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Conferences, Lectures, & Seminars
Events for February
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NL Seminar -Harnessing Black-Box Control to Boost Commonsense in LM's Generation
Thu, Feb 01, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Yufei Tian, UCLA
Talk Title: Harnessing Black-Box Control to Boost Commonsense in LM's Generation
Series: NL Seminar
Abstract: REMINDER: This talk will be a live presentation only, it will not be recorded. Meeting hosts only admit 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 provide your: Full Name, Title and Name of Workplace to (nlg-seminar-host(at)isi.edu) beforehand so we’ll be aware of your attendance. Also, let us know if you plan to attend in-person or virtually. More Info for NL Seminars can be found at: https://nlg.isi.edu/nl-seminar/ Large language models like Alpaca and GPT-3 generate coherent texts but sometimes lack commonsense, yet improving their commonsense via fine-tuning is resource expensive in terms of both data and computation. In this talk, I'll present BOOST, a resource-efficient framework that steers a frozen Pre-Trained Language Model (PTLM) towards more reasonable outputs. This involves creating an interpretable and reference-free evaluator that assigns a sentence with a commonsensical score which grounds the sentence to a dynamic commonsense knowledge base. Using this evaluator as a guide, we extend the NADO controllable generation method to train an auxiliary head that improves the PTLM's output. Our framework was tested on various language models, including GPT-2, Flan-T5, and Alpaca-based models. On two constrained concept-to-sentence benchmarks, human evaluation results show that BOOST consistently generates the most commonsensical content. Finally, I will demonstrate how ChatGPT outputs are different from and sometimes less favored than our outputs.
Biography: Yufei Tian is a CS PhD student at UCLA advised by Prof. Nanyun (Violet) Peng. Her research is centered around creative and controllable text generation, machine reasoning and its interaction with cognitive science, as well as designing evaluation metrics for open-ended NLG tasks. She is supported by the UCLA-Amazon fellowship program.
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://www.youtube.com/watch?v=WTIKszPDzDkLocation: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=WTIKszPDzDk
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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Alfred E. Mann Department of Biomedical Engineering
Fri, Feb 02, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Michael Elowitz, Howard Hughes Medical Institute Investigator and Professor of Biology and Biological Engineering and Applied Physics at Caltech
Talk Title: Many to many protein networks: modules of multicellularity
Abstract: In multicellular organisms, many biological pathways exhibit a curious structure, involving sets of protein variants that bind or interact with one another in a many-to-many fashion. What functions do these seemingly complicated architectures provide. And can similar architectures be useful in synthetic biology. Here, I will discuss recent work in our lab that shows how many to many circuits can function as versatile computational devices, explore the roles these computations play in natural biological contexts, and show how many-to-many architectures can be used to design synthetic multicellular behaviors.
Biography: Michael Elowitz is a Howard Hughes Medical Institute Investigator and Professor of Biology and Biological Engineering, and Applied Physics at Caltech. Dr. Elowitz's laboratory has introduced synthetic biology approaches to build and understand genetic circuits in living cells and tissues. As a graduate student with Stanislas Leibler, Elowitz developed the Repressilator, an artificial genetic clock that generates gene expression oscillations in individual E. coli cells. Since then, he has continued to design and build synthetic genetic circuits, bringing a “build to understand” approach to bacteria, yeast, and mammalian cells. He and his lab showed that gene expression is intrinsically stochastic, or ‘noisy’, and revealed how noise functions to enable probabilistic differentiation, time-based regulation, and other functions. Currently, Elowitz’s lab is bringing synthetic approaches to understand and program cell-cell communication, epigenetic memory and cell fate control, and to provide foundations for future therapeutic devices. His lab also co-develops the synthetic “MEMOIR” system that allows cells to record their own lineage histories. Elowitz received his PhD in Physics from Princeton University and did postdoctoral research at Rockefeller University. Honors include the HFSP Nakasone Award, MacArthur Fellowship, Presidential Early Career Award, Allen Distinguished Investigator Award, the American Academy of Arts and Sciences, and election to the National Academy of Sciences.
Host: Peter Wang
Location: Olin Hall of Engineering (OHE) - 100 B
Audiences: Everyone Is Invited
Contact: Carla Stanard
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Photonics SEminar - Jie Qiao, Friday, Feb 2nd at 3pm in EEB 248
Fri, Feb 02, 2024 @ 03:00 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jie Qiao, Rochester Institute of Technology
Talk Title: Ultrafast-Lasers-Enabled Photonics, Optics, and Waveguide Lasers
Series: Photonics Seminar Series
Abstract: The investigation into ultrafast-laser-based photonics fabrication and integration represents multifaceted interdisciplinary research, intersecting applied physics, photonics, lasers, materials, and imaging. This presentation describes computational models and elucidates physical processes pertaining to the utilization of ultrafast lasers for the fabrication of optical, photonic, and laser components. Topics covered include the 3D writing of waveguides, waveguide lasers, and beam splitters in crystal and glass materials, as well as nanostructuring, shape correction, and the precision bonding of semiconductor and dielectric materials.
Biography: Dr. Jie Qiao is an associate professor at the Carlson Center for Imaging Science at the Rochester Institute of Technology. Her research at RIT focuses on ultrafast laser phonics, wavefront sensing and beam shaping. Prior to joining RIT, she was a laser system scientist at the Department -of-Energy-funded Laboratory for Laser Energetics, the University of Rochester. She led the demonstration of the world's first 1.5-meter coherently-phased-grating pulse compressor for the OMEGA EP kilojoule, petawatt lasers. She has worked on technology innovation of various ultrafast laser systems, photonics devices, optical imaging, and metrology systems for two photonic startups and one optics company. She was a Fulbright US research scholar and a visiting professor at the Center for Intense Lasers and Applications (CELIA), Universite Bordeaux, France in the 2022 academic year. Dr. Qiao is an Optica Fellow and was an associate editor for Optics Express from 2018 to 2021. She is the General Chair for the 2024 and 2025 CLEO conference, the Application and Technology Program. She earned her doctoral degree from the Department of Electrical and Computer Engineering, University of Texas, Austin.
Host: Mercedeh Khajavikhan, Michelle Povinelli, Constantine Sideris; Hossein Hashemi; Wade Hsu; Mengjie Yu; Wei Wu; Tony Levi; Alan E. Willner; Andrea Martin Armani
More Information: Jie Qiao Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute, ISE 651 Seminar ClassTue, Feb 06, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium - Nathan Sturtevant (University of Alberta / Amii) - Researching the foundations of heuristic search
Wed, Feb 07, 2024 @ 09:00 AM - 10:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Nathan Sturtevant, University of Alberta / Amii
Talk Title: Researching the foundations of heuristic search
Abstract: Although the field of heuristic search is over 50 years old, the last 6-7 years have seen numerous revisions to the foundational algorithms in the field. These include the theories for bidirectional search, for suboptimal search, and for improving the worst-case performance of fundamental algorithms such as A* and IDA*. This talk will give an overview of these new results, demonstrating the changes and their impact, many of which center around the notion of whether re-expansions are allowed during search.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Nathan is a Fellow and Canada CIFAR AI Chair at Amii and a Professor in the Department of Computing Science at the University of Alberta. His research looks broadly at heuristic and combinatorial search problems, including both theoretical and applied approaches, with many applications in games. His work on pathfinding was used in the game Dragon Age: Origins, and will appear in the upcoming Nightingale. Nathan’s work has won the best paper awards at the AAAI, and SoCS conferences, as well as the AI Journal Prominent Paper Award.
Host: Sven Koenig
More Info: https://usc.zoom.us/j/6192383533
Location: https://usc.zoom.us/j/6192383533
Audiences: Everyone Is Invited
Contact: CS Events
Event Link: https://usc.zoom.us/j/6192383533
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CS Colloquium - Chien-Ming Huang (Johns Hopkins University) - Becoming Teammates: Designing Assistive, Collaborative Machines
Wed, Feb 07, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Chien-Ming Huang , Johns Hopkins University
Talk Title: Becoming Teammates: Designing Assistive, Collaborative Machines
Abstract: The growing power in computing and AI promises a near-term future of human-machine teamwork. In this talk, I will present my research group’s efforts in understanding the complex dynamics of human-machine interaction and designing intelligent machines aimed to assist and collaborate with people. I will focus on 1) tools for onboarding machine teammates and authoring machine assistance, 2) methods for detecting, and broadly managing, errors in collaboration, and 3) building blocks of knowledge needed to enable ad hoc human-machine teamwork. I will also highlight our recent work on designing assistive, collaborative machines to support older adults aging in place.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Chien-Ming Huang is the John C. Malone Assistant Professor in the Department of Computer Science at the Johns Hopkins University. His research focuses on designing interactive AI aimed to assist and collaborate with people. He publishes in top-tier venues in HRI, HCI, and robotics including Science Robotics, HRI, CHI, and CSCW. His research has received media coverage from MIT Technology Review, Tech Insider, and Science Nation. Huang completed his postdoctoral training at Yale University and received his Ph.D. in Computer Science at the University of Wisconsin–Madison. He is a recipient of the NSF CAREER award. https://www.cs.jhu.edu/~cmhuang/
Host: Stefanos Nikolaidis
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: CS Events
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Alfred E. Mann Department of Biomedical Engineering
Wed, Feb 07, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: X.Edward Guo, Ph.D., Columbia University, New York
Talk Title: Bone Bioengineering: Microstructure, Mechanics, Mechanobiology, and Beyond
Abstract: Bone bioengineering is a basic science of clinical significance in many medical fields, such as osteoporosis, osteoarthritis, or intervertebral disc degeneration. I will highlight our development of three-dimensional imaging analysis and modeling techniques for trabecular bone microstructure, its applications in basic science research of bone mechanics, and clinical applications in osteoporosis and osteoarthritis. We will discuss bone microstructural phenotypes in different races and their implications in genetic and precision medicine, anthropology, evolution, and mechanobiology of the skeletons. In parallel to these developments, we will also showcase how mechanobiology links to bone microstructure and mechanics
Biography: Dr. Guo was born and grew up in China. He received his B.S. in applied mechanics from Peking University. He continued his graduate studies in the US and received his M.S. in 1990 and Ph.D. in 1994 in Medical Engineering and Medical Physics from Harvard University-MIT. From 1994 to 1996, Professor Guo did his postdoctoral fellowship in the Orthopaedic Research Laboratories at the University of Michigan at Ann Arbor. In 1996, he joined the Department of Mechanical Engineering and Biomedical Engineering at Columbia University as an Assistant Professor. He was promoted to Associate Professor with tenure in 2003, Professor in 2007, and named Stanley Dicker Professor in 2018. He directs the Bone Bioengineering Laboratory in the Department of Biomedical Engineering at Columbia, focusing his research interests on micromechanics of bone tissue, computational biomechanics, and mechanobiology of bone. His past honors include the Young Investigator Recognition Award from the Orthopaedic Research Society, the National Research Service Award from the US National Institutes of Health (NIH), a CAREER award from the US National Foundation of Science (NSF), Funds for Talented Professionals (Joint Research Fund for Overseas Chinese Young Scholars) from the National Natural Science Foundation of China, and Christopher R Jacobs Award from Biomedical Engineering Society (BMES). He is elected fellow of the American Institute for Medical and Biological Engineering, American Society of Mechanical Engineers, BMES, American Society of Bone and Mineral Research, International Combined Orthopaedic Research Societies, and International Academy of Medical and Biological Engineering. He was one of the founders and co-editor-in-chief of Cellular and Molecular Bioengineering (CMBE), an international journal of BMES. He has served on many NIH, NSF, and NASA review panels. The Whitaker Foundation, the NSF, and the NIH have supported his research. He served as President of the International Chinese Musculoskeletal Research Society, the Society for Physical Regulation in Biology and Medicine, a Member of the Board of Directors of the Orthopaedic Research Society, and a Member of the Board of Directors of AIMBE. He founded the Special Interest Group (SIG) in CMBE at the BMES and served as its founding Chair. He served as the Chair of the Department of Biomedical Engineering at Columbia University from 2017 to 2023, and he founded the Northeast BME League and served as its inaugural President.
Host: Peter Wang
Location: Corwin D. Denney Research Center (DRB) - 145
Audiences: Everyone Is Invited
Contact: Carla Stanard
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AME Seminar
Wed, Feb 07, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Negar Nazari, Harvard
Talk Title: Microfluidics with Macro-Impact: Advancing Sustainability through Nanoparticle - Enhanced Foams for Optimized CO2 Sequestration
Abstract: The contemporary global challenge centers on ensuring water and energy access for a growing population while minimizing environmental impacts and promoting sustainability. Porous media play a crucial role in this, facilitating processes like carbon sequestration, hydrogen storage, and geothermal energy extraction within geological formations. The Paris Climate Accord emphasizes reducing greenhouse gas emissions, with carbon sequestration in geological formations being a potential solution. However, challenges like ensuring safe storage and preventing leaks remain. Utilizing a foaming solution alongside CO2 injection emerges as a promising method to reduce the mobility of CO2, enhancing the blockage of CO2 in more permeable areas and thus bolstering storage safety. A significant hurdle in this technique is the thermodynamic instability of the bubble interface in the high salinity brines found in host formations. The introduction of nanoparticles enhances the interface's stability, counteracting the capillary forces that destabilize the foam's lamellae. The dynamics of gas-liquid interfaces differ between aqueous surfactants and nanoparticles. Nanoparticles impact the drag on elongated bubbles at low capillary numbers by establishing monolayer formations at the fluid interface, which in turn increases the interfacial dilatational viscoelasticity. This enhancement in viscoelasticity strengthens the interface's dynamic resistance to changes in surface area, whether through stretching or compressing, thereby improving the stability of the interface.
Biography: Negar Nazari is a Postdoctoral fellow at the school of engineering and applied sciences at Harvard University. Her research focuses on understanding complex fluid flow and transport in porous media with particular emphasis on topics relevant to energy and sustainability including but not limited to carbon and hydrogen storage. Prior to her postdoc, she completed her PhD at the energy science and engineering department at Stanford University. Her PhD research focused on microscale analysis of fluid-fluid interactions and complex multiphase flow in fractured systems and channels. Her research interests lie in energy and sustainability, microfluidics, and data-driven and programming techniques to upscale flow studies. Negar received the Trailblazing Researcher Award from the California Institute of Technology for exceptional contributions and frontier research in Energy and Sustainability.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09Location: James H. Zumberge Hall Of Science (ZHS) - 252
WebCast Link: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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Semiconductors & Microelectronics Technology Seminar - Tingyi Gu, Friday, Feb. 9th at 2pm in EEB 248
Fri, Feb 09, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Tingyi Gu, ECE- University of Delaware
Talk Title: On-chip wavefront shaping and image classification on silicon photonics
Series: Semiconductors & Microelectronics Technology
Abstract: The advancement of nanotechnologies enables powerful control of photons by subwavelength structures. In recent years, rapid advancement of metasurface and metamaterials reveal the potential of nanophotonics in the applications across disciplines, from image processing/conversion to controlled light-matter interactions. In this talk, I will progressively illustrate the powerful role of the meta-atoms, meta-surface, and meta-system in integrated photonic platform, which enabled the control of nonHermicity, perform mathematical conversion to machine learning, respectively. 0D: Embedding individual symmetric or asymmetric meta-atoms in silicon micro- resonators provide the full control of non-Hermicity, which has been proved to coherently suppress the nanofabrication resulted backscattering [1]. 1D: The integrated metasystem performs analogue optical computing tasks, from simple Fourier transformation to spatial differentiations (1D+) [2]. Also, we have shown that asymmetric subwavelength design engineers the wave momentum space for broadband and power independent back reflection suppression. 2D: With lithographically defined inter-layer alignment, we demonstrate diffractive deep optical network on silicon photonic platform, towards broadband spatial pattern classification and hyperspectral imaging [3]. In addition to materials offered by the foundry, I will try to extend the scope of 'heterogeneous integration' for layered phase change materials for integrated photonic memory devices [4], and potential integration scheme with silicon photonics.
Biography: Tingyi Gu is an associate professor in the electrical engineering of University of Delaware. Her group works on foundry compatible silicon photonic meta-components for optical communication and sensing, with the focus on optoelectronic reconfigurability and high-speed operation. She served on 19 committees for optics and optoelectronics societies, including SPIE, CLEO, FiO and IPC. She received a B.S. from Shanghai Jiao Tong University, and M.S. and Ph.D. degrees from Columbia University, all in EE. She has held positions at Bell Labs, Princeton University and Hewlett Packard Labs.
Host: J Yang, H Wang, C Zhou, S Cronin, W Wu
More Information: Tingyi Gu_2024-02-09.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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ECE Virtual Seminar: Transdisciplinary Engineering: Reaching Beyond Engineering to Exploit Concepts From Other Disciplines
Mon, Feb 12, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Azad M. Madni, University Professor of Astronautics, Aerospace and Mechanical Engineering, USC Viterbi School of Engineering
Talk Title: Transdisciplinary Engineering: Reaching Beyond Engineering to Exploit Concepts From Other Disciplines
Abstract: This talk presents transdisciplinary engineering and how it is enabled by exploiting convergence of engineering with other disciplines. Specifically, it presents an overview of my research in this area, TRASEE™ educational paradigm, and the transformation of the Systems Architecting and Engineering Program using TRASEE. It focuses on storytelling in virtual worlds as an exemplar of exploiting convergence between engineering and entertainment/cinematic arts.
Biography: Azad Madni is a University Professor of Astronautics, Aerospace and Mechanical Engineering in the University of Southern California. The designation of University Professor honors USC’s most accomplished multidisciplinary faculty with significant achievements across multiple technical fields. He is the holder of the Northrop Grumman Fred O’Green Chair in Engineering, and the Executive Director of University of USC’s Systems Architecting and Engineering Program. He also holds a joint appointment in the Sonny Astani Department of Civil and Environmental Engineering, and courtesy appointments in the Rossier School of Education and Keck School of Medicine. He is the Founding Director of the Distributed Autonomy and Intelligent Systems Laboratory and is a faculty affiliate of USC’s Ginsberg Institute for Biomedical Therapeutics in the Keck School of Medicine. He is the founding director of the Ph.D. degree program in Systems Engineering in the Astronautics Department. He is also a Senior Fellow of the Loker Hydrocarbon Research Institute founded by Nobel Laureate, George Olah. He is a member of the London Digital Twin Research Centre. He is the founder and CEO of Intelligent Systems Technology, Inc., an award-winning hi-tech company specializing in model-based approaches for addressing scientific and societal problems of national and global significance. He is the Chief Systems Engineering Advisor to The Aerospace Corporation. He received his Ph.D., M.S., and B.S. degrees in Engineering from the University of California, Los Angeles. He is a graduate of AEA/Stanford Institute Executive Program for Technology Executives.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/91315597163?pwd=YjlrMlhGYnV4NEV4UkFiZXdETkZiQT09WebCast Link: https://usc.zoom.us/j/91315597163?pwd=YjlrMlhGYnV4NEV4UkFiZXdETkZiQT09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CCI, AAI, and MHI Joint Seminar Series - Radoslav Ivanov (Rensselaer Polytechnic Institute): Safe and secure autonomy within reach: a verified machine learning and control perspective
Tue, Feb 13, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Radoslav Ivanov, Rensselaer Polytechnic Institute
Talk Title: Safe and secure autonomy within reach: a verified machine learning and control perspective
Abstract: In this talk, I will present an integrated approach to assuring the safety and security of cyber-physical systems (CPS) through a combination of offline verification and online monitoring techniques. For offline assurance, I have developed an approach, called Verisig, for verifying the safety of autonomous systems with neural network controllers. I will present an exhaustive evaluation on a neural-network-controlled (1/10-scale) autonomous racing car, in terms of modeling, verification and experiments on the real platform. In the second part of the talk, I will describe my work on run-time monitoring of system safety, with applications to medical CPS. Specifically, I will present a detector for critical drops in the patient's oxygen content during surgery, with guaranteed performance regardless of varying physiological parameters such as metabolism. The detector is evaluated on real-patient data collected from the Children's Hospital of Philadelphia.
Zoom Link: https://usc.zoom.us/j/98624281836?pwd=ajJSWGRvbkRpUVgvRC9nOXd5K29TZz09 Meeting ID: 986 2428 1836 Passcode: CPS24
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Radoslav Ivanov He is an Assistant Professor in Computer Science at the Rensselaer Polytechnic Institute. Prior to that, he was a postdoc at the PRECISE center at the University of Pennsylvania. Radoslav received the B.A. degree in computer science and economics from Colgate University in 2011, and the Ph.D. degree in computer and information science from the University of Pennsylvania in 2017. His research interests are broadly in the field of safe and secure autonomy, with a focus on verified machine learning, control theory and cyber-physical security. The natural application domains of his work are automotive and medical cyber-physical systems.
Host: Pierluigi Nuzzo and Lars Lindemann
More Info: https://usc.zoom.us/j/98624281836?pwd=ajJSWGRvbkRpUVgvRC9nOXd5K29TZz09
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: CS Events
Event Link: https://usc.zoom.us/j/98624281836?pwd=ajJSWGRvbkRpUVgvRC9nOXd5K29TZz09
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Epstein Institute, ISE 651 Seminar Class
Tue, Feb 13, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yale T. Herer, Professor, Technion - Israel Institute of Technology
Talk Title: An Asymptotic Perspective on Risk Pooling: Limitations and Relationship to Transshipments
Host: Prof. Maged Dessouky
More Information: February 13, 2024.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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MFD Spring Seminars- Distinguished Lecture Series
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Tue, Feb 13, 2024 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Yury Gogotsi, Drexel University
Talk Title: 2D Carbides and Nitrides (MXenes) -“ from Discovery to Applications
Abstract: MXenes are a family of two-dimensional (2D) early transition metal carbides, nitrides, oxycarbides, carbonitrides, and related structures with a general formula of Mn+1XnTx, where M is a transition metal, X is carbon or nitrogen (oxygen substitution is possible), T represents the surface terminations (O, OH, halogen, chalcogen, etc.), and n = 1—4 [1]. More than 50 MXene compositions have already been reported, but the number of possible compositions is infinite if one considers solid solutions and combinations of surface terminations. MXenes open an era of computationally driven atomistic design of 2D materials. MXenes possess electronic, optical, mechanical, and electrochemical properties that differentiate them from other materials. Chemically tunable superconductivity has been demonstrated in Nb- and Mo-based MXenes. Chemically tunable ferromagnetism and antiferromagnetism have been predicted. Highly nonlinear optical properties of MXenes are being explored. Several MXenes have been predicted to act as topological insulators. Many MXenes are metals but with a tunable density of states at the Fermi level, like semiconductors. Moreover, their properties are tunable by design and can be modulated using an ionotronic approach [2], leading to breakthroughs in the fields ranging from optoelectronics, electromagnetic interference shielding, and communication to energy storage, catalysis, sensing, and healthcare. In several applications, such as electromagnetic interference shielding, MXenes have already outperformed all other materials. In this talk, I’ll discuss the synthesis and structure of MXenes, their optoelectronic properties, and the coupling between electrochemical redox processes in MXenes and their optical properties, which can be monitored in situ using spectroelectrochemistry techniques [3].
Biography: Yury Gogotsi is a Distinguished University Professor and Charles T. and Ruth M. Bach Endowed Chair in the Department of Materials Science and Engineering at Drexel University (Philadelphia, USA). He is the founding Director of the A.J. Drexel Nanomaterials Institute. He received his MS (1984) and PhD (1986) from Kyiv Polytechnic and a DSc degree from the National Academy of Sciences of Ukraine in 1995. Together with his students and colleagues, he made principal contributions to the development of materials for electrochemical capacitors and other energy storage devices, discovered MXenes, demonstrated the tuning of structure and porosity of carbide-derived carbons, and developed new processes for the synthesis, surface modification, and purification of nanotubes and nanodiamonds. He also published the first microscopic observation of water inside carbon nanotubes, discovered polygonal nanotubes (graphite polyhedral crystals), and shaped the field of high-pressure surface science. He is recognized as a Highly Cited Researcher in Materials Science and Chemistry and a Citations Laureate by Clarivate Analytics (Web of Science). He has received numerous awards for his research, including the Ceramic Prize from the World Academy of Ceramics, the Materials Research Society (MRS) Medal, the American Chemical Society (ACS) Award in the Chemistry of Materials, etc. He has been elected a Fellow of the National Academy of Inventors, the World Academy of Ceramics, the European Academy of Sciences, and many professional societies. He holds honorary doctorates from several European Universities.
Host: Mork Family Department
Location: James H. Zumberge Hall Of Science (ZHS) - 252
Audiences: Everyone Is Invited
Contact: Monique Garcia
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CS Colloquium: Parastoo Abtahi (Princeton University) - From Haptic Illusions to Beyond Real Interactions in Virtual Reality
Wed, Feb 14, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Parastoo Abtahi, Princeton University
Talk Title: From Haptic Illusions to Beyond Real Interactions in Virtual Reality
Abstract: Advances in audiovisual rendering have led to the commercialization of virtual reality (VR) hardware; however, haptic technology has not kept up with these advances. While haptic devices aim to bridge this gap by simulating the sensation of touch, many hardware limitations make realistic touch interactions in VR challenging. In my research, I explore how by understanding human perception, we can design VR interactions that not only overcome the current limitations of VR hardware but also extend our abilities beyond what is possible in the real world. In this talk, I will present my work on redirection illusions that leverage the limits of human perception to improve the perceived performance of encountered-type haptic devices, such as improving the position accuracy of drones, the speed of tabletop robots, and the resolution of shape displays when used for haptics in VR. I will then present a framework I have developed through the lens of sensorimotor control theory to argue for the exploration and evaluation of VR interactions that go beyond mimicking reality.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Parastoo Abtahi is an Assistant Professor of Computer Science at Princeton University, where she leads Princeton’s Situated Interactions Lab (Ψ Lab) as part of the Princeton HCI Group. Before joining Princeton, Parastoo was a visiting research scientist at Meta Reality Labs Research. She received her PhD in Computer Science from Stanford University, working with Prof. James Landay and Prof. Sean Follmer. Her research area is human-computer interaction, and she works broadly on augmented reality and spatial computing. Parastoo received her bachelor’s degree in Electrical and Computer Engineering from the University of Toronto, as part of the Engineering Science program
Host: Heather Culbertson
More Info: https://usc.zoom.us/j/95030499252?pwd=YVl3dU93ZUlTeVNrWEFVeWNkYjB2Zz09
Location: Ronald Tutor Hall of Engineering (RTH) - 115
Audiences: Everyone Is Invited
Contact: CS Events
Event Link: https://usc.zoom.us/j/95030499252?pwd=YVl3dU93ZUlTeVNrWEFVeWNkYjB2Zz09
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AME Seminar
Wed, Feb 14, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Zhenyu Gao, University of Texas at Austin
Talk Title: Computational Paradigms Towards Sustainable Aeronautics
Abstract: As technology and the environment rapidly evolve, the aerospace industry is actively seeking solutions to three significant opportunities and challenges. First, the data-intensive transformation will reframe the aerospace industry with big data technologies, analytical methods, and high-performance computation. Second, future aerospace systems must be environmentally, socially, and economically sustainable. Third, aerospace systems of diverse types and capabilities will grow robustly and operate at larger scales. In this talk, I will share a series of recent studies which leverage data-driven and computational methods for the design and analysis of sustainable aeronautical systems. This includes (1) a machine learning approach for efficient and accurate aviation environmental impact modeling, (2) a data-driven optimization approach for holistic and equitable advanced air mobility noise management, and (3) a modeling and simulation approach for sustainable and safe 3D urban airspace design. This research highlights the significance of data-driven approaches for the sustainable development of novel aerospace systems.
Biography: Zhenyu Gao is a Postdoctoral Fellow in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin. His areas of research encompass sustainable aviation, data-driven aerospace engineering, and intelligent transportation systems. He earned his Ph.D. in Aerospace Engineering and an M.S. in Operations Research from Georgia Institute of Technology, and a B.S. in Aerospace Engineering from the University of Illinois at Urbana–Champaign. His doctoral dissertation was awarded the 2023 Georgia Tech Sigma Xi Best Ph.D. Thesis Award. He has also served as a visiting researcher at the National University of Singapore and the Institute of Science and Technology Austria (ISTA). During his time at Georgia Tech and UT Austin, he has contributed to over ten research projects funded by entities such as the FAA, NASA, and industry corporations like The Boeing Company.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09Location: James H. Zumberge Hall Of Science (ZHS) - 252
WebCast Link: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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Alfred E. Mann Department of Biomedical Engineering
Fri, Feb 16, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Arnab Mukherjee, Ph.D., Assistant Professor of Chemical Engineering & Biological Engineering University of California, Santa Barbara
Talk Title: Engineering genetic reporters for molecular MRI
Abstract: The study of biological functions in intact organisms requires noninvasive genetic reporters to track cells, image gene expression, and monitor signaling pathways. While fluorescent and bioluminescent proteins are widely used as reporters, their utility in deep tissues is limited due to the scattering and absorption of light, which impede imaging beyond a depth of ~ 1 mm from the tissue surface. To overcome this challenge, my research harnesses unexpected connections between proteins and the physics of magnetic resonance (MRI) to create new biomolecular reporters for deep tissue imaging. In this talk, I will discuss our recent efforts to address three long-standing challenges in the development of viable MRI reporters: sensitivity, specificity, and sensor design. First, I will highlight our recent work in increasing reporter gene sensitivity to detect small numbers of genetically labeled cells, potentially, as few as hundred cells per imaging voxel. I will then describe the creation of chemically erasable reporters, which enable “hotspot” imaging with a low tissue background. Finally, I will discuss a new modular approach for programming MRI sensors based on protease modulation of reporter activity.
Biography: Arnab Mukherjee is an Assistant Professor of Chemical Engineering & Biological Engineering at the University of California, Santa Barbara. Prior to arriving at UCSB, Dr. Mukherjee completed a James G. Boswell fellowship in Molecular Engineering at Caltech (working with Prof. Mikhail Shapiro) and obtained his Ph.D. in chemical and biomolecular engineering from the University of Illinois, Urbana-Champaign. The Mukherjee lab works at the intersection of molecular engineering, synthetic biology, and molecular imaging to create new genetic reporters and sensors for magnetic resonance imaging (MRI). Research in the Mukherjee group has been consistently supported by the NIH, Army, and foundations; and recognized with notable awards, including an Outstanding Young Investigator Award (NIH MIRA), a Discovery Award from the DoD, the NARSAD Young Investigator Award from the Brain & Behavior Research Foundation, and a 2022 Scialog Fellows award in Advanced Bioimaging.
Host: Jenny Treweek
Location: Olin Hall of Engineering (OHE) - 100 B
Audiences: Everyone Is Invited
Contact: Carla Stanard
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Seminar
Fri, Feb 16, 2024 @ 03:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ahmad Beirami, Google Research
Talk Title: Language Model Alignment: Theory & Practice
Series: AIF4S Seminar Series
Abstract: Generative language models have advanced to a level where they can effectively solve a variety of open-domain tasks with little task specific supervision. However, the generated content from these models may still not satisfy the preference of a human user. The goal of the alignment process is to remedy this issue by generating content from an aligned model that improves a reward (e.g., make the generation safer) but does not perturb much from the base model. A simple baseline for this task is best-of-N, where N responses are drawn from the base model, ranked based on a reward, and the highest ranking one is selected. More sophisticated techniques generally solve a KL-regularized reinforcement learning (RL) problem with the goal of maximizing expected reward subject to a KL divergence constraint between the aligned model and the base model. An alignment technique is preferred if its reward-KL tradeoff curve dominates other techniques. In this talk, we give an overview of language model alignment and give an understanding of known results in this space through simplified examples. We also present a new modular alignment technique, called controlled decoding, which solves the KL-regularized RL problem while keeping the base model frozen through learning a prefix scorer, offering inference-time configurability. Finally, we also shed light on the remarkable performance of best-of-N in terms of achieving competitive or even better reward-KL tradeoffs when compared to state-of-the-art alignment baselines.
Biography: Ahmad Beirami is a research scientist at Google Research, leading research efforts on building safe, helpful, and scalable generative language models. At Meta AI, he led research to power the next generation of virtual digital assistants with AR/VR capabilities through robust generative language modeling. At Electronic Arts, he led the AI agent research program for automated playtesting of video games and cooperative reinforcement learning. Before moving to industry in 2018, he held a joint postdoctoral fellow position at Harvard & MIT, focused on problems in the intersection of core machine learning and information theory. He is the recipient of the Sigma Xi Best PhD Thesis Award from Georgia Tech.
Host: Mahdi Soltanolkotabi
Webcast: https://usc.zoom.us/j/92673154833?pwd=Z1QwYk52RVhWSkRXRmhzTmRhUTU3UT09More Information: 14766.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/92673154833?pwd=Z1QwYk52RVhWSkRXRmhzTmRhUTU3UT09
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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CS Colloquium - Krishna Kant Chintalapudi (Microsoft Research Redmond) - "Leveling up Next Gen Xbox User Experience with Neural Networks and Sound"
Tue, Feb 20, 2024 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Krishna Kant Chintalapudi, Principal Researcher, Microsoft Research Redmond (MSR)
Talk Title: Leveling up Next Gen Xbox User Experience with Neural Networks and Sound
Abstract: This talk presents two groundbreaking innovations in enhancing the gaming experience on Next-Gen Xbox platforms - ADR-X (NSDI 2024) and Ekho (SIGCOMM 2023). ADR-X, is a neural network-assisted wireless link rate adaptation technique for compute-constrained embedded gaming devices. It uses a meticulously crafted NN based contextual bandit that leverages existing communication theory domain knowledge. This allows ADR-X to perform at par with state-of-the-art reinforcement learning techniques such as PPO while also running 100× faster. Ekho introduces a novel approach to synchronizing cloud gaming media over the internet - crucial for immersive gameplay. By embedding faint, human-inaudible pseudo-noise markers into game audio and detecting them through player microphones, Ekho accurately measures and compensates for inter-stream delays.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Krishna Kant Chintalapudi is a Principal Researcher in the Networking Research Group at Microsoft Research Redmond (MSR). His research interests span AI/ML, Networking & Systems, Video Analytics, AR/VR and Internet of Things. He has published more than 50 papers in reputed international conferences and journals which have been cited over 8000 times and he holds over 30 patents granted by USPTO. Krishna graduated from the University of Southern California with a Phd in Computer Science in 2006. Prior to joining MSR, Krishna was a Senior Research Engineer at Bosch Research and Technology Center in Palo Alto, CA, USA.
Host: Ramesh Govindan
Location: Hedco Neurosciences Building (HNB) - 107
Audiences: Everyone Is Invited
Contact: CS Events
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CSC/CommNetS-MHI Seminar: Yongduan Song
Tue, Feb 20, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yongduan Song, Director, Research Institute for Artificial Intelligence | Chair Professor, School of Automation | Chongqing University
Talk Title: Several critical issues in neural network driven control design and analysis
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
Neural networks (NN) and related learning algorithms are crucial components of artificial intelligence. The utilization of neural networks combined with learning algorithms for controller design has become a mainstream direction in the field of intelligent control. This talk will examine the typical NN-driven design approaches and expose several critical issues related to functionality and effectiveness of the NN-based control methods.
Biography:
Professor Yongduan Song is a Fellow of IEEE, Fellow of AAIA, Fellow of International Eurasian Academy of Sciences, and Fellow of Chinese Automation Association. He was one of the six Langley Distinguished Professors at National Institute of Aerospace (NIA), USA and registered professional engineer (USA). He is currently the dean of Research Institute of Artificial Intelligence at Chongqing University. Professor Song is the Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems (TNNLS) and the founding Editor-in-Chief of the International Journal of Automation and Intelligence.
Host: Dr Petros Ioannou, ioannou@usc.edu
More Information: 2024.02.20 Seminar - Yongduan Song.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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CS Colloquium - Pavithra Prabhakar (Kansas State University) - Safety Analysis of AI-enabled Cyber-Physical Systems (CPS): A Formal Approach
Tue, Feb 20, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Prof. Pavithra Prabhakar, Kansas State University
Talk Title: Safety Analysis of AI-enabled Cyber-Physical Systems (CPS): A Formal Approach
Abstract: AI-based components have become an integral part of Cyber-Physical Systems enabling transformative functionalities. With the ubiquitous use of Machine Learning components in perception, control and decision making in safety critical application domains such as automotive and aerospace, rigorous analysis of these systems has become imperative toward real-world deployment. In this talk, we will present a formal approach to verifying the safety of AI-enabled CPS. We consider a closed-loop system consisting of a dynamical system model of the physical plant and a neural network model of the perception/control modules and analyze the safety of this system through reachable set computation.
One of the main challenges with reachable set computation of neural network-controlled CPS is the scalability of the methods to large networks and complex dynamics. We present a novel abstraction technique for neural network size reduction that provides soundness guarantees for safety analysis and indicates a promising direction for scalable analysis of the closed-loop system. Specifically, our abstraction consists of constructing a simpler neural network with fewer neurons, albeit with interval weights called interval neural network (INN), which over-approximates the output range of the given neural network. We present two methods for computing the output range analysis problem on the INNs, one by reducing it to solving a mixed integer linear programming problem, and the other a symbolic computation method using a novel data structure called the interval star set. Our experimental results highlight the trade-off between the computation time and the precision of the computed output set. We will discuss other foundational questions on neural network size reduction by exploring the notion of equivalence and approximate equivalence. We will conclude by pointing to ongoing work on incorporating a camera model along with a neural network for perception in the closed-loop system framework.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Pavithra Prabhakar is professor in the department of computer science, and the Peggy and Gary Edwards Chair in Engineering at Kansas State University. She is currently serving the National Science Foundation as a Program Director in the Software and Hardware Foundations Cluster in the Computer and Information Science and Engineering Directorate, where she manages formal methods and verification portfolio. Specifically, she leads the Formal Methods in the Field (FMitF) program, has been a founding program director for the Safe Learning Enabled Systems (SLES) program and is a cognizant program director for the Foundations of Robotics Research (FRR) and the Cyber-Physical Systems (CPS) program.
She obtained her doctorate in computer science and a master's degree in applied mathematics from the University of Illinois at Urbana-Champaign, followed by a CMI postdoctoral fellowship at the California Institute of Technology. Prior to coming to K-State, she spent four years at the IMDEA Software Institute in Spain as a tenure-track assistant professor. She is the recipient of a Marie Curie Career Integration Grant from the European Union (2014), an NSF CAREER Award (2016), an ONR Young Investigator Award (2017), NITW distinguished young alumnus award (2021), and an Amazon Research Award (2022).
Host: Jyotirmoy Deshmukh
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: CS Events
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Epstein Institute, ISE 651 Seminar Class
Tue, Feb 20, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Jay Lee, Mork Family Department of Chemical Engineering and Materials Science, USC Viterbi
Talk Title: Role of Process Systems Engineering in Decarbonization and Energy Transition
Host: Prof. Maged Dessouky
More Information: February 20, 2024.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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Alfred E. Mann Department of Biomedical Engineering
Wed, Feb 21, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Konstantinos Konstantopoulos, Ph.D., William H. Schwarz Professor of Chemical and Biomolecular Engineering The Johns Hopkins University
Talk Title: Cell Mechanosensing and Prognostic Assays in Cancer
Abstract: Cell locomotion is a critical step in the process of cancer metastasis, as it enables cancerous cells dissociating from a primary tumor to navigate through interstitial tissues and ultimately colonize distant organs. Metastasizing cells migrate through three-dimensional (3D) longitudinal channel-like tracks created by various anatomical structures or generated via remodeling of extracellular matrix by cancer-associated stroma cells. This seminar will present a multidisciplinary approach, integrating bioengineering tools with molecular and cell biology techniques to understand cancer cell migration in precisely engineered microenvironments, which recapitulate in vitro the 3D longitudinal channels encountered in vivo. The plasticity of cancer cell migration will be discussed, focusing on how cells sense, adapt, and respond to different physical cues, such as confinement and extracellular fluid viscosity. Moreover, this presentation will outline how our current knowledge on the mechanisms of cell motility has led to the development of a novel microchannel assay capable of distinguishing aggressive from non-aggressive cancer cells for accurate diagnosis, prognosis and precision care of cancer patients.
Biography: Received the Diploma of Chemical Engineering from the National Technical University of Athens, Greece in 1989 and the doctorate in Chemical Engineering from Rice University, Houston, Texas in 1995. After his postdoctoral training in the Institute of Biosciences and Bioengineering at Rice University, he joined the faculty of Chemical and Biomolecular Engineering at Johns Hopkins in 1997, and served as Department Chair from 2008 till 2017. He holds secondary appointments in the Departments of Biomedical Engineering and Oncology. He is Fellow of the American Institute for Medical and Biological Engineering (AIMBE) and of the Biomedical Engineering Society (BMES). His signature research focuses on how cells sense and respond to different physical cues. He is known for deciphering a new mechanism of tumor cell migration in confinement called the Osmotic Engine Model, for identifying extracellular fluid viscosity as a novel physical cue regulating cancer metastasis, and for developing innovative prognostic and diagnostic assays in cancer. He has also discovered key functional selectin ligands involved in tumor cell adhesion to host cells, and characterized biophysically these receptor-ligand interactions at the single-molecule level. He has published over 160 peer-reviewed articles in premier journals such as Nature, Cell, Nature Biomedical Engineering, Science Advances etc. His work has been cited ~13,500 times with an h-index of 66. Eleven of his mentees have launched successful academic careers in premier institutions, whereas another 18 have joined the government or industry and now hold leading appointments. He is currently the PI or MPI on multiple NIH R01 and CDMRP grants.
Host: Peter Wang
Location: Corwin D. Denney Research Center (DRB) - 145
Audiences: Everyone Is Invited
Contact: Carla Stanard
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WIE x TBP: Male Allies in STEM
Wed, Feb 21, 2024 @ 06:30 PM - 07:30 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Join WIE and the Tau Beta Pi engineering honor society for our Male Allies in STEM Event!
A panel of women and non-binary science and engineering students and faculty will be sharing their stories about identity and experiences with male allyship, to raise awareness about the challenges of working in male-dominated professions and ways that men can be more effective allies.
All undergraduates and graduate students are welcome, and we'll have free burritos (vegetarian and vegan options available)!Location: Sign into EngageSC to View Location
Audiences: Everyone Is Invited
Contact: Thelma Federico Zaragoza
Event Link: https://engage.usc.edu/WIE/rsvp?id=395816
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Center of Autonomy and AI, Center for Cyber-Physical Systems and the Internet of Things, and Ming Hsieh Institute for Electrical & Computer Engineering Joint Seminar Series: Dengwang Tang (USC)
Thu, Feb 22, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dengwang Tang, University of Southern California
Talk Title: Informed Posterior Sampling Based Algorithms for Markov Decision Processes
Series: Center of Autonomy and AI, Center for Cyber-Physical Systems and the Internet of Things, and Ming Hsieh Institute for Electrical & Computer Engineering Joint Seminar Series
Abstract: The traditional paradigm of RL often features an agent who learns to control the system only through interaction. However, such a paradigm can be impractical since
learning can be very slow. In many engineering applications, there's often an offline dataset available before the application of the online learning algorithm. We proposed
the informed posterior sampling-based reinforcement learning (iPSRL) to use offline datasets to bootstrap online RL algorithms in both episodic and continuing MDP
learning problems. In this algorithm, the learning agent forms an informed prior with the offline data along with the knowledge about the offline policy that generated the data.
This informed prior is then used to initiate the posterior sampling procedure. Through a novel prior-dependent regret analysis of the posterior sampling procedure, we showed
that when the offline data is informative enough, the iPSRL algorithm can significantly reduce the learning regret compared to the baseline. Based on iPSRL, we then
proposed the more practical iRLSVI algorithm and we showed that in episodic MDP learning problems, it can significantly reduce regret via empirical results.
Biography: Dengwang Tang is currently a postdoctoral researcher at University of Southern California. He obtained his B.S.E in Computer Engineering from University of Michigan,
Ann Arbor in 2016. He earned his Ph.D. in Electrical and Computer Engineering (2021), M.S. in Mathematics (2021), and M.S. in Electrical and Computer Engineering (2018) all
from University of Michigan, Ann Arbor. Before joining USC, he was a postdoctoral researcher at University of California, Berkeley. His research interests involve control
and learning algorithms in stochastic dynamic systems, multi-agent systems, queuing theory, and dynamic games.
Host: Pierluigi Nuzzo
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: CS Events
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NL Seminar -Red Teaming Language Model Detectors with Language Models
Thu, Feb 22, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Yihan Wang, UCLA
Talk Title: Red Teaming Language Model Detectors with Language Models
Series: NL Seminar
Abstract: REMINDER: This talk will be a live presentation only, it will not be recorded. Meeting hosts only admit 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 provide your: Full Name, Title and Name of Workplace to (nlg-seminar-host(at)isi.edu) beforehand so we’ll be aware of your attendance. Also, let us know if you plan to attend in-person or virtually. More Info for NL Seminars can be found at: https://nlg.isi.edu/nl-seminar/ The prevalence and strong capability of large language models (LLMs) present significant safety and ethical risks if exploited by malicious users. To prevent the potentially deceptive usage of LLMs, recent works have proposed algorithms to detect LLM-generated text and protect LLMs. In this paper, we investigate the robustness and reliability of these LLM detectors under adversarial attacks. We study two types of attack strategies: 1) replacing certain words in an LLM's output with their synonyms given the context; 2) automatically searching for an instructional prompt to alter the writing style of the generation. In both strategies, we leverage an auxiliary LLM to generate the word replacements or the instructional prompt. Different from previous works, we consider a challenging setting where the auxiliary LLM can also be protected by a detector. Experiments reveal that our attacks effectively compromise the performance of all detectors in the study with plausible generations, underscoring the urgent need to improve the robustness of LLM-generated text detection systems. This talk may also introduce some of our other recent works on trustworthy and ethical LLMs.
Biography: Yihan is Ph.D. student at UCLA in Computer Science. She received her B.Eng. degree in Computer Science and Technology from Tsinghua University in June 2020. Ms. Wang's research interest is machine learning, especially improving trustworthiness and generalization of machine learning models. Yihan is currently working with Prof. Cho-Jui Hsieh at UCLA. If speaker approves to be recorded for this NL Seminar talk, it will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI. Subscribe here to learn more about upcoming seminars: https://www.isi.edu/events/
Host: Jon May and Justin Cho
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://youtu.be/Fx1T9lyNDh0?si=qEL0QipveladKDwPLocation: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689
WebCast Link: https://youtu.be/Fx1T9lyNDh0?si=qEL0QipveladKDwP
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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Alfred E. Mann Department of Biomedical Engineering
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Peter Chung, Ph.D., Robert D. Beyer Early Career Chair in the Natural Sciences and an assistant professor in the Department of Physics and Astronomy University of Southern California
Talk Title: Polymers and Parkinsons: Elucidating Protein Function through Soft Matter Paradigms and Techniques
Abstract: Despite being unequivocally linked to Parkinson’s disease, the function of alpha-synuclein remains unclear beyond transiently binding to the lipid membrane of synaptic vesicles (organelles filled with neurotransmitters). This is due, in part, to its intrinsically disordered nature; alpha-synuclein does not fold into a globular structure and instead behaves much like a biopolymer. While precluding traditional characterization methods, this makes alpha-synuclein incredibly amenable to investigation via a polymer physics framework. First, through purpose-designed membrane nanoparticles and advanced synchrotron X-ray methods I will demonstrate that alpha-synuclein binds to and collectively works to sterically-stabilize membrane surfaces, a biological manifestation of polyelectrolyte-stabilized colloids. I will then reconcile observed transient binding to synaptic vesicles by establishing that alpha-synuclein preferentially binds to osmotically-stressed membranes (a proxy for neurotransmitter-filled synaptic vesicles), a newly discovered biophysical function by which alpha-synuclein interrogates organelle contents. Utilizing these insights, I will contextualize alpha-synuclein as a guidepost that spatiotemporally directs non-equilibrium
Biography: Peter Chung is the Robert D. Beyer Early Career Chair in the Natural Sciences and an assistant professor in the Department of Physics and Astronomy at the University of Southern California. His research focuses on the intersection of intrinsically disordered proteins (especially those unequivocally linked to neurodegenerative disease) and soft matter physics, with the hope of understanding emergent phenomena associated with these proteins and repurposing them for basic science research and novel therapeutic approaches. Previously he was a Kadanoff-Rice Postdoctoral Fellow at the University of Chicago and earned his PhD from the University of California, Santa Barbara
Host: Eunji Chung
Location: Olin Hall of Engineering (OHE) - 100 B
Audiences: Everyone Is Invited
Contact: Carla Stanard
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale
dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic, mihailo@usc.edu
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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CSC/CommNetS-MHI Seminar: Milad Siami
Fri, Feb 23, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Milad Siami, Assistant Professor of Electrical and Computer Engineering | Northeastern University
Talk Title: Optimizing sparse interactions for control and sensing in complex networks
Series: CSC/CommNetS-MHI Seminar Series
Abstract:
This presentation introduces innovative strategies for enhancing control and sensing in large- scale complex networks, with a focus on minimizing resource usage to improve system performance. We address the challenge of non-submodular sensor scheduling in large-scale linear time-varying dynamics, tackling combinatorial, non-convex, NP-hard tasks. Beginning with a simple greedy algorithm, we present an approximation bound based on submodularity and curvature concepts, showing its superiority over existing methods. Shifting to discrete-time autonomous vehicle platoons, we employ graph- theoretic principles for state feedback laws, analyzing stability conditions based on underlying graph properties and update cycles. We explore H2-based robustness, demonstrating the impact of network density and update cycles on system performance. Specifically, we show that denser networks (i.e., networks with more communication links) might require faster agents (i.e., smaller update cycles) to outperform or achieve the same level of robustness as sparse networks (i.e., networks with fewer communication links). Practical examples and results from simulations and experiments, including work with Quanser's Qlabs and Qcars, validate the effectiveness of our approaches, emphasizing strategic sensor scheduling and robust design in autonomous vehicle platoons.
Biography:
Milad Siami is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University and a Core Faculty Member of the Institute for Experiential AI at the same institution. Prior to joining Northeastern, he served as a Postdoctoral Associate at the MIT Institute for Data, Systems, and Society. He earned his M.Sc. and Ph.D. degrees in Mechanical Engineering from Lehigh University and was a long- term visiting researcher at the Institute for Mathematics and Its Applications at the University of Minnesota. Additionally, he has experience as a Software Engineering Research Intern in the Modeling and Data Mining Group at Google Research NYC. Dr. Siami's research primarily focuses on the structural/graphical underpinnings of large-scale dynamical networks and enhancing the reliability and security of AI-based autonomous systems. His specific areas of interest include distributed control systems, multi-robot systems, and autonomous networks. His current research is supported by grants from the National Science Foundation (NSF), the Department of Homeland Security (DHS), the Office of Naval Research (ONR), and the Army Research Laboratory (ARL).
Host: Dr. Mihailo Jovanovic, mihailo@usc.edu
More Info: https://csc.usc.edu/seminars/2024Spring/siami.html
More Information: 2024.02.23 Seminar - Milad Siami.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/siami.html
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ECE Seminar
Fri, Feb 23, 2024 @ 03:30 PM - 04:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jorge F. Silva, PhD, Universidad de Chile
Talk Title: Information Theoretic Measures for Representation Learning
Abstract: Information-theoretic measures have been widely adopted for machine learning (ML) feature design. Inspired by this, we look at the relationship between information loss in the Shannon sense and the operation loss in the minimum probability of error (MPE) sense when considering a family of lossy representations (or encoders). In this talk, we introduce a series of results that show how adequate the adoption of mutual information (MI) is for predicting the operational quality of a representation in classification. Our findings support the observation that selecting/designing representations that capture informational sufficiency (IS) is appropriate for learning. However, we also show that this selection is rather conservative if the intended goal is achieving MPE in classification. We conclude by discussing the capacity of the information bottleneck (IB) method to achieve lossless prediction and the expressive power of digital encoders in ML.
Biography: Information-theoretic measures have been widely adopted for machine learning (ML) feature design. Inspired by this, we look at the relationship between information loss in the Shannon sense and the operation loss in the minimum probability of error (MPE) sense when considering a family of lossy representations (or encoders). In this talk, we introduce a series of results that show how adequate the adoption of mutual information (MI) is for predicting the operational quality of a representation in classification. Our findings support the observation that selecting/designing representations that capture informational sufficiency (IS) is appropriate for learning. However, we also show that this selection is rather conservative if the intended goal is achieving MPE in classification. We conclude by discussing the capacity of the information bottleneck (IB) method to achieve lossless prediction and the expressive power of digital encoders in ML.
Host: Dr. Eduardo Pavez
More Information: Jorge Silva Seminar 2.23.24.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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AME Seminar
Mon, Feb 26, 2024 @ 01:30 PM - 02:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Zach Patterson, MIT
Talk Title: Blending Soft and Rigid for Physical Intelligence in Robotics
Abstract: Most large animals have a blend of soft and rigid materials in their load-bearing structures. This design principle is largely overlooked by traditional robotics, which favors rigid materials, and by soft robotics, which predominantly uses soft components. Inspired by the natural integration of these materials in the animal kingdom, my research aims to develop robotic systems that combine soft and rigid elements harmoniously, leading to inherent "physical intelligence.” I will begin with an exploration of manipulators that embody this innovative soft-strong paradigm, followed by a discussion on the critical role of advanced control algorithms in harnessing physical intelligence effectively. Next, I will showcase the application of this soft-rigid hybrid approach in creating biomimetic robots, drawing inspiration from marine creatures like sea turtles and echinoderms. These biomimetic robots serve as versatile experimental platforms, enabling us to explore and elucidate questions in biomechanics and paleobiology that are otherwise challenging to address. I will finally discuss how these diverse categories of robots could revolutionize the interactions of intelligent machines with the environment.
Biography: Zach Patterson is a Postdoctoral Associate at the MIT Computer Science & Artificial Intelligence Lab. His research sits at the intersection of robot design, control, and biomimetics with a focus on utilizing soft robotic technologies. Zach received his B.S. in Mechanical Engineering from the University of Pittsburgh in 2017 and his Ph.D. in Mechanical Engineering from Carnegie Mellon University in 2022.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09Location: Olin Hall of Engineering (OHE) - 406
WebCast Link: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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CSC/CommNetS-MHI Seminar: Ingvar Ziemann
Mon, Feb 26, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Ingvar Ziemann, Postdoctoral Researcher | University of Pennsylvania
Talk Title: Sharp rates in dependent learning theory
Series: CSC/CommNetS-MHI Seminar Series
Abstract: In this talk I discuss some recent advances in supervised learning with dependent data. In particular, the emphasis of this talk is to provide an instance-optimal understanding of learning with dependent data for the square loss function. The approach I present yields rates that match and extend known asymptotics even without any realizability assumption. This stands in stark contrast to typical non-asymptotic results which exhibit variance proxies that are deflated multiplicatively by the mixing time of the underlying data-generating process. Indeed, our results instead scale additively with the mixing time and are thereby only affected by second order statistics in the leading term. The key to obtaining this scaling is the introduction of the notion of a weakly sub-Gaussian class, which allows us to invoke mixed tail generic chaining. This notion is general enough to nearly all cover smooth hypothesis classes and a wide range of parametric classes. As a motivating example, I will also discuss our recent work on multi-task learning. Even when the problem itself is realizable, the analysis of a natural “two-stage” estimator decomposes into two supervised learning problems: one which is realizable, and one which is not. In this setting, we demonstrate how our refined understanding of supervised learning with dependent data can be applied to extend and sharpen existing guarantees for iid multi-task learning.
Biography: Ingvar Ziemann is a postdoctoral researcher at the University of Pennsylvania. He received his PhD in November 2022 from the Division of Decision and Control Systems at The Royal Institute of Technology (KTH) under the supervision of Henrik Sandberg. His research is centered on using statistical and information theoretic tools to study learning-enabled control methods, with a current interest in studying how learning algorithms generalize in the context of dynamical systems. Prior to starting his Ph.D., he obtained two sets of Master's and Bachelor's degrees in Mathematics (SU/KTH) and in Economics and Finance (SSE). Ingvar is the recipient of a Swedish Research Council International Postdoc Grant, the 2022 IEEE Conference on Decision and Control Best Student Paper Award, and the 2017 Stockholm Mathematics Center Excellent Master Thesis Award.
Host: Dr. Lars Lindemann
More Info: https://csc.usc.edu/seminars/2024Spring/ziemann.html
More Information: 2024.02.26 CSC Seminar - Ingvar Ziemann.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Miki Arlen
Event Link: https://csc.usc.edu/seminars/2024Spring/ziemann.html
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ECE Seminar: Dr. Giacomo Nannicini
Tue, Feb 27, 2024 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Giacomo Nannicini, Associate Professor, Epstein Dept of ISE, USC Viterbi School of Engineering
Talk Title: Convex Optimization Algorithms on Quantum Computers
Abstract: Optimization is often mentioned as one of the main application areas for quantum computers, but is this claim backed up by theoretical evidence? In this talk we provide a gentle overview of recent advances in quantum optimization, with an emphasis on algorithms and subroutines for convex optimization problems that lead to rigorous asymptotic speedups. The main results of this talk are a faster classical algorithm for the semidefinite relaxation of the MaxCut problem, an even faster quantum algorithm for the same problem, and a new idea for linear optimization on quantum computers.
Biography: Giacomo Nannicini is an associate professor in the Industrial & Systems Engineering department at the University of Southern California, which he joined in 2022. Prior to that, he was a research staff member in the quantum algorithms group at the IBM T. J. Watson Research Center, and an assistant professor in the Engineering Systems and Design pillar at the Singapore University of Technology and Design. His main research interest is optimization broadly defined and its applications. Giacomo received several awards, including the 2021 Beale--Orchard-Hays prize, the 2015 Robert Faure prize, and the 2012 Glover-Klingman prize.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Webcast: https://usc.zoom.us/j/95762332255?pwd=NitkT2p5c1kvWWp0a0JuUUVNZTRudz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/95762332255?pwd=NitkT2p5c1kvWWp0a0JuUUVNZTRudz09
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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ECE-EP Seminar - Aziza Suleymanzade, Tuesday, Feb. 27th at 2pm via Zoom
Tue, Feb 27, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Aziza Suleymanzade, Harvard University
Talk Title: Building quantum networks: from solid-state defects and Rydberg atoms in cavities to a new scientific frontier with hybrid quantum systems
Series: ECE-EP Seminar
Abstract: The experimental development of quantum networks marks a significant scientific milestone, poised to enable secure quantum communication, distributed quantum computing, and entanglement-enhanced nonlocal sensing. In this talk, I will discuss the recent advancements in the field along with the outstanding challenges through my work on two different platforms: Silicon Vacancy defects in diamond nanophotonic cavities and Rydberg atoms coupled to hybrid cavities. First, I will present our recent results on distributing entanglement across a two-node network with on-chip solid-state defects in cavities which we built at Harvard. We demonstrated high-fidelity entanglement between communication and memory qubits and showed long-distance entanglement over the 35 km of deployed fiber in the Cambridge/Boston area. Second, I will describe our work at the University of Chicago on using Rydberg atoms as transducers of quantum information between optical and microwave photons, with the goal of integrating Rydberg platforms with superconducting circuits and paving the way for advanced quantum network architectures. The talk will conclude with a perspective on the potential of this hybrid platform approach in constructing quantum networks, highlighting the uncharted scientific and technological opportunities it could unlock.
Biography: Aziza is a postdoc at Harvard in the group of Mikhail Lukin. She did her PhD at the University of Chicago in groups of Jon Simon and David Schuster, working on the transduction of single optical to millimeter wave photons using Rydberg atoms in cavities. Aziza got a Bachelor's degree from Harvard University and an MPhil from the University of Cambridge, where she built an experiment for generating potassium-39 BEC in a uniform box potential.
Host: ECE-EP
More Info: https://usc.zoom.us/j/96689616375?pwd=bGJ0dXZZUEdxTjN3bHFlL3ZnVWdVUT09
More Information: Aziza Suleymanzade Seminar Announcement.pdf
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/96689616375?pwd=bGJ0dXZZUEdxTjN3bHFlL3ZnVWdVUT09
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Epstein Institute, ISE 651 Seminar Class
Tue, Feb 27, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Xiaolei Fang, Assistant Professor, Department of Industrial & Systems Engr, North Carolina State University
Talk Title: High-Dimensional Data Analytics for System Condition Monitoring and Performance Improvement
Host: Prof. Qiang Huang
More Information: February 27, 2024.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
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MFD Spring Seminars- Distinguished Lecture Series
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Tue, Feb 27, 2024 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Mark Hersam , North Western University
Talk Title: Mixed-Dimensional Heterostructures for Electronic and Energy Technologies
Abstract: Layered two-dimensional (2D) materials interact primarily via van der Waals bonding, which has created new opportunities for heterostructures that are not constrained by epitaxial lattice matching requirements [1]. However, since any passivated, dangling bond-free surface interacts with another via non-covalent forces, van der Waals heterostructures are not limited to 2D materials alone. In particular, 2D materials can be integrated with a diverse range of other materials, including those of different dimensionality, to form mixed-dimensional van der Waals heterostructures [2]. Furthermore, chemical functionalization provides additional opportunities for tailoring the properties of 2D materials and the degree of coupling across heterointerfaces [3]. In this manner, a variety of optoelectronic and energy applications can be enhanced including photodetectors, optical emitters, supercapacitors, and batteries [4-7]. Furthermore, mixed-dimensional heterostructures enable unprecedented electronic device function to be realized including neuromorphic memtransistors, mixed-kernel heterojunction transistors, and moiré synaptic transistors [8-10]. In addition to technological implications for electronic and energy technologies, this talk will explore several fundamental issues including band alignment, doping, trap states, and charge/energy transfer across mixed-dimensional heterointerfaces.
Biography: Mark C. Hersam is the Walter P. Murphy Professor of Materials Science and Engineering, Director of the Materials Research Center, and Chair of the Materials Science and Engineering Department at Northwestern University. He also holds faculty appointments in the Departments of Chemistry, Applied Physics, Medicine, and Electrical Engineering. He earned a B.S. in Electrical Engineering from the University of Illinois at Urbana-Champaign (UIUC) in 1996, M.Phil. in Physics from the University of Cambridge (UK) in 1997, and Ph.D. in Electrical Engineering from UIUC in 2000. His research interests include nanomaterials, additive manufacturing, nanoelectronics, scanning probe microscopy, renewable energy, and quantum information science. Dr. Hersam has received several honors including the Presidential Early Career Award for Scientists and Engineers, TMS Robert Lansing Hardy Award, AVS Peter Mark Award, MRS Outstanding Young Investigator, U.S. Science Envoy, MacArthur Fellowship, AVS Medard W. Welch Award, and eight Teacher of the Year Awards. Dr. Hersam has been repeatedly named a Clarivate Analytics Highly Cited Researcher with over 650 peer-reviewed publications that have been cited more than 70,000 times with an h-index of 125. An elected member of the National Academy of Inventors with over 170 issued and pending patents, Dr. Hersam has founded two companies, NanoIntegris and Volexion, which are commercial suppliers of nanoelectronic and battery materials, respectively. Dr. Hersam is a Fellow of MRS, ACS, AVS, APS, AAAS, SPIE, and IEEE, and also serves as an Executive Editor of ACS Nano.
Host: Mork Family Department
Location: James H. Zumberge Hall Of Science (ZHS) - 252
Audiences: Everyone Is Invited
Contact: Monique Garcia
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CS Colloquium: Luyi Xing (Indiana University) - Security Foundations for Cloud-based IoT Systems
Wed, Feb 28, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Luyi Xing, Indiana University
Talk Title: Security Foundations for Cloud-based IoT Systems
Abstract: The Internet of Things (IoT) cloud is one of the key pillars of the foundation upon which modern IoT systems rest (Smart Home, Industrial, Smart City, Retail, and Health applications, etc.). IoT manufacturers generally deploy IoT devices under managed PaaS and IaaS IoT cloud services (e.g., AWS IoT Core, Azure IoT Hub, SmartThings, Apple Home/iCloud), which offload much of the security responsibilities and deployment burden to the cloud providers. IoT clouds must trust-manage hundreds of millions of IoT devices and users, and provide device manufacturers reliable and usable tools for secure IoT deployments and control. In IoT systems, compromised security or improper deployments can cause hazardous situations and serious consequences. In this talk, we will focus on three areas of fundamental problems in the security of IoT systems: (1) IoT supply chain, (2) IoT security models and real-world deployments, (3) emerging IoT design and application paradigms. Our systematic research in advancing these areas are backed by formal verification, automatic analysis on protocols and programs, and ML/AI-based semantic analysis and formal-model generation. We developed principled, open-source approaches to reveal emerging threats, and formally verify complex, deployed IoT systems to provide new security and privacy guarantees. We identified more than 50 new types of attacks/vulnerabilities in 200+ IoT devices/services (e.g., smart locks, drones) with serious security, safety, and privacy implications. Our formal verification tools have been adopted by industry and government agencies such as AWS. Our security patches have been adopted and deployed by 50+ IoT vendors (AWS IoT, Apple HomeKit, Samsung SmartThings, Microsoft Azure IoT, Yale Locks, August, iRobot, etc.).
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Luyi Xing is an Assistant Professor in the department of Computer Science, Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington since 2018. He is founder of the System Security Foundations lab at IU. Prior to IU, he had years of professional experience in engineering large production systems at AWS and Amazon. He is a recipient of the NSF CAREER award (2021, IoT systems security), Facebook Research Award (2021, Privacy Enhancing Technologies), 5 Facebook Whitehat awards (2012, 2013, 2020, 2021), Google Developer Data Protection award (2019), Microsoft Whitehat award (2019), Android Security Acknowledgements (2013 - 2016, 2018) and Apple Security Acknowledgement (2015, 2019, 2020), among others. His research has changed the design space (access control, authentication) of hundreds of operating system modules (Unix/Linux based OSes, MacOS, Android, iOS), applications, and online services that almost every citizen uses every day. His research aims at improving guarantees for security and privacy in deployed systems, in particular, IoT, cloud, mobile, and software supply chain, with efforts in formal verification, program analysis, machine learning/NLP, compliance, and technology standardization. His research has led to the discovery of 100+ new types of vulnerabilities in the design of commercial and open-source systems, uncovering new attack techniques and undermining prior security guarantees and assumptions. He is a pioneer for a few key research directions, including formal methods for IoT systems security, logic flaws in systems, iOS security and privacy, and security of IoT standards. He is an active practitioner in applying AI/NLP for system security and formal methods.
Host: Chao Wang
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
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AME Seminar
Wed, Feb 28, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Keya Ghonasgi, Georgia Institute of Technology
Talk Title: Intelligent Wearable Systems for Synergistic Human-Robot Interactions
Abstract: Wearable robots hold immense, untapped potential to enhance human performance through physical interactions combining human and robot abilities. For instance, assistive robots can follow user intent while overcoming limitations like reduced strength due to neurological injuries. Surgical robots can enhance expert surgeons’ skill with precision and accuracy. In the future, wearable robots could become as ubiquitous as smart watches and phones. However, current state-of-the-art solutions face challenges – providing limited improvements in performance, being expensive and impractical for the real-world, or causing discomfort, leading to abandonment. This talk showcases three avenues to unlock the promised synergistic potential of humans and robots.
First, I explore the role of understanding human interaction behaviors in the development of responsive robots. For example, combining data-driven and model-based approaches can help us characterize behaviors and identify generalizable movement patterns. Next, I discuss how robots can be tailored to suit human biomechanics and abilities. For instance, can diverse users easily interact with the device? If not, can humans be taught to interact with non-intuitive robots? Finally, I motivate the need for simultaneous learning in the individual and the robot. Such co-evolving systems enable personalized interactions, especially beneficial for individualized rehabilitation or skill training applications. These research areas are interlinked, requiring an interdisciplinary approach at the intersection of human neuroscience and biomechanics, artificial intelligence, and robot design and control. This research empowers synergistic robot interactions and paves the way for the seamless integration of wearable robots into human life.
Biography: Keya Ghonasgi is a postdoctoral fellow at the Georgia Institute of Technology where she works with lower limb assistive devices. She received her Ph.D. in Mechanical Engineering from the University of Texas at Austin (UT) in 2023 and her M.S. in Mechanical Engineering from Columbia University in 2018. Keya’s research on robotic exoskeletons has led to honors including being selected as a Rising Star in Mechanical Engineering (2022) and a CalTech Young Investigator Lecturer (2023). Keya’s work has been funded through various sources including a UT graduate student fellowship award, an NSF M3X grant, and industry collaborations with Meta Reality Labs and Google Brain. Keya is passionate about developing the next generation of human-interactive technology in the form of wearable robots that harness synergistic human and robot capabilities.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09Location: James H. Zumberge Hall Of Science (ZHS) - 252
WebCast Link: https://usc.zoom.us/j/95892885119?pwd=QXZOZUhrcTJRYk5qZzZwVThrTytVZz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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2024 Viterbi Keynote Lecture
Thu, Feb 29, 2024 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Arogyaswami Paulraj, Emeritus Professor, Stanford University
Talk Title: Big Ideas in Mobile Wireless Technology: Many are Called, but Only Some are Chosen
Series: Viterbi Lecture
Abstract: This talk takes a panoramic view of the evolution of mobile wireless technology from 2G to 5G. The research community has put forth several significant ideas, but only some (as of yet) have actually made it into mobile standards. This talk takes a somewhat simplistic (but hopefully accessible) view of these ideas and outlines the complex tradeoffs that pick winners and losers.
Biography: Paulraj is an Emeritus Professor at Stanford University and a pioneer of MIMO (Multiple Input, Multiple Output) wireless, the key technology adopted in all modern wireless systems. Paulraj served for 25 years with the Indian Navy, leading programs in ASW Naval sonar systems for a decade and, for shorter periods, other major Indian national initiatives in AI, high-speed computing, and combat jet aircraft. He received a Ph.D. from the Indian Institute of Technology, New Delhi, India, in 1973. After prematurely retiring from the Navy in 1991, Paulraj joined Stanford University as a research associate. Paulraj founded Iospan Wireless Inc., which pioneered MIMO-OFDMA wireless technology. He co-founded Beceem Communications Inc., which became the leader in 4G-WiMAX chip sets. And later, he founded Rasa Networks for AI-based WiFi network analytics. These companies were acquired by Intel, Broadcom, and HPE, respectively. Paulraj's recognitions include the 2023 IET Faraday Medal, the 2014 Marconi Prize, the 2011 IEEE Alexander Graham Bell Medal, the 2018 Induction into the US Patent Office’s National Inventors Hall of Fame, and the 2022 Induction into the Wireless History Foundation’s Hall of Fame. He is a member of ten national academies spanning engineering, the sciences, and the arts. His recognitions also include the Friendship Award from the Government of PR China and the Padma Bhushan from the Government of India.
Host: Dr. Richard M. Leahy, leahy@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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