00PM - 4:15PM
Biography: Dr. Dowell is an elected member of the National Academy of Engineering, an Honorary Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a Fellow of the American Academy of Mechanics and the American Society of Mechanical Engineers. He has also served as Vice President for Publications and member of the Executive Committee of the Board of Directors of the AIAA; as a member of the United States Air Force Scientific Advisory Board; the Air Force Studies Board, the Aerospace Science and Engineering Board and the Board on Army Science and Technology of the National Academies; the AGARD (NATO) advisory panel for aerospace engineering, as President of the American Academy of Mechanics, as Chair of the US National Committee on Theoretical and Applied Mechanics and as Chairman of the National Council of Deans of Engineering. From the AIAA he has received the Structure, Structural Dynamics and Materials Award, the Von Karman Lectureship, the Crichlow Trust Prize and the Reed Aeronautics Award; from the ASME he has received the Spirit of St. Louis Medal, the Den Hartog Award, Lyapunov Medal and the Caughey Medal; and he has also received the Guggenheim Medal which is awarded jointly by the AIAA, ASME, AHS and SAE. He has served on the boards of visitors of several universities and is a consultant to government, industry and universities in science and technology policy and engineering education as well as on the topics of his research. Dr. Dowell research and teaching ranges over the topics of acoustics, aerodynamics, aeroelasticity, dynamics and structures. In addition to being author of over four hundred research articles, Dr. Dowell is the author or co-author of four books, "Aeroelasticity of Plates and Shells", "A Modern Course in Aeroelasticity", "Studies in Nonlinear Aeroelasticity" and “Dynamics of Very High Dimensional Systems”. Dr. Dowell received his B.S. degree from the University of Illinois and his S.M. and Sc.D. degrees from the Massachusetts Institute of Technology. Before coming to Duke as Dean of the School of Engineering, serving from 1983-1999, he taught at M.I.T. and Princeton. He has also worked with the Boeing Company.
Host: Dr. Petros Ioannou, ioannou@usc.edu
More Info: https://forms.gle/zUxvBSDsb1TCHdcEA
Location: Ronald Tutor Hall of Engineering (RTH) - RTH 526
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://forms.gle/zUxvBSDsb1TCHdcEA
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AAI-CCI-MHI Seminar on CPS
Wed, Oct 16, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alex Robey, Postdoctoral Researcher
Talk Title: Jailbreaking LLM-Controlled Robots
Series: EE598 Seminar Series
Abstract: Recent research has shown that large language models (LLMs) such as OpenAI's ChatGPT are susceptible to jailbreaking attacks, wherein malicious users fool an LLM into generating harmful content (e.g., bombbuilding instructions). However, these attacks are generally limited to eliciting text from chatbots. In contrast, we consider attacks on LLM-controlled robots, which, if jailbroken, could be manipulated into causing physical harm in the real world. Our attacks successfully jailbreak a self-driving LLM, a wheeled Clearpath Robotics Jackal robot, and, most concerningly, the commercially available Unitree Go2 robot dog. In this talk, we will walk through the recent history of jailbreaking, describe our robotic attacks, and discuss how such attacks can be mitigated to avoid the misuse of AI-powered robots.
Biography: Alex Robey is a postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University, where he is advised by J. Zico Kolter. He is also affiliated with Gray Swan, a start-up that aims to develop AI models resistant to adversarial attacks. In 2024, he received his Ph.D. from the Department of Electrical and Systems Engineering at the University of Pennsylvania, where he was advised by Hamed Hassani and George J. Pappas. He was recently named a Rising Star in Adversarial Machine Learning (AdvML) at the NeurIPS 2024 workshop on AdvML, and he was also the recipient of the Best Paper Award from the AdvML workshop at ICML 2023.
Host: Stephen Tu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Ariana Perez
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AME Seminar
Wed, Oct 16, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Ananya Balakrishna, UC Santa Barbara
Talk Title: Phase Transformations in Multifunctional Materials
Abstract: Phase transformation materials are characterized by their ability to rapidly and reversibly switch between distinct properties, such as insulating and conducting, paramagnetic and ferromagnetic, or Li-rich and Li-poor. These transformations, however, are accompanied by abrupt structural changes in the crystal lattices, which can nucleate defects, accumulate strain energy, and accelerate material decay. We investigate these transformations in multifunctional materials from the viewpoint of Ericksen’s multiple energy wells. By doing so, we identify important links between material constants, crystallographic microstructures, and macroscopic properties. This approach to understanding material behavior from the perspective of energy landscapes may suggest new ways to design materials with improved properties and lifespans. In this talk, I will present our findings on phase transformations in battery electrodes (intercalation compounds), photomechanical materials (molecular crystals), and soft magnetic alloys. Most of this work has primarily been conducted by Delin Zhang (PhD candidate at USC/AME) and Devesh Tiwari (MS from USC/AME).
Biography: Ananya Renuka Balakrishna is an Assistant Professor in the Materials Department at the University of California Santa Barbara. She received her B.Tech degree in Mechanical Engineering from the National Institute of Technology Karnataka and her Ph.D. in Solid Mechanics and Materials Engineering from the University of Oxford. Before her current appointment, she was a Lindemann Postdoctoral Fellow at MIT and the University of Minnesota and joined the faculty in the Department of Aerospace & Mechanical Engineering at the University of Southern California in 2020. Her research group develops theoretical models to understand the interplay between fundamental material constants and microstructural instabilities, and how they collectively shape the physical response of a material.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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Computational Science Distinguished Seminar Series
Thu, Oct 17, 2024 @ 09:00 AM - 10:30 AM
USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Jessica Zhang, Carnegie Mellon University
Talk Title: From neurological disorders to additive manufacturing: integrating isogeometric analysis with deep learning and digital twins
Abstract: Coupling physics-based simulation and data-driven modeling have demonstrated great power in predicting complex systems. This talk focuses on integrating an advanced finite element method called isogeometric analysis (IGA) with deep learning and digital twins to address challenging problems in investigating neurological disorders and additive manufacturing (AM). To investigate neurodevelopmental disorders, we introduce a novel phase field model coupled with tubulin and synaptogenesis concentration to simulate intricate neurite outgrowth and disorders using IGA, dynamic domain expansion and local refinement. By integrating IGA and convolutional neural networks, we conduct thorough investigations into the functional role of various parameters affecting the neurodevelopmental disorder with comparison to experimental results. To investigate intracellular transport induced neurodegenerative disorders, we develop a PDE-constrained optimization model to simulate traffic jams induced by microtubule reduction and swirl. We also build a novel IGA-based physics-informed graph neural network to quickly predict normal and abnormal transport phenomena in complex neuron geometries.
In the second half of the talk, I will present our latest research on generative manufacturing or combining AI with IGA for AM applications. It includes a machine learning framework for inverse design and manufacturing of self-assembling fiber-reinforced composites in 4D printing, IGA-based topology optimization for AM of heat exchangers, as well as data-driven residual deformation prediction to enhance metal component printability and lattice support structure design in the laser powder bed fusion (LPBF) AM process. By speeding up geometry distortion predictions from several hours to mere seconds with uncertainty quantification, our model can be deployed to prevent generation of infeasible designs. Our on-going efforts also include developing digital twins to enable prediction and control of process parameters in LPBF manufacturing, where reduced order modeling is one key technique to efficiently simulate underlying physics.
Biography: Jessica Zhang is the George Tallman Ladd and Florence Barrett Ladd Professor of Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Biomedical Engineering. She received her B.Eng. in Automotive Engineering, and M.Eng. in Engineering Mechanics from Tsinghua University, China; and M.Eng. in Aerospace Engineering and Engineering Mechanics and Ph.D. in Computational Engineering and Sciences from Institute for Computational Engineering and Sciences (now Oden Institute), The University of Texas at Austin. Her research interests include computational geometry, isogeometric analysis, finite element method, data-driven simulation, image processing, and their applications in computational biomedicine and engineering. Zhang has co-authored over 230 publications in peer-reviewed journals and conference proceedings and received several Best Paper Awards. She published a book entitled “Geometric Modeling and Mesh Generation from Scanned Images” with CRC Press, Taylor & Francis Group. Zhang is the recipient of Simons Visiting Professorship from Mathematisches Forschungsinstitut Oberwolfach of Germany, US Presidential Early Career Award for Scientists and Engineers, NSF CAREER Award, Office of Naval Research Young Investigator Award, and USACM Gallagher Young Investigator Award. At CMU, she received David P. Casasent Outstanding Research Award, George Tallman Ladd and Florence Barrett Ladd Professorship, Clarence H. Adamson Career Faculty Fellow in Mechanical Engineering, Donald
L. & Rhonda Struminger Faculty Fellow, and George Tallman Ladd Research Award. She is a Fellow of ASME, SIAM, IACM, USACM, IAMBE, AIMBE, SMA, and ELATES at Drexel. She is the Editor-in-Chief of Engineering with Computers.
Host: The School of Advanced Computing
More Info: https://sac.usc.edu/events/
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://sac.usc.edu/events/
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Six Sigma Green Belt for Process Improvement
Thu, Oct 17, 2024 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Speaker: IISE Faculty, IISE Faculty
Talk Title: Six Sigma Green Belt for Process Improvement
Abstract: USC Viterbi School of Engineering's Six Sigma Green Belt for Process Improvement, offered in partnership with the Institute of Industrial and Systems Engineers, allows professionals to learn how to integrate principles of business, statistics, and engineering to achieve tangible results. Master the use of Six Sigma to quantify the critical quality issues in your company. Once the issues have been quantified, statistics can be applied to provide probabilities of success and failure. Six Sigma methods increase productivity and enhance quality. As a USC Six Sigma Green Belt, you will be equipped to support and champion a Six Sigma implementation in your organization. To earn the USC Six Sigma Green Belt Certificate, you will be required to pass the Institute of Industrial and Systems Engineer's green belt exam (administered on the final day of the course).
Host: USC Viterbi Corporate and Professional Programs
Audiences: Six Sigma Green Belt Students
Contact: VASE Executive Education
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Oct 18, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: David Issadore, Ph.D., Professor of UPenn
Talk Title: Diagnosing disease on a microchip: Finding nanoscale needles in messy nanoscale haystacks
Abstract: The transformative growth in microelectronics in the latter half of the 20th century was fueled fundamentally by the ability to miniaturize complex circuits onto chips. The impact of this has been profound– computing is pervasive and portable and communication is instant and global. My research aims to harness this same engineering approach to solve high impact problems in medical diagnostics. To accomplish this goal my lab develops hybrid microchips, where microfluidics are built directly on top of semiconductor chips. In this talk I will focus on recent work at Penn on 'digital asays.' Digital assays — in which ultra-sensitive molecular measurements are made by performing millions of parallel experiments in picoliter droplets — have generated enormous enthusiasm due to their single molecule resolution. These assays have incredible untapped potential for disease diagnostics but are currently confined to laboratory settings due to the instrumentation necessary to generate, control, and measure tens of millions of droplets. To overcome this challenge, we are developing a hybrid microelectronic / microfluidic chip to ‘unlock’ droplet-based assays for mobile use. Our microDroplet Megascale Detector (µMD) takes inspiration from cellular networks, in which phones are identified by their carrier frequency and not their particular location. In collaboration with physicians at The Abramson Cancer Center, we are demonstrating the power of this approach by developing a multiplexed extracellular vesicle-based diagnostic for the early detection of pancreatic cancer. I will also discuss ongoing projects on the early diagnosis of lung cancer, treatment guidance for traumatic brain injury, and the differential diagnosis of Alzheimer's versus Lewy body dementia.
Biography: The Issadore lab combines microelectronics, microfluidics, nanomaterials, and machine learning to solve big problems in healthcare. We create miniaturized platforms for the diagnosis of disease, we develop new platforms to manufacture micro and nanomaterials, and we dip our toes into an assortment of other areas where we can leverage our engineering training to improve healthcare. This work requires an interdisciplinary approach in which engineers, scientists, and physicians work together in teams. David received his PhD in applied physics from Harvard and his BS in both electrical engineering and physics from Penn State. Before coming to Penn, where he is now a Professor of Bioengineering, he was a postdoctoral fellow at MGH's Department of Systems Biology.
Host: Maral Mousavi
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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AI Seminar- Why Are Human Laws So Difficult For AI to Follow?
Fri, Oct 18, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: John Licato, University of South Florida
Talk Title: Why Are Human Laws So Difficult For AI to Follow?
Abstract: Join Zoom Meeting: https://usc.zoom.us/j/96076927864?pwd=tOuC1grLlyiRgcwicpm9e7XziHgE0R.1 Meeting ID: 960 7692 7864 Passcode: 810249 Register in advance for this webinar: https://usc.zoom.us/webinar/register/WN_ANEShGxrSfeTwa5sFZsRag Although it is now incredibly easy to create and deploy a chatbot for almost any application, powered by highly capable LLMs, even the best systems still tend to perform poorly when they need to interpret and reason about rules---specifically, rules expressed in the kind of language found in laws, contracts, regulations, and the like. Why does this problem still exist, and how can it be overcome? Dr. Licato argues that the problem is rooted in a feature (not a bug) of human languages called open-texturedness. And this open-texturedness, because it is an inevitable feature of normative rule systems, must be addressed by any agent-level AI system, especially if we want it to be able to follow our laws.
Biography: John Licato, PhD is an Associate Professor of Computer Science and Engineering at USF, Director of the USF Advancing Machine and Human Reasoning (AMHR) Lab, and founder of AI startup Actualization AI, LLC. He designed and teaches the natural language processing course (the field that created ChatGPT) at USF, and his lab's mission is to not only make AI smarter, but to use those advances to make people reason better as well. His research expertise lies in AI, NLP, human reasoning, cognitive modeling, and legal / regulatory reasoning, with over 100 peer-reviewed publications. He has been featured in outlets such as NPR's Marketplace Tech, ABC Action News, and the Tampa Bay Business Journal. If speaker approves to be recorded for this AI Seminar talk, it will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.
Host: Abel Salinas and Pete Zamar
More Info: https://www.isi.edu/events/5149/why-are-human-laws-so-difficult-for-ai-to-follow/
Webcast: https://www.youtube.com/watch?v=CmNz7hAAtLsLocation: Information Science Institute (ISI) - Virtual Only
WebCast Link: https://www.youtube.com/watch?v=CmNz7hAAtLs
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/events/5149/why-are-human-laws-so-difficult-for-ai-to-follow/
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MHI ISSS Seminar - Dr. Ioannis Savidis, Friday, October 18th at 2pm in EEB 132
Fri, Oct 18, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ioannis Savidis, Associate Professor, Drexel University
Talk Title: AI/ML for EDA: Learning Algorithms in Analog and Digital Design
Series: Integrated Systems
Abstract: In the ever-evolving landscape of Electronic Design Automation (EDA), the integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms with traditional heuristic optimization algorithms has emerged as a transformative force in automated circuit design. This presentation delves into the dynamic intersection of AI/ML and EDA, exploring state-of-the-art techniques shaping the analog and digital physical design space. Machine learning, specifically deep learning, has the potential to significantly improve the accuracy, speed, efficiency, and reliability of EDA tasks such as circuit modeling, simulation, layout design, and optimization. Delving into such cutting-edge advancements, I will describe current AI/ML research performed by the ICE Lab that promises to transcend traditional paradigms, with the goal of enabling designers to navigate complexities with unparalleled efficiency and accuracy. Specifically, a focus on state-of-the-art learning and optimization techniques for the modeling and design of mixed-signal ICs will be presented and discussed. Practical considerations, challenges, and opportunities of ML algorithms for analog and digital circuit design will be discussed, with a focus on the use of such algorithms for prediction and optimization tasks within the EDA design flow.
Biography: Dr. Ioannis Savidis (S'03-M'13-SM'18) is an Associate Professor in the Department of Electrical and Computer Engineering at Drexel University, where he directs the Integrated Circuits and Electronics (ICE) Design and Analysis Laboratory. He received his B.S.E. from Duke University in 2005, and his M.Sc. and Ph.D. from the University of Rochester in 2007 and 2013, respectively. Dr. Savidis has authored over 130 technical papers in peer-reviewed journals and conferences, including a book on Three-Dimensional Integrated Circuit Design and holds 16 issued and five pending patents. His research interests include high-performance digital and mixed-signal integrated circuits, power management for SoC and microprocessor circuits, hardware security, AI/ML algorithms for circuit optimization, and electro-thermal modeling for 2-D and 3-D circuits. Dr. Savidis is a senior member of IEEE and has received two Best Paper Awards, the 2018 NSF CAREER Award, and the 2019 DoD DURIP Award. He serves on organizing committees for several conferences including IEEE HOST, ACM GLSVLSI, and IEEE ISCAS, and on technical program committees for DAC, ICCAD, MLCAD, and others. Dr. Savidis is a member of the VLSI Systems and Applications Technical Committee of the IEEE Circuits and Systems Society and serves on the editorial boards of IEEE Transactions on VLSI Systems, Microelectronics Journal, and ACM Transactions on Design Automation of Electronic Systems.
Host: Hossein Hashemi, Mike Chen and Constantine Sideris
Webcast: https://usc.zoom.us/j/94304141343More Information: MHI_Seminar_Flyer_Savidis_Oct18_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/94304141343
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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CSC/CommNetS-MHI Seminar: Murat Arcak
Mon, Oct 21, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Murat Arcak, Professor of Electrical Engineering and Computer Sciences | University of California, Berkeley
Talk Title: Data-Driven Approaches for Estimating Reachable Sets in Complex Dynamical Systems
Series: CSC/CommNetS-MHI Seminar Series
Abstract: The computation of reachable sets is essential for characterizing and verifying the behavior of safety-critical systems. However, many practical systems are high-dimensional and analytically intractable, making the exact computation of reachable sets difficult or impossible. We propose a data-driven approach that uses a finite ensemble of sample trajectories to estimate reachable sets with probabilistic accuracy guarantees. This method is broadly applicable and computationally advantageous, as the main cost comes from simulating a predetermined number of trajectories, which can be parallelized to reduce computation time. We first present a method that uses scenario optimization to construct reachable set estimates as approximate solutions to chance-constrained optimization problems. Next, we use a class of polynomials derived from empirical moment matrices, whose sublevel sets act as nonconvex estimates of the reachable set. These data-driven methods offer scalable solutions for estimating reachable sets in systems with complex dynamics.
Biography: Murat Arcak is a professor at the University of California, Berkeley, where he holds the Robert M. Saunders Endowed Chair. He has a primary appointment in Electrical Engineering and Computer Sciences, and a courtesy appointment in Mechanical Engineering. He earned his B.S. degree in Electrical Engineering from BoÄaziçi University, Istanbul, Turkey, in 1996, and his M.S. and Ph.D. degrees from the University of California, Santa Barbara, in 1997 and 2000. His research focuses on dynamical systems and control theory, with applications in multi-agent systems and transportation. He received a CAREER Award from the National Science Foundation in 2003, the Donald P. Eckman Award from the American Automatic Control Council in 2006, the Control and Systems Theory Prize from the Society for Industrial and Applied Mathematics (SIAM) in 2007, and the Antonio Ruberti Young Researcher Prize from the IEEE Control Systems Society in 2014. He is a member of ACM and SIAM, and a fellow of both IEEE and the International Federation of Automatic Control (IFAC)
Host: Dr. Lars Lindemann, llindema@usc.edu
More Information: 2024.10.21 CSC Seminar - Murat Arcak.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Computational Science Distinguished Seminar Series
Tue, Oct 22, 2024 @ 09:00 AM - 10:30 AM
USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Vikram Gavini, University of Michigan
Talk Title: Large-scale electronic structure calculations of extended defects in materials
Abstract: Defects play a crucial role in influencing the macroscopic properties of solids—examples include the role of dislocations in plastic deformation, dopants in semiconductor properties, and domain walls in ferroelectric properties. These defects are present in very small concentrations (few parts per million), yet, produce a significant macroscopic effect on the materials behavior through the long-ranged elastic and electrostatic fields they generate. Notably, the strength and nature of these fields, as well as other critical aspects of the defect-core are all determined by the electronic structure of the material at the quantum-mechanical length-scale. However, carefully converged electronic structure studies on extended defects, such as dislocations, have been out of reach due to the cell-size and periodicity limitations of the widely used electronic structure codes.
This talk will discuss the recent developments that have enabled large-scale density functional theory (DFT) calculations, paving the way for electronic structure studies of defects. The first part of the talk will discuss the development of computational methods and numerical algorithms for conducting fast and accurate large-scale DFT calculations using adaptive finite-element discretization, which form the basis for the recently released DFT-FE open-source code. The second part of the talk will focus on electronic structure studies of dislocations using the developed methods and the insights obtained into fundamental questions such as: What is the core size of a dislocation? Are forces on dislocations solely from elastic interactions? Recent studies on using DFT-FE to understand the energetics of <c+a> dislocations in Mg, and the energetics and nucleation kinetics of quasicrystals (ScZn7.33) will be discussed
Biography: Vikram Gavini is Professor of Mechanical Engineering and Materials Science & Engineering at the University of Michigan. He received his Ph.D. from California Institute of Technology in 2007. His interests are in developing methods for large-scale and quantum-accurate electronic structure calculations, numerical analysis of PDEs and scientific computing. DFT-FE, a massively parallel open-source code for large-scale real-space DFT calculations, has been developed in his group. He is the recipient of NSF CAREER Award in 2011, AFOSR Young Investigator Award in 2013, Humboldt Research Fellowship for Experienced Researchers (2012-14), USACM Gallagher Award in 2015, among others. He led the team that received the 2023 ACM Gordon Bell Prize in high performance computing.
Host: The School of Advanced Computing
More Info: https://sac.usc.edu/events/
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://sac.usc.edu/events/
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ECE Seminar: A plug-and-play acceleration framework for generative AI models on the edge
Tue, Oct 22, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yanzhi Wang, Associate Professor and Faculty Fellow, Dept. of ECE, Northeastern University
Talk Title: A plug-and-play acceleration framework for generative AI models on the edge
Abstract: In the generative AI era, general users need to apply different base models, fine tuned checkpoints, and LoRAs. Also the data privacy and real-time requirement will favor on-device, local deployment of large-scale generative AI models. It is desirable to develop a "plug-and-play" framework such that users can download any generative AI model, click and run on their own device. This poses significant challenge to the current AI deployment frameworks, which are typically time-consuming and requires human expertise of hardware and code generation. We present our effort of OminiX, which is a first step towards unified library and acceleration of generative AI models across various hardware platforms. Integrating our unique front-end library and back-end instantaneous acceleration techniques, which will be open-source soon, we show capability of plug-and-play deployment and state-of-the-art acceleration of various generative AI models, starting from image generation, large language models, multi-model language models, speech generation and voice cloning, real-time chatting engine, real-time translation, video generation, real-time avatar, to name a few. This can be achieved on everyone's own platform.
Biography: Yanzhi Wang is Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University, a senior member of IEEE. His research interests focus on real-time and energy-efficient deep learning and artificial intelligence systems, especially on efficient large language models and large-scale generative AI systems. His research works have been published broadly in (i) machine learning conferences such as AAAI, CVPR, NeurIPS, ICML, ICCV, ICLR, IJCAI, ECCV, KDD, ICRA, ACM MM, ICDM, etc., (ii) architecture and system conferences such as ASPLOS, ISCA, MICRO, HPCA, CCS, VLDB, PLDI, WWW, ICS, PACT, CGO, IPDPS, INFOCOM, ICDCS, DAC, ICCAD, FPGA, FCCM, ISSCC, CICC, RTAS, RTSS, etc., and (iii) IEEE and ACM transactions. His research works have been cited over 20,500 times. He has received six Best Paper Awards and another 12 Best Paper Nominations. He has received the U.S. Army Research Office Young Investigator Program Award (YIP), IEEE TC-SDM Early Career Award, Asia Pacific Signal and Information Processing Association Distinguished Leader Award, Massachusetts Acorn Innovation Award, design contest awards from multiple conferences, and other research awards from Google, MathWorks, etc. His research work has been reported and cited by around 500 media. He has 13 academic descendants as tenure-track faculty members at University of Minnesota, Michigan State University, University of Georgia, Clemson University, etc.
Host: Dr. Sandeep Gupta, sandeep@usc.edu
Webcast: https://usc.zoom.us/j/98817797740?pwd=OfzLgQ5S1Gbb7b7mxxXe9FgST9u99L.1 (USC NetID Login Required)Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/98817797740?pwd=OfzLgQ5S1Gbb7b7mxxXe9FgST9u99L.1 (USC NetID Login Required)
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Generative Models and the Transport of Measure
Tue, Oct 22, 2024 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Gavin Kerrigan, PhD Candidate - Department of Computer Science, UC Irvine
Talk Title: Generative Models and the Transport of Measure
Abstract: A key theme in contemporary generative modeling is the continuous transport of measure, in which a simple reference distribution is gradually transformed into the data distribution. Many recent models, including diffusions and flows, can be viewed through this unifying lens. In this talk, we will first explore some geometric tools for studying dynamics in the space of probability measures. We will then leverage these tools to design generative models, with a focus on applications to inverse problems and complex data structures such as function-valued data.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
In-person ONLY; recording available post-presentation.
Biography: Gavin Kerrigan is a final year PhD candidate in the Department of Computer Science at UC Irvine, where he is advised by Padhraic Smyth. Prior to joining UCI, he obtained a BSc in mathematics from the Schreyer Honors College at Penn State University. His research focuses on advancing the theory and practice of deep generative models, ranging from fundamental methodology to applications in climate science. His work has been recognized through a best paper award at AISTATS'23 for contributions to function-space generative modeling.
Host: USC Machine Learning Center
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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The Algorithmic Abyss: Exploring Autonomy without Robotic Horror
Tue, Oct 22, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Juan Wachs , Professor & University Faculty Scholar, Industrial Engineering School - Purdue University
Talk Title: The Algorithmic Abyss: Exploring Autonomy without Robotic Horror
Abstract: Robots can already solve sophisticated problems ranging from playing games, autonomous driving, and dancing—given enough observational data for training. The core of such success resides in efficient algorithms, compliant hardware and robust computing, all implemented using carefully curated data collected before the training phase. Thus, robots learn in a “sterile” domain, under clean, controlled and to some extent supervised environments. As the target domain changes, however, moving to more quotidian scenarios, robots struggle to perform well. It is hard to think of an autonomous car trained in Silicon Valley being able to successfully navigate the crowded streets of New Delhi. – this is the “algorithm abyss”. Ideally, we would like to robots adapt to challenging settings while immersed in mundane settings, and learn from few observations. To address this hurdle, my work in the area of robotics and autonomous systems focuses on transferring skills and knowledge from controlled settings to the wild. In this talk, I emphasize strategies and techniques to address fundamental challenges in emergent, high-risk, high-stakes scenarios. Specifically, I will discuss work related to telesurgery, skill augmentation and bioinspired designs. While healthcare is one of the research domains discussed, the outcomes and findings are applicable to the range field of autonomous robotics. Progress in these directions will contribute to the public purpose of creating the knowledge for developing robots that are more accessible, effective and sensitive to social needs.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Zoom Details: https://usc.zoom.us/j/99548396089
Biography: Dr. Juan Wachs is a Professor and University Faculty Scholar in the Industrial Engineering School at Purdue University, Professor of Biomedical Engineering (by courtesy), an Adjunct Associate Professor of Surgery at IU School of Medicine, and Adjunct Professor at Johns Hopkins University. He recently served at NSF as a Program Director for Robotics and AI programs at CISE. He is also the director of the Intelligent Systems and Assistive Technologies (ISAT) Lab at Purdue, and he is affiliated with the Regenstrief Center for Healthcare Engineering. He completed postdoctoral training at the Naval Postgraduate School’s MOVES Institute under a National Research Council Fellowship from the National Academies of Sciences. Dr. Wachs received his B.Ed.Tech in Electrical Education in ORT Academic College, at the Hebrew University of Jerusalem campus. His M.Sc and Ph.D in Industrial Engineering and Management from the Ben-Gurion University of the Negev, Israel. He is the recipient of the 2013 Air Force Young Investigator Award, and the 2015 Helmsley Senior Scientist Fellow, and 2016 Fulbright U.S. Scholar, the James A. and Sharon M. Tompkins Rising Star Associate Professor, 2017, and the ACM Distinguished Speaker 2018. Since 2020 he has been elected University Faculty Scholar. He is also the Associate Editor of IEEE Transactions in Human-Machine Systems, Frontiers in Robotics and AI.
Host: Prof. Stefanos Nikolaidis
Webcast: https://usc.zoom.us/j/99548396089Location: Ronald Tutor Hall of Engineering (RTH) - 217
WebCast Link: https://usc.zoom.us/j/99548396089
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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**No Epstein Institute, ISE 651 Seminar Class - Due to INFORMS**
Tue, Oct 22, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: NO CLASS- INFORMS, NO CLASS- INFORMS
Talk Title: NO CLASS-INFORMS
Host: NO CLASS- INFORMS
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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The Critical Role of Cyber Infrastructure in City Innovation and Beyond
Wed, Oct 23, 2024 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Zhenhui (Jessie) Li , Chief Scientist - Yunqi Academy of Engineering
Talk Title: The Critical Role of Cyber Infrastructure in City Innovation and Beyond
Abstract: Cities, humanity’s greatest inventions, offer vast opportunities for innovation in science and technology. The increasing availability of big data paints a promising future for our cities. Over the past decade, my work has focused on applying AI to address real-world city challenges. Recent collaborations with city practitioners have deepened my understanding of these complexities and refined my vision for achieving city intelligence.
In this talk, I will present my work on advanced AI techniques for city transportation problems, e.g., reinforcement learning for traffic signal control. I will then expand on this to discuss the resource-centric concept of city intelligence, using real-world practices to showcase its practical applications. Finally, I will emphasize the urgent need for new cyber infrastructure, vital not only for city innovations but for all scientific disciplines driven by big data and intensive computing.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
**Lecture will be in-person ONLY
Biography: Dr. Zhenhui (Jessie) Li currently serves as the Chief Scientist at the Yunqi Academy of Engineering, a non-profit institution situated in Hangzhou, China. Prior to this role, she held a tenured associate professor position at Pennsylvania State University. She earned her doctoral degree in Computer Science from the University of Illinois at Urbana-Champaign. Her research primarily focuses on advancing computing technologies to harness data for interdisciplinary studies, including those in smart city, environmental science, transportation, and ecology. For further information, you can visit her website at (https://jessielzh.com/).
Host: Machine Learning Center
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Machine Learning Center
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AME Seminar
Wed, Oct 23, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Jian Cao, Northwestern
Talk Title: Physics-based AI-assisted Design and Control of Manufacturing Processes
Abstract: Current research efforts at my manufacturing group aim to advance the capability to co-design materials and manufacturing processes using hybrid physics-based and data-driven approaches. In this talk, I will demonstrate our work in the development of differentiable simulation tools, sensing, and process control to achieve effective and efficient predictions and control of a material’s mechanical behavior in metal additive manufacturing processes. Furthermore, I will show how we use machine learning to accelerate the physics-based simulations and to realize active sensing with the goal of effective in-situ local process control. Our solutions particularly target three notoriously challenging aspects of the process: long history-dependent properties, complex geometric features, and the high dimensionality of their design space. The approaches are applicable to other manufacturing processes as well, such as flexible incremental forming.
Biography: Cardiss Collins Professor Jian Cao (MIT’Ph.D, MIT’MS, SJTU’BS) specialized in innovative manufacturing processes and systems, particularly in the areas of deformation-based processes and laser additive manufacturing processes. She is the Founding Director of the research center on Manufacturing Science and Innovation at Northwestern, known as NIMSI.
Prof. Cao is an elected member of the National Academy of Engineering (NAE) and of the American Academy of Arts and Sciences (AAA&S). She is a Fellow of American Association for the Advancement of Science (AAAS), ASME, the International Academy for Production Engineering (CIRP) and SME. Her major awards include DoD Vannevar Bush Faculty Fellowship, ASME Ted Belytschko Applied Mechanics Award, the inaugural ASME Devor-Kapoor Manufacturing Medal, Hideo Hanafusa Outstanding Investigator Award for Flexible Automation, ASME Milton C. Shaw Manufacturing Research Medal, Charles Russ Richards Memorial Award from ASME and Pi Tau Sigma, SME Gold Medal, and SME Frederick W. Taylor Research Medal. Cao was the Editor-in-Chief of Journal of Materials Processing Technology.
Prof. Cao now serves as an Associate Vice President for Research at Northwestern, a member of the National Materials and Manufacturing Board of the National Academies, a member of the Defense Materials, Manufacturing and its Infrastructure (DMMI) Standing Committee of the National Academies, Board of Directors of SME, and Board of mHUB – accelerator for hardtech innovation and manufacturing in Chicago.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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ECE Pioneer Series: Ming Hsieh
Wed, Oct 23, 2024 @ 03:30 PM - 05:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ming Hsieh, Entrepreneur and Philanthropist
Talk Title: From Rural Northeastern China to the American National Academy of Engineering: The Transformative Journey of a Young Boy Empowered by Interdisciplinary Electrophysics & Electrical Systems Education
Series: ECE Pioneer Series
Abstract: This seminar traces the transformative journey of Ming Hsieh, from his early education in rural Northeastern China to becoming a distinguished member of the American National Academy of Engineering. Hsieh’s passion for engineering began at the age of 14 in 1970, deeply influenced by his father, an electrical engineer and scientist, who was dedicated to bringing electricity to rural villages in Northern China. Beginning his studies in Semiconductor Physics/Devices at Southern China University of Technology in 1978, Hsieh shifted his academic focus after transferring to the University of Southern California (USC) in 1981. Under the mentorship of Professor Kurt Lehovec in the Electrical Engineering (EE) Electrophysics group, Hsieh integrated the disciplines of electrophysics and electrical systems. This interdisciplinary education laid the foundation for his professional career, where he pioneered innovations at the intersection of physics and systems. His work, ranging from deploying large-scale biometric systems to accelerating breakthroughs in biomedical research and cancer therapeutics, demonstrates the transformative power of a unified approach to engineering and science. Through his story, Hsieh exemplifies how a robust, interdisciplinary education can lead to groundbreaking advancements with a global impact.
Biography: Ming Hsieh, BSEE ’83, MSEE ’84, is co-founder, president, CEO and chairman of the board of Cogent, Inc., one of the top providers of fingerprint identification systems in the United States. His generous gift of $35 million was the largest ever to name an engineering department in the United States. Ten years later, his endowment continues to set the course for electrical engineering’s expansion into new realms of human invention. As our field grows, so too does the quality of our academic standards and the ability of our graduates to meet the challenges of today's global community.
Below is a sampling of stories and events related to Dr. Hsieh:
Greatest Hits, Vol. 1 (2006-2016): The Ming Hsieh Department of Electrical and Computer Engineering - Read about some of our department's greatest achievements in the decade since Ming Hsieh's gift. https://magazine.viterbi.usc.edu/fall-2016/whats-next/greatest-hits-vol-1-2006-2016-the-ming-hsieh-department-of-electrical-engineering/
Q+A: Ming Hsieh - On the 10th anniversary of his naming gift to the USC Viterbi Ming Hsieh Department of Electrical and Computer Engineering, Ming Hsieh spoke about the department, cancer research and his desire to give back. https://magazine.viterbi.usc.edu/fall-2016/whats-next/qa-ming-hsieh/
Putting a Fingerprint on Electrical Engineering - Cogent, Inc. co-founder and Viterbi School alumnus Ming Hsieh has given $35 million to name the School's oldest and most prominent department. Read this cover story about him from the Fall/Winter 2006 USC Viterbi Engineer magazine. https://viterbi.usc.edu/news/news/2006/putting-a-fingerprint.htm
Viterbi School Celebrates a Momentous Gift to Name the Department of Electrical and Computer Engineering - The Viterbi School celebrates a record-breaking gift and naming of the third department in its history at a red-carpet ceremony held in the Ronald Tutor Hall Courtyard. https://viterbi.usc.edu/news/news/2006/usc-alumnus-ming.htm
Host: Dr. Richard Leahy, leahy@usc.edu
More Information: Screenshot 2024-10-23 at 10.59.36 AM.png
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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NL Seminar-Mission: Impossible Language Models
Thu, Oct 24, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Julie Kallini, Stanford University
Talk Title: Mission: Impossible Language Models
Abstract: REMINDER: Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please inform us at (nlg-seminar-host(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins. If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location. ZOOM INFO: https://usc.zoom.us/j/97400245543?pwd=uo9TL9Ss4TA4Wa4TPtfDQnedE7Va8B.1 Meeting ID: 974 0024 5543 Passcode: 407395 Chomsky and others have very directly claimed that large language models (LLMs) are equally capable of learning languages that are possible and impossible for humans to learn. However, there is very little published experimental evidence to support such a claim. Here, we develop a set of synthetic impossible languages of differing complexity, each designed by systematically altering English data with unnatural word orders and grammar rules. These languages lie on an impossibility continuum: at one end are languages that are inherently impossible, such as random and irreversible shuffles of English words, and on the other, languages that may not be intuitively impossible but are often considered so in linguistics, particularly those with rules based on counting word positions. We report on a wide range of evaluations to assess the capacity of GPT-2 small models to learn these uncontroversially impossible languages, and crucially, we perform these assessments at various stages throughout training to compare the learning process for each language. Our core finding is that GPT-2 struggles to learn impossible languages when compared to English as a control, challenging the core claim. More importantly, we hope our approach opens up a productive line of inquiry in which different LLM architectures are tested on a variety of impossible languages in an effort to learn more about how LLMs can be used as tools for these cognitive and typological investigations.
Biography: Julie Kallini is a second-year Computer Science Ph.D. student at Stanford University advised by Christopher Potts and Dan Jurafsky. Her research spans several topics in natural language processing, including computational linguistics, cognitive science, interpretability, and model architecture. Julie's work is generously supported by the NSF Graduate Research Fellowship, the Stanford School of Engineering Graduate Fellowship, and the Stanford EDGE Fellowship. Before starting her Ph.D., Julie was a software engineer at Meta, where she worked on machine learning for advertisements. Julie graduated summa cum laude from Princeton University with a B.S.E. in Computer Science and a minor in Linguistics.
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://www.youtube.com/watch?v=sDMUu8rrgV8Location: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=sDMUu8rrgV8
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Oct 25, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Summer Decker and Dr. Jonathan Ford, Director Center for Innovation in Medical Visualization Grace Whisler Endowed Professor in Medicine Professor of Clinical Radiology, Surgery, and Pathology/ Dr. Ford, Associate Director of the Center and Associate Professor in Clinical Radiology, Surgery,
Talk Title: Personalized Medicine for a 3D Patient
Abstract: 3D medical technologies are revolutionizing healthcare and allowing for more personalized medicine and rapid innovation in the hospital setting. New USC faculty members, Dr. Summer Decker and Dr. Jonathan Ford, established one of the nation’s most recognized point-of- care 3D teams at the University of South Florida Morsani College of Medicine. They will present on their work in validating the technologies, their medical innovations, and clinical impact as well as discuss their new USC Center for Innovation in Medical Visualization in the Keck School of Medicine.
Biography: Dr. Summer Decker - Biography
Summer J. Decker, PhD, is the inaugural director of the Center for Innovation in Medical Visualization at the University of Southern California’s Keck School of Medicine as where she is the Grace Whisler Endowed Professor in Medicine and holds appointments in Clinical Radiology, Surgery and Pathology.
Dr. Decker graduated with her doctorate in medical sciences from the University of South Florida Morsani College of Medicine in 2010 specializing in Pathology and Medical Imaging (Clinical Radiology) and then spent 12 years as the founder and director of the 3D Clinical Applications Division in the USF Health Department of Radiology at Tampa General Hospital. She served as the department’s Vice Chair of Radiology for Research and Innovation and associate radiology residency program director. She also held appointments in the Departments of Surgery, Plastic Surgery, and Pathology as well as in the USF College of Engineering’s Department of Medical Engineering. Their 3D team worked with physicians at Tampa General Hospital, Moffitt Cancer Center, Johns Hopkins All Children’s Hospital, as well as the James A Haley VA and Bay Pine VA hospitals. Under her leadership, the USF/TGH 3D Clinical Applications lab gained world renown as one of the most innovative 3D medical labs globally.
During the COVID-19 pandemic, Dr. Decker led a national team that designed and developed a 3D printed nasopharyngeal swab for COVID diagnostics to address the international crisis in testing due to global supply chain shortages, which has been used in more than 60 countries. It was recognized by Fast Company’s the 2021 World Changing Idea Award finalist. For her work, she has won several humanitarian awards including the United States Patent and Technology Office’s 2023 Patents for Humanity Award, the Arthur P. Gold Foundation 2021 National Champions of Healthcare award, as well as the International FormLabs Impact Award for her work’s impact on humanity and healthcare through 3D technologies.
Dr. Decker serves on the Board of the International Society of Forensic Radiology and Imaging where she is the senior associate editor for the journal Forensic Imaging and associate editor of the journal, 3D Printing in Medicine. She was appointed to the Radiological Society of North America (RSNA)’s Science Council and serves as the co-chair of the RSNA’s Vice Chairs for Research Committee. She currently serves on the Board as Vice Chair of the RSNA’s 3D Special Interest Group where she leads also leads the Education Committee, as well as the president-elect for the Association of Academic Radiology (AAR)’s Radiology Research Alliance. She currently serves as a 3D Printing Advisor for the American College of Radiology’s Committee on Reimbursement.
Dr. Jonathan Ford - Biography
Dr. Jonathan Ford is the inaugural associate director of the Center for Advanced Visualization Technologies in Medicine at the University of Southern California’s Keck School of Medicine He holds appointments in Clinical Radiology, Surgery and Pathology as an associate professor. He also holds appointments in the USC Viterbi School of Engineering and USC School of Cinematic Arts.
Dr. Ford graduated with his doctorate in Engineering from the University of South Florida College of Engineering in 2013 specializing Biomedical Engineering. He then spent over 10 years as the technical director of the 3D Clinical Applications Division in the Department of Radiology at the University of South Florida Morsani College of Medicine and Tampa General Hospital. He also held an associate professor appointment in the USF College of Engineering, Department of Medical Engineering. The team, led by Dr. Summer Decker, worked with physicians at Tampa General Hospital, Moffitt Cancer Center, Johns Hopkins All Children’s Hospital, as well as the James A. Haley VA and Bay Pine VA hospitals.
He holds multiple patents from his work in 3D modeling and printing. He also serves as an advisor for numerous industry and society committees such as the Society of Manufacturing Engineers (SME) where he helps lead the Healthcare Additive Manufacturing Advisory Group. His work has won international awards and recognitions including the International FormLabs Impact Award for his work’s impact on humanity and healthcare through 3D technologies
Working with Dr. Decker as a team for more than a decade, they have been able to build their 3D Clinical Applications lab into one of the most innovative 3D medical labs globally.
Host: Qifa Zhou
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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Program Analysis for Block-Based Learners Programs
Fri, Oct 25, 2024 @ 11:00 AM - 12:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Prof. Gordon Fraser, PhD, Computer Science Professor - University of Passau, Germany
Talk Title: Program Analysis for Block-Based Learners Programs
Abstract: Programming is increasingly taught using dedicated block-based programming environments such as Scratch. While the use of blocks instead of text prevents syntax errors, learners can still make semantic mistakes implying a need for feedback and help. While professional programmers receive this support from efficient program analyses built into their IDEs, block-based programming environments offer no such support. In this talk I will describe some of our efforts to remedy this issue, ranging from static source code linting, search-based testing, interrogative debugging, automated program repair, to neural program analysis. The colourful and small nature of learners’ programs is deceiving, as the game-like, highly concurrent and event-driven nature of the programs poses unique challenges for these analyses.
This lecture satisfies the requirements for CSCI 591: Research Colloquium.
IN-PERSON LECTURE ONLY
Biography: Gordon Fraser is a full professor in Computer Science at the University of Passau, Germany. He received a PhD in computer science from Graz University of Technology, Austria, in 2007, worked as a post-doc at Saarland University, and was a Senior Lecturer at the University of Sheffield, UK. The central theme of his research is improving software quality, and his recent research concerns the prevention, detection, and removal of defects in software.
Host: Prof. William GJ Halfond, PhD
Location: Corwin D. Denney Research Center (DRB) - 146
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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ISSS - Dr. Hyun-Sik Kim, Friday, October 25th at 2pm in EEB 132 and Zoom
Fri, Oct 25, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Hyun-Sik Kim, Associate Professor, KAIST
Talk Title: Exploring Ways to Maximize Efficiency and Performance in Low-Dropout (LDO) Regulators
Series: Integrated Systems
Abstract: Low-dropout (LDO) regulators are ideal off- and on-chip solutions for powering noise-sensitive loads due to their ripple-less output. LDOs also have many benefits over switch-mode dc-dc converters, such as rapid transient response, excellent power supply rejection (PSR), and compact footprint. Unfortunately, they suffer from an inescapable disadvantage: poor power efficiency; this is primarily caused by a considerable dropout voltage (VDO). Reducing VDO to improve efficiency often leads to a significant drop in LDO's regulation performance. Because of this, most LDOs are designed with a large VDO, making them perceived as energy-consuming components of power management systems. This talk will delve into effective ways to extremely minimize the dropout voltage without compromising performance, aiming for energy-efficient LDO regulators. We will begin with a thorough investigation of operational principles, analyses, and strategies, exploring trade-offs among key performance metrics. Next, several promising approaches to realizing energy-efficient LDO regulators will be investigated, including traditional digital LDOs, a dual-rail analog/digital-hybrid LDO, a triode-region LDO, and a voltage/current-hybrid (VIH) LDO. Finally, the technical merits and flaws of each high-efficiency LDO topology will be investigated by comparing them. In this talk, I will also share my insights from my experience developing the VIH LDO regulator that achieves 98.6% efficiency and a -75dB PSR at 30kHz.
Biography: Hyun-Sik Kim is currently an Associate Professor of Electrical Engineering at the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea. He received his B.S. degree (Hons.) in electronic engineering from Hanyang University, Seoul, South Korea, in 2009, and his M.S. and Ph.D. degrees in electrical engineering from KAIST, in 2011 and 2014, respectively. His research interests include the CMOS analog-integrated circuit designs, with an emphasis on display drivers, power managements, and sensory readout chips. Prof. Kim was a recipient of two Gold Prizes in the 18th and 19th Samsung Human-Tech Paper Awards in 2012 and 2013, respectively, the IEEE SSCS Pre-Doctoral Achievement Award in 2014, the IEEE SSCS Seoul Chapter Best Student JSSC Paper Award in 2014, and the KAIST Technology Innovation Award in 2022. He served as a Guest Editor for the IEEE SOLID-STATE CIRCUITS LETTERS (SSC-L) and was a member of the Technical Program Committee (TPC) for the IEEE Asian Solid-State Circuits Conference (A-SSCC) from 2016 to 2023. He is currently serving on the TPC for the IEEE International Solid-State Circuits Conference (ISSCC) and is the TPC Subcommittee Chair for the IEEE Custom Integrated Circuits Conference (CICC). He has been appointed as a Distinguished Lecturer (DL) in the IEEE Solid-State Circuits Society (SSCS) for the term 2024-2026.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Info: https://usc.zoom.us/j/92995535728
More Information: MHI_Seminar_Flyer_Kim_Oct25_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/92995535728
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CSC/CommNetS-MHI Seminar: Jorge Cortes
Mon, Oct 28, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jorge Cortes, Professor and Cymer Corporation Endowed Chair in High Performance Dynamic Systems Modeling and Control | Department of Mechanical and Aerospace Engineering, University of California, San Diego
Talk Title: The safe gradient flow: a system-theoretic approach to anytime constrained optimization through control barrier functions
Series: CSC/CommNetS-MHI Seminar Series
Abstract: Problems where the solution to a constrained optimization problem is used to regulate a physical process modeled as a dynamically evolving plant arise in multiple application areas, including safety-critical control, power networks, traffic networks, and network congestion. This may take the form of providing setpoints, specifying optimization-based controllers, or steering the system toward an optimal steady state. A paradigmatic example is the use of CBF-based quadratic programs for controller synthesis in robotics. In this talk, we are motivated by situations where the problem incorporates constraints which, when violated, threaten the safe operation of the physical system. In such cases, the algorithm that solves the optimization must be anytime, meaning that it is guaranteed to return a feasible point even when terminated before it has converged to a solution. We introduce a class of novel system-theoretic algorithms for solving constrained nonlinear programs that combine continuous-time gradient flows to optimize the objective function with techniques from control barrier functions to maintain forward invariance of the feasible set. We refer to the resulting closed-loop system as the safe gradient flow. We draw on the alternative interpretation of the safe gradient flow as a projected dynamical system to characterize its dynamical properties regarding regularity, stability, convergence, contractivity, and invariance. We also show how the proposed framework is conducive to the extension of the proposed designs to monotone variational inequalities and discrete-time settings.
Biography: Jorge Cortes is a Professor and Cymer Corporation Endowed Chair in High Performance Dynamic Systems Modeling and Control in the Department of Mechanical and Aerospace Engineering, University of California, San Diego. He is the author of "Geometric, Control and Numerical Aspects of Nonholonomic Systems" (New York: Springer-Verlag, 2002) and co-author of "Distributed Control of Robotic Networks” (Princeton: Princeton University Press, 2009). He is a Fellow of IEEE, SIAM, and IFAC. He has co-authored papers that have won the 2008 and the 2021 IEEE Control Systems Outstanding Paper Award, the 2009 SIAM Review SIGEST selection from the SIAM Journal on Control and Optimization, the 2012 O. Hugo Schuck Best Paper Award in the Theory category, and the 2019 and 2023 IEEE Transactions on Control of Network Systems Outstanding Paper Award. At the IEEE Control Systems Society, he has been a Distinguished Lecturer (2010-2014), an elected member (2018-2020) of the Board of Governors, and Director of Operations (2019-2022) of its Executive Committee. His research interests include distributed control and optimization, network science and complex systems, resource-aware control and coordination, distributed decision making and autonomy, network neuroscience, and multi-agent coordination in robotic, power, and transportation networks.
Host: Dr. Lars Lindemann, llindema@usc.edu
More Information: 2024.10.28 CSC Seminar - Jorge Cortes.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Epstein Institute, ISE 651 Seminar Class
Tue, Oct 29, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yunhe Hou, Department of Electrical & Electronic Engineering, University of Hong Kong
Talk Title: Building Sustainable and Resilient Energy Systems: Challenges and Current Progress
Host: Dr. Jong-Shi Pang
More Information: Flyer 651 Dr. Yunhe Hou 10.29.24.png
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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IEEE-GRSS-APS-SSCS Joint seminar - Stefano Maci, Wed. Oct. 30th at 10am in RTH 211 and Zoom
Wed, Oct 30, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Stefano Maci, IEEE AP-S Past President, University of Sienna, Italy
Talk Title: Metasurface Antennas
Series: IEEE GRSS-APS-SSCS
Abstract: Metasurfaces belong to the category of thin metamaterials and find applications across a wide frequency range, from microwaves to optical frequencies, for developing innovative electromagnetic engineering devices. These surfaces are created by densely arranging small elements on or etching them into a dielectric substrate in a locally periodic distribution. By adjusting the dimensions of these elements while maintaining sub-wavelength 2D periodicity, a pixelated visual appearance and an electromagnetic modulation of the equivalent local impedance boundary conditions (IBC) are achieved. The manipulation of IBC allows for localized modifications in the dispersion equation, influencing the local wavevector while maintaining a constant operating frequency. This capability enables the transformation of surface or guided waves into various wavefield configurations with specified properties. This presentation will focus on the control of both surface waves and space waves, showcasing examples such as the design of high-gain, low cross-polarization antennas, multibeam antennas, and scanning beam flat lenses. Emphasis will be given to space applications. The discussion will also delve into the third generation of adaptive metasurfaces (MTSs), featuring dynamically reconfigurable boundary conditions. This advancement opens possibilities for exploring new perspectives in the development of next-generation wireless communication systems.
Biography: Prof. Stefano Maci is a Professor at the University of Siena (UNISI). Since 2000, he has been P.I. of 10 research projects funded by the European Union (EU) and by the European Space Agency (ESA). He is a Fellow of IEEE since 2004. In 2004 he founded the European School of Antennas (ESoA), a PhD school that presently comprises 35 courses on Antennas, Propagation, and Electromagnetic Theory, and 200 teachers, among them 20 IEEE Fellow. He has been advisor of 40 PhD students. He has been former member of IEEE Antennas and Propagation Society (AP-S) AdCom, the Chair of the Award Committee of the IEEE AP-S, member of the AP Executive Board of IET (UK), Distinguished Lecturer of IEEE and of EurAAP. He was recipient of several prizes and awards, among which the EurAAP Award 2014, the Chen-To Tai Distinguished Educator award 2016, of the Shelkunoff Transaction Prize in 2015, and of the URSI Dellinger Gold Medal in 2020. He is presently Director of ESoA. He has been TPC Chair of the METAMATERIAL 2020 and and General Chair of EuCAP 2023. He was the president of the IEEE Antennas and Propagation Society 2023. In the last ten years he has been invited 60 times as key-note speaker in international conferences. His research activity is documented in 200 papers published in international journals, (among which 100 on IEEE journals), 10 book chapters, and about 450 papers in proceedings of international conferences.
Host: IEEE GRSS-APS-SSCS Joint Student Chapter
More Info: Meeting ID: 925 1030 8883, Passcode: 613281
More Information: IEEE Stefano Maci.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: Meeting ID: 925 1030 8883, Passcode: 613281
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Language Models as Temporary Training Wheels to Improve Mental Health
Wed, Oct 30, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Tim Althoff, Assistant Professor, Allen School of Computer Science - University of Washington
Talk Title: Language Models as Temporary Training Wheels to Improve Mental Health
Abstract: Access to mental health care falls short of meeting the significant need. More than one billion individuals are affected by mental health conditions, with the majority not receiving the necessary treatment. In this talk, I will describe how human-AI collaboration, critically enabled by language models, can improve access to and quality of mental health support. Language models have the potential to act as temporary training wheels providing immediate support and guidance to help individuals develop essential mental health skills. This approach emphasizes the importance of using these tools as initial aids rather than long-term crutches. By offering structured assistance, practice, and feedback, language models can help individuals and professionals learn skills, such as cognitive reframing, emotional regulation, and conflict resolution. However, the ultimate goal is for individuals to gradually transition away from dependence on these models, fostering sustained skill development and long-term well-being. This talk will describe how language models can be developed towards these aims and evaluate their effectiveness across multiple randomized trials and real-world deployments with over 150,000 participants.
Learn to challenge unhelpful thinking with your personal AI assistant at https://bit.ly/changing-thoughts
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Register for Zoom webinar here: https://usc.zoom.us/webinar/register/WN_IFvScow2St2noJndL8FucA
Biography: Tim Althoff is an associate professor in the Allen School of Computer Science & Engineering at the University of Washington. Tim’s research seeks to better understand and empower people through data and computation. His AI research has directly improved mental health services utilized by over ten million people and informed federal policy. Tim holds a Ph.D. degree from the Computer Science Department at Stanford University. His work has received various awards including WWW, 2x ICWSM, ACL, UbiComp, and IMIA Best Paper Awards, the SIGKDD Dissertation Award 2019, and an NSF CAREER Award. Tim’s research has been covered internationally by news outlets including BBC, CNN, The Economist, The Wall Street Journal, and The New York Times.
Host: CAIS
More Info: https://cais.usc.edu/events/usc-cais-seminar-with-dr-tim-althoff/
Webcast: https://usc.zoom.us/webinar/register/WN_IFvScow2St2noJndL8FucALocation: Zoom Webinar
WebCast Link: https://usc.zoom.us/webinar/register/WN_IFvScow2St2noJndL8FucA
Audiences: Everyone Is Invited
Contact: Hailey Winetrobe Nadel, MPH, CHES
Event Link: https://cais.usc.edu/events/usc-cais-seminar-with-dr-tim-althoff/
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AAI-CCI-MHI Seminar on CPS
Wed, Oct 30, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Anushri Dixit, Assistant Professor in the Department of Mechanical & Aerospace Engineering at the University of California, Los Angeles
Talk Title: Perceive with Confidence: Statistical Safety Assurances for Vision-based Navigation
Series: EE598 Seminar Series
Abstract: Significant strides in perception over the past few years have enabled robotic systems to interpret and interact with the world in increasingly versatile ways. The large, often multi-modal, datasets that are used to train modern perception systems endow robots with capabilities for scene understanding like object detection and segmentation. However, the safe integration and reliability of these learned perception models for robotic applications still remains in question due to their failures in unfamiliar environments. In this talk, I will discuss our framework, Perceive with Confidence (PwC), for rigorously quantifying the uncertainty of a pre-trained obstacle detection system in a way that provides a formal assurance on correctness and safety for planning applications. This is achieved by utilizing a technique called conformal prediction to calibrate the perceptual outputs while ensuring generalization to novel environments. I will provide experimental validations of PwC’s formal assurances for indoor navigation applications on the Unitree Go1 quadruped.
Biography: Anushri Dixit is an Assistant Professor in the Department of Mechanical & Aerospace Engineering at the University of California, Los Angeles. Prior to UCLA, she was a postdoctoral researcher at Princeton University. She received her Ph.D. in Control and Dynamical Systems from California Institute of Technology in 2023 and her B.S. in Electrical Engineering from Georgia Institute of Technology in 2017. Her research focuses on motion planning and control of robots in unstructured environments while accounting for uncertainty in a principled manner. Her work on risk-aware methodologies for planning has been deployed on various robotic platforms as a part of Team CoSTAR’s effort in the DARPA Subterranean Challenge. She has received the Outstanding Student Paper Award at the Conference on Decision and Control, Best Student Paper Award at the Conference of Robot Learning, and was selected as a Rising Star in Data Science by The University of Chicago.
Host: Stephen Tu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Ariana Perez
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NL Seminar-InterIntent Investigating Social Intelligence of LLMs via Intention Understanding in a Game context
Thu, Oct 31, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Ziyi Liu, USC
Talk Title: InterIntent Investigating Social Intelligence of LLMs via Intention Understanding in a Game Context
Abstract: REMINDER: Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please inform us at (nlg-seminar-host(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins. If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location. Zoom Info: https://usc.zoom.us/j/95325436571?pwd=NMJIFIQNQ01esvL9UffxxIp4dnSCmF.1Meeting ID: 953 2543 6571/Passcode: 985321 Abstract: Large language models (LLMs) have demonstrated the potential to mimic human social intelligence. However, most studies focus on simplistic and static self-report or performance-based tests, which limits the depth and validity of the analysis. In this paper, we developed a novel framework, INTERINTENT, to assess LLMs’ social intelligence by mapping their ability to understand and manage intentions in a game setting. We focus on four dimensions of social intelligence: situational awareness, self-regulation, self-awareness, and theory of mind. Each dimension is linked to a specific game task: intention selection, intention following, intention summarization, and intention guessing. Our findings indicate that while LLMs exhibit high proficiency in selecting intentions, achieving an accuracy of 88%, their ability to infer the intentions of others is significantly weaker, trailing human performance by 20%. Additionally, game performance correlates with intention understanding, highlighting the importance of the four components towards success in this game. These findings underline the crucial role of intention understanding in evaluating LLMs’ social intelligence and highlight the potential of using social deduction games as a complex testbed to enhance LLM evaluation. INTERINTENT contributes a structured approach to bridging the evaluation gap in social intelligence within multiplayer games.
Biography: Ziyi Liu is a second-year PhD student at the University of Southern California, advised by Professor Jieyu Zhao in LIME Lab. Previously, she earned her master’s degree at USC and was a Research Assistant in USC ISI’s Ink Lab for two years under the guidance of Professor Xiang Ren. Her research focuses on social intelligence and hallucination detection in human-LLM interactions, particularly in evaluating LLM behaviors and aligning LLM values with those of humans. Her work is driven by two key questions: (1) How can we make interactions between models and humans more seamless? (2) How can we ensure the faithfulness of LLMs and avoid hallucinations during interactions?
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://www.youtube.com/watch?v=yHfeHKahMoILocation: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=yHfeHKahMoI
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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AIF4S Seminar: Value of Pretraining Data: Scaling Laws for Downstream Task Performance of Large Language Models
Thu, Oct 31, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Berivan Isik, Research Scientist, Google, Inc.
Talk Title: Value of Pretraining Data: Scaling Laws for Downstream Task Performance of Large Language Models
Abstract: This talk explores the challenges and open questions surrounding the value of pretraining data for large language models (LLMs) in transfer learning settings. While scaling laws have provided valuable insights for LLM design, existing work has predominantly focused on pretraining loss. In contrast, this work investigates scaling behavior in a transfer learning setting where LLMs are finetuned for downstream tasks. Specifically, we examine how the choice and size of pretraining data impact downstream performance, as measured by cross-entropy and translation quality metrics such as BLEU and COMET. Our experiments reveal that the size of the finetuning dataset and the alignment between pretraining and downstream data significantly influence scaling behavior. With sufficient alignment, both cross-entropy and translation quality improve with increased pretraining data, and we demonstrate the ability to predict translation quality using a new log-law. However, in cases of moderate misalignment, we observe that translation quality can fluctuate or even deteriorate with more pretraining data, despite consistent improvements in cross-entropy. Through analysis of these findings, we provide insights for selecting appropriate pretraining data. The talk will conclude with a discussion of future research directions and remaining open questions in this area.
Biography: Berivan Isik is a research scientist at Google, working on efficient and trustworthy AI. Her current interests are efficient training/finetuning of large models, pretraining data valuation and scaling laws for LLMs, differential privacy, and unlearning. She earned her PhD from Stanford University in 2024, where she was affiliated with the SAIL and StatsML groups. Her research was supported by Stanford Graduate Fellowship (2019-2023), Google Ph.D. Fellowship (2023-2026), and a Meta research grant.
Host: Dr. Mahdi Soltanolkotbi, soltanol@usc.edu
Webcast: https://usc.zoom.us/j/98648507063?pwd=kORhNLFVMLol7FYlHv6TsAmqcKqD7t.1Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/98648507063?pwd=kORhNLFVMLol7FYlHv6TsAmqcKqD7t.1
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
