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Conferences, Lectures, & Seminars
Events for November
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Nov 01, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Remo Rohs, Ph.D., Professor of Quantitative and Computational Biology, Chemistry, Physics and Astronomy and Computer Science, University of Southern California
Talk Title: Engineering+: AI-driven discovery in biology
Abstract: In recent years, research in biology has become increasingly quantitative. This trend is due to two major drivers: Biology now generates large amounts of data in every experiment, and the power of computers has grown exponentially. The combination of data and computing is the basis of biological discovery in the 21st century. This talk will introduce AI-based and other computational methods developed in the Rohs lab with the goal to answer important biological questions related to gene regulation, nucleic acid structure, protein-nucleic acid binding, and drug design. These computational approaches combine biophysics, mathematics, and statistical machine learning. They enable, for instance, the probing a protein for its preference to bind either DNA or RNA or allow for the design of novel drug-like molecules that are not available in current drug libraries. Feature engineering is a crucial factor for the interpretability of these models. The talk will provide a vision for the crucial role of computational biology at the interface of engineering, medicine, and science.
Biography: Biography:Remo Rohs is the founding chair of the Department of Quantitative and Computational Biology. He received his undergraduate and master’s degree in physics at Humboldt University Berlin. His Ph.D. in chemistry is from Free University Berlin and the Max Delbrück Center for Molecular Medicine in Berlin, Germany. Remo Rohs did his postdoctoral training in structural biology at the Weizmann Institute of Science in Israel. He received further training in computational biology and bioinformatics as research scientist at Columbia University in New York. Remo Rohs started his independent faculty career at the University of Southern California in 2010. He received tenure and was promoted to associated professor in 2016 and to full professor in the same year. He became head of the computational biology and bioinformatics faculty in 2016, founded a section of quantitative and computational biology in 2018, and his current department in 2021. He also designed the quantitative biology undergraduate major. His research is primarily funded by the National Institutes of Health.
Host: Stecey Finley
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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MHI - Physics Joint Seminar Series - Yogesh Joglekar, Friday, Nov. 1st at 2pm in SSL 202
Fri, Nov 01, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Yogesh Joglekar, Professor of Physics, Indiana University
Talk Title: Non-Hermitian quantum dynamics: super quantum correlations and breaking the quantum speed limit
Series: MHI Physics Joint Seminar Series
Abstract: Quantum theory provides rules governing much of the microscopic world. It dictates unitarity for isolated systems that when coupled to an environment, undergo decoherence. Among its counter-intuitive consequences are temporal (Leggett-Garg) correlations that exceed the bounds from local, classical theories. In the simplest system - a single qubit - LG correlations are bounded below 1.5 for unitary and decohering dynamics, with excess over 1 indicating "quantumness". Fundamentally, these bounds arise due to limits on the speed at which a quantum state can evolve into an orthogonal one. In recent years, quantum systems undergoing coherent but non-unitary evolution have emerged. They are governed by non-Hermitian, parity-time (PT) symmetric Hamiltonians with exceptional point degeneracies. After a short review of such systems, I will present results for PT-symmetry breaking, temporal correlations that exceed the LG bound of 1.5, and quantum state-transfers that exceed the quantum speed limit in a single trapped ion (arXiv:2304.12413, PRA 108, 032202 (2023)).*Work done with David Allcock group (University of Oregon) and Sourin Das group (IISER, Kolkata).
Biography: Yogesh Joglekar is an experimentally-minded theoretical physicist. After initial training and some time in condensed matter physics, he started moonlighting in the area of PT symmetry with the help of high-school students. They have helped him see how PT symmetry emerges in disparate platforms such as a single LC circuit or a vibrating tank of water. His primary area of research is open classical and quantum systems. He usually has far more questions than answers.
Host: Mercedeh Khajavikhan & Demetri Christodoulides
More Information: Yogesh Joglekar Flyer.pdf
Location: Seaver Science Library (SSL) - 202
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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MHI ISSS Seminar - Dr. Xuan "Silvia" Zhang, Friday, Nov. 1st at 2pm in EEB 132
Fri, Nov 01, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Xuan "Silvia" Zhang, Associate Professor, Northeastern University
Talk Title: Foundational AI Framework for Automated Synthesis of Analog Integrated Circuits
Series: Integrated Systems
Abstract: Artificial intelligence (AI) and machine learning (ML) technologies have profoundly reshaped our world, manifesting their prowess in perception, knowledge generation, and decision making. In a similar fashion, AI/ML will undoubtedly be a disruptive force to revolutionize the IC design process. Due to their labor-intensive nature, analog and radio frequency (RF) circuits take a disproportionate share in design cost and could therefore benefit tremendously from automation. In this talk, I will present the recent work from my lab towards the goal of building a foundational AI framework for analog IC design automation. I will first introduce our deep learning-based method to automate parameter optimization in analog/RF circuits with a unique domain knowledge-infused approach. This method is then expanded to provide robustness and sampling efficiency against design variations caused by process, voltage, and temperature (PVT). Next, I will briefly talk about CktGNN, our hierarchical graph neural network-based approach to synthesizing circuit topology and the first of its kind that leads to the construction of an open-sourced analog circuit dataset (https://github.com/zehao-dong/CktGNN). Finally, I will conclude the talk with a vision statement and roadmap for future AI-driven design automation.
Biography: Dr. Xuan Zhang is an Associate Professor in the Electrical and Computer Engineering Department at Northeastern University. She works across the fields of integrated circuits/VLSI design, computer architecture, and electronic design automation. Dr. Zhang is an IEEE Women in Engineering (WiE) Distinguished Lecturer for 2023-2024, IEEE Circuits and Systems Society (CAS) Distinguished Lecturer for 2022-2023, and the recipient of NSF CAREER Award in 2020. She currently serves as the Associate Editor-in-Chief at IEEE Transactions on Circuits and Systems I (TCAS-I) and Associate Editor at IEEE Transactions on Computer-Aided Designs (TCAD). Her work has received numerous best paper awards and nominations including ISLPED Best Paper Award in 2022, AsianHOST Best Paper Award in 2020, DATE Best Paper Award in 2019, and Best Paper nominations at DAC 2022, ASP-DAC 2021, MLCAD 2020, DATE 2019, and DAC 2017.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Info: https://usc.zoom.us/j/92564669688
More Information: MHI_Seminar_Flyer_Zhang_Nov1_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/92564669688
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CSC/CommNetS-MHI Seminar: Negar Mehr
Mon, Nov 04, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Negar Mehr, Associate Professor, Department of Mechanical Engineering | UC Berkeley
Talk Title: Interactive Autonomy: Game-Theoretic Learning and Control for Multi-Agent Interactions
Series: CSC/CommNetS-MHI Seminar Series
Abstract: To transform our lives, autonomous systems need to interact with other agents in complex shared environments. For example, autonomous cars need to interact with pedestrians, human-driven cars, and other autonomous cars. Autonomous delivery drones need to navigate in the aerial space shared by other drones, or mobile robots in a warehouse must navigate in the factory space shared by robots. The multi-agent nature of such application domains requires us to develop a systematic methodology for enabling efficient interactions of autonomous systems across various applications. In this talk, I will first focus on game-theoretic planning and control for robots. To reach intelligent robotic interactions, robots must account for the dependence of agents' decisions upon one another. I will discuss how game-theoretic planning and control enables robots to be cognizant of their influence on other agents. I will present our recent results on leveraging the structure that is inherent in interactions to develop efficient motion planning algorithms which are suitable for real-time operation on robot hardware. In the second part of the talk, I will focus on how robots can learn and infer the intentions of their surrounding agents to account for agents' preferences and objectives. Currently, robots can infer the objectives of isolated agents within the formalism of inverse reinforcement learning; however, in multi-agent domains, agents are not isolated, and the decisions of all agents are mutually coupled. I will discuss a mathematical theory and numerical algorithms for inferring these interrelated preferences from observations of agents’ interactions.
Biography: Negar Mehr is an assistant professor in the Department of Mechanical Engineering at the University of California, Berkeley. Before that, she was an assistant professor of Aerospace Engineering at the University of Illinois Urbana-Champaign. She was a postdoctoral scholar at Stanford Aeronautics and Astronautics department from 2019 to 2020. She received her Ph.D. in Mechanical Engineering from UC Berkeley in 2019 and her B.Sc. in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, in 2013. She is a recipient of the NSF CAREER Award. She was awarded the IEEE Intelligent Transportation Systems best Ph.D. dissertation award in 2020.
Host: Dr. Lars Lindemann, llindema@usc.edu
More Information: 2024.11.04 CSC Seminar - Negar Mehr.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 05, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hongsheng Zhong, United Parcel Service
Talk Title: Optimizing Global Logistics: Advanced Operations Research and Analytics at UPS
Host: Dr. John Carlsson
More Information: FLYER 651, Dr. Hongsheng Zhong 11.5.24.png
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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Shifting the Frame: The Labors of ImageNet and AI Data
Wed, Nov 06, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Alex Hanna, Director of Research, Distributed AI Research Institute (DAIR)
Talk Title: Shifting the Frame: The Labors of ImageNet and AI Data
Abstract: Artificial intelligence (AI) technologies like ChatGPT, Stable Diffusion, and LaMDA have led a multi-billion dollar industry in generative AI, and a potentially much larger industry in AI more generally. However, these technologies would not exist were it not for the immense amount of data mined to make them run, low-paid and exploited annotation labor required for labeling and content moderation, and questionable arrangements around consent to use these data. Although datasets used to train and evaluate commercial models are often obscured from view under the shroud of trade secrecy, we can learn a great deal about these systems by interrogating certain publicly available datasets which are considered foundational in academic AI research.
In this talk, I investigate a single dataset, ImageNet. It is not an understatement to say that without ImageNet, we may not have the current wave of deep learning techniques which power nearly all modern AI technologies. I begin from three vantage points: the histories of ImageNet from the perspective of its curators and its linguistic predecessor WordNet, the testimony of the data annotators which labeled millions of ImageNet images, and the data subjects and the creators of the images within ImageNet. Academically, I situate this analysis within a larger theory and practice of infrastructure studies. Practically, I point to a vision for technology which is not based on practices of unrestricted data mining, exploited labor, and the use of images without meaningful consent.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Alex Hanna is Director of Research at the Distributed AI Research Institute (DAIR). A sociologist by training, her work centers on the data used in new computational technologies, and the ways in which these data exacerbate racial, gender, and class inequality. She also works in the area of social movements, focusing on the dynamics of anti-racist campus protest in the US and Canada. She holds a BS in Computer Science and Mathematics and a BA in Sociology from Purdue University, and an MS and a PhD in Sociology from the University of Wisconsin-Madison.
Dr. Hanna has published widely in top-tier venues across the social sciences, including the journals Mobilization, American Behavioral Scientist, and Big Data & Society, and top-tier computer science conferences such as CSCW, FAccT, and NeurIPS. Dr. Hanna serves as a Senior Fellow at the Center for Applied Transgender Studies, and sits on the advisory board for the Human Rights Data Analysis Group and the Scholars Council for the UCLA Center for Critical Internet Inquiry.
She is a recipient of the Wisconsin Alumni Association’s Forward Award, has been included on FastCompany’s Queer 50 and Go Magazine’s Women We Love lists, and has been featured in the Cal Academy of Sciences New Science exhibit, which highlights queer and trans scientists of color.
With Emily M. Bender, Dr. Hanna runs the Mystery AI Hype Theater 3000 series, playfully and wickedly tearing apart AI hype for a live audience online on Twitch and on their podcast.
Host: CAIS
More Info: https://cais.usc.edu/events/usc-cais-webinar-with-dr-alex-hanna/
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
Event Link: https://cais.usc.edu/events/usc-cais-webinar-with-dr-alex-hanna/
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AME Seminar
Wed, Nov 06, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Zachary Manchester, Carnegie Mellon University
Talk Title: Composable Optimization for Robotic Motion Planning and Control
Abstract: Contact interactions are pervasive in key real-world robotic tasks like manipulation and walking. However, the non-smooth dynamics associated with impacts and friction remain challenging to model, and motion planning and control algorithms that can fluently and efficiently reason about contact remain elusive. In this talk, I will share recent work from my research group that takes an “optimization-first” approach to these challenges: collision detection, physics, motion planning, state estimation, and control are all posed as constrained optimization problems. We then build a set of algorithmic and numerical tools that allow us to flexibly compose these optimization sub-problems to solve complex robotics problems involving discontinuous, unplanned, and uncertain contact mechanics.
Biography: Zac Manchester is an Assistant Professor of Robotics at Carnegie Mellon University. He holds a Ph.D. in aerospace engineering and a B.S. in applied physics from Cornell University. Zac was a postdoc in the Agile Robotics Lab at Harvard University and previously worked at Stanford, NASA Ames Research Center and Analytical Graphics, Inc. He received a NASA Early Career Faculty Award in 2018 and has led four satellite missions. His research interests include motion planning, control, and numerical optimization, particularly with application to robotic locomotion and spacecraft guidance, navigation, and control.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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NL Seminar-OATH-Frames: Characterizing Online Attitudes Towards Homelessness with LLM Assistants
Thu, Nov 07, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jaspreet Ranjit, USC
Talk Title: OATH-Frames: Characterizing Online Attitudes Towards Homelessness with LLM Assistants
Series: NL Seminar
Abstract: REMINDER: Meeting hosts only admit on-line guests that they know to the Zoom meeting. Hence, you’re highly encouraged to use your USC account to sign into Zoom. If you’re an outside visitor, please inform us at (nlg-seminar-host(at)isi.edu) to make us aware of your attendance so we can admit you. Specify if you will attend remotely or in person at least one business day prior to the event Provide your: full name, job title and professional affiliation and arrive at least 10 minutes before the seminar begins. If you do not have access to the 6th Floor for in-person attendance, please check in at the 10th floor main reception desk to register as a visitor and someone will escort you to the conference room location. ZOOM INFO: https://usc.zoom.us/j/91020044560?pwd=HDtcMbDbHjlohYmDCyDO9brk7PUpeG.1 Meeting ID: 910 2004 4560 Passcode: 920185 Public attitudes towards key societal issues, expressed on online media, are of immense value in policy and reform efforts, yet challenging to understand at scale. We study one such social issue: homelessness in the U.S., by leveraging the remarkable capabilities of large language models to assist social work experts in analyzing millions of posts from Twitter. We introduce a framing typology: Online Attitudes Towards Homelessness (OATH) Frames: nine hierarchical frames capturing critiques, responses and perceptions. We release annotations with varying degrees of assistance from language models, with immense benefits in scaling: 6.5× speedup in annotation time while only incurring a 3 point F1 reduction in performance with respect to the domain experts. Our experiments demonstrate the value of modeling OATH-Frames over existing sentiment and toxicity classifiers. Our large-scale analysis with predicted OATH-Frames on 2.4M posts on homelessness reveal key trends in attitudes across states, time periods and vulnerable populations, enabling new insights on the issue. Our work provides a general framework to understand nuanced public attitudes at scale, on issues beyond homelessness.
Biography: Jaspreet Ranjit is a third-year Computer Science PhD student at the University of Southern California, advised by Professor Swabha Swayamdipta in the DILL Lab and also a Student Leader of the Center for AI in Society. Her research interests lie in investigating to what extent language models can help us understand sensitive societal issues (i.e. homelessness, suicide interventions) by exploring collaborative settings between social science experts and generative models. Previously, she earned her M.S. and B.S. degree from the University of Virginia in Computer Science as a Rodman Scholar.
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://www.youtube.com/watch?v=j5unlGhB-I4Location: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=j5unlGhB-I4
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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Seminar: Responsible and User-Controllable Artificial Intelligence
Thu, Nov 07, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: PrzemysÅaw (Przemek) Kazienko, Full Professor, Wroclaw University of Science and Technology
Talk Title: Responsible and User-Controllable Artificial Intelligence
Abstract: AI has a major positive impact on the economy and their users, providing them with a better experience, increased satisfaction, saving time and even expanding their horizons. Here, however, we focus on the potential negative impact of AI on humans, such as reinforcement of information bubbles, addiction, excessive use, reduced concentration, creativity and curiosity, enhanced consumerism, weakened autonomy to make free choices, interpersonal communication, and human relationships. We indicate what human features cause our increased susceptibility to the influence of RSs and what manipulation mechanisms they can potentially and even unintentionally exploit. We show some use cases in which the goals pursued by business may conflict with the goals of their users. it is also observable that AI-based approaches are evolving from decision-support to decision-making systems. Consequently, we propose the concept of Responsible AI, which respects the goals and beliefs of their users in addition to business goals. Another solution are user-controllable AI systems that may be incorporated in recently investigated Large Language Models (LLMs).
Biography: PrzemysÅaw (Przemek) Kazienko, Ph.D. is a full professor and leader of three research groups: AI and human values, HumaNLP, and Emognition at Wroclaw Tech (Wroclaw University of Science and Technology), Poland. Research carried out by HumaNLP refer to human aspects of NLP, including subjectivity, personalization, context-based NLP, hate speech, emotions, user-controlled LLMs, etc. The Emognition group focuses on emotion recognition from physiological signals. He has authored over 300 research papers, including 50 in journals with impact factor related to personalization and subjective tasks in NLP, Large Language Models (LLMs), self-learning LLMs, ethics and responsibility in AI, affective computing and emotion recognition, social/complex network analysis, deep machine learning, sentiment analysis, collaborative systems, recommender systems, information retrieval, data security, and many others. He gave 30+ keynote/invited talks to international audiences and served as a co-chair of over 20 international scientific conferences and workshops. Also, he initialized and led over 50 projects, including large European ones, chiefly in cooperation with companies with total local budget over €10M. He is an IEEE Senior Member, a member of the Polish Committee for Standardization in AI, and the Ethics Committee for the LLM development.
Host: Shrikanth Narayanan, shri@usc.edu | Kleanthis Avramidis, avramidi@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Miki Arlen
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Alfred E. Mann Department of Biomedical Engineering
Fri, Nov 08, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: John Rogers, Ph.D., Louis Simpson and Kimberly Querrey Professor of Mterials Science and Engineering, Biomedical and Neurological Surgery
Talk Title: Soft, Skin-Interfaced Electronic and Microfluidic Systems for Health Monitoring
Abstract: Over the last decade, a convergence of new concepts in materials science, biomedical engineering, electrical engineering and advanced manufacturing has led to the emergence of diverse, classes of 'biocompatible' electronic and microfluidic systems with skin-like physical properties and wireless operational capabilities. A broad range of clinical-grade sensors of physiological health can be deployed into these platforms. The resulting technologies address health care challenges from the earliest to the latest stages of life, with demonstrated uses in both high and low resource settings, at the hospital and in the home. This talk presents an overview of the most recent fundamental and translational activities in this area, currently in progress at the Querrey-Simpson Institute for Bioelectronics at Northwestern University and at several associated companies.
Biography: Professor John A. Rogers began his career at Bell Laboratories as a Member of Technical Staff in the Condensed Matter Physics Research Department in 1997 and served as Director from the end of 2000 to 2002. He then spent thirteen years at the University of Illinois, as the Swanlund Chair Professor and Director of the Seitz Materials Research Laboratory. In 2016, he joined Northwestern University as the Simpson/Querrey Professor, where he is also Director of the Institute for Bioelectronics. He has co-authored more than 900 papers and he is co-inventor on more than 100 patents. His research has been recognized by many awards, including a MacArthur Fellowship (2009), the Lemelson-MIT Prize (2011), the Smithsonian Award for American Ingenuity in the Physical Sciences (2013), the Benjamin Franklin Medal (2019), a Guggenheim Fellowship (2021), the NAS James Prize for Science and Technology Integration (2022) and the IEEE Biomedical Engineering Medal (2024). He is a member of the National Academy of Engineering, the National Academy of Sciences, the National Academy of Medicine, the National Academy of Inventors and the American Academy of Arts and Sciences.
Host: Maral Mousavi
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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MHI - Physics Joint Seminar Series - Andrew Vlasic, Friday, November 8th at 2pm in SSL 202
Fri, Nov 08, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Andrew Vlasic, PhD, Fundamental Research Lead Quantum Institute, Deloitte Consulting LLP
Talk Title: A Categorical Perspective of Encoding Real-World Data in Quantum Computers
Series: MHI Physics Joint Seminar Series
Abstract: The question of how to encode real-world data in quantum computer has a tremendous amount of importance in the quantum machine learning (QML) community. There are a few proposed metrics to quantify the efficacy of quantum feature maps with the most used criteria being 'expressibility' [1] and 'expressivity' [2]. However, as noted by the authors, there are shortcomings with these two techniques. Our empirical analysis of using the standard schemes of angle encoding, instantaneous quantum polynomial encoding (IQP), and amplitude encoding to perform machine learning tasks on different dataset reveals new insights into our metrics need to be considered when choosing a particular quantum encoding technique [3,4]. Using the perspective of category theory, we propose that quantum encoding techniques should preserve "structures" of classical data. Based on this insight, we proposed technique on comparing the entropy of a point-cloud against the analytic extension of von Neuman entropy applied to quantum operators [5], directly addressing one area of structure. [5]
Biography: Andrew earned a PhD in mathematics from the University of Illinois at Urbana-Champaign and has extensive experience in fundamental and applied research in the academia, DoD, and industry. Andrew has been a postdoc at Queen's University in Ontario, an acting funding officer at the Army Research Office, a senior data scientist at Bank of America, and is currently the fundamental research lead in the Quantum Research Group at Deloitte Consulting. If interested, view Andrew's portfolio on Google Scholar.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Information: Andrew Vlasic-Nov 8.pdf
Location: Seaver Science Library (SSL) - 202
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 12, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Jeff Shamma, Professor, Department Head, and Jerry S. Dobrovolny Chair, Department of Industrial & Enterprise Systems Engineering, University of Illinois at Urbana
Talk Title: Multi-Agent Higher-Order Learning VS Nash Equilibrium
Host: Dr. Maged Dessouky
More Information: FLYER 651 Dr. Jeff Shamma 11.12.24.png
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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ECE Seminar: Scaling Energy Efficiency of Mobile XR using Hardware/Software Codesign
Wed, Nov 13, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Scott Mahlke, Claude E. Shannon Professor of Engineering Sciences, EECS Department, University of Michigan
Talk Title: Scaling Energy Efficiency of Mobile XR using Hardware/Software Codesign
Abstract: Extended Reality (XR) is an important frontier in technology that combines virtual reality (VR) wherein users are immersed in a virtual world and augmented reality (AR) wherein virtual content is overlayed on the real world. Mobile XR focuses on the realization of AR/VR technologies in the context of portable headsets and other wearable technology, which severely restricts power dissipation and weight requirements for the onboard computing and sensory systems. The constraints preclude direct adoption of desktop/server solutions, instead require efficiency scaling by one to two orders of magnitude. To solve this problem, this work focuses on specialization of both the XR software stack and the underlying hardware. On the software side, simultaneous localization and mapping (SLAM) algorithms that track an agent's movements through an unknown environment are too computationally expensive to be applied in a brute-force manner. Instead, we develop SlimSLAM, a domain-specific runtime scheduler, which adapts SLAM algorithmic parameters based on input needs, minimizing computation while maintaining accuracy. SlimSLAM exploits information from a SLAM algorithm's state to detect and adjust over-provisioned parameters in real-time. SlimSLAM outperforms other adaptive approaches by an average of 2.3x with iso-accuracy. On the hardware side, we focus on in-memory computing that enables data parallel computation to occur in-place in an on-chip memory system, thereby eliminating data movement into and out of the processor and achieving high levels of data parallel computation. Specifically, we develop a duality cache architecture that flexibly transforms caches on demand into programmable in-memory accelerators that can execute arbitrary data-parallel programs commonly used in AR/VR. The cache accelerator outperforms a server-class GPU by 3.6x and CPU by 72.6x with only a 3.5% area cost across a range of data parallel applications.
Biography: Scott Mahlke is the Claude E. Shannon Professor of Engineering Sciences in the EECS Department at the University of Michigan. He leads the Compilers Creating Custom Processors research group that focuses on hardware/software technologies for scaling performance, energy efficiency, and cost of computing systems through specialization of the hardware down to the software it runs. Mahlke has won numerous awards including the 2022 IEEE B. Ramakrishna Rau Award, and is a Fellow of the IEEE and ACM.
Host: Drs. Murali Annavaram (annavara@usc.edu) and Viktor Prasanna (prasanna@usc.edu)
Webcast: https://usc.zoom.us/j/97853375830?pwd=3oQpMoZJyA9SVdgaGf40va9ObZJl4r.1 (USC NetID log in required)Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/97853375830?pwd=3oQpMoZJyA9SVdgaGf40va9ObZJl4r.1 (USC NetID log in required)
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Startup Stories- Matt Petros
Wed, Nov 13, 2024 @ 12:30 PM - 02:00 PM
Viterbi Technology Innovation and Entrepreneurship
Conferences, Lectures, & Seminars
Every startup has a story. Uncover the blueprint of success in the words of our very own Viterbi Alumni, Matt Petros and hear about resources available to you start a business while at USC.
Location: Sign into EngageSC to View Location
Audiences: Everyone Is Invited
Contact: Jashan Dhami
Event Link: https://engage.usc.edu/Viterbitie/rsvp?id=399387
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Seminar - Raghuveer (Raghu) M. Rao, Ph.D., Wednesday, November 13th at 1:30pm in EEB 248
Wed, Nov 13, 2024 @ 01:30 PM - 02:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Raghuveer (Raghu) M. Rao, Ph.D., Chief, Intelligent Perception Branch DEVCOM Army Research Laboratory FCDD-RLA-IE
Talk Title: The Army Research Laboratory: Some Current Interests and Opportunities
Abstract: The DEVCOM Army Research Laboratory (ARL) is the primary executor of basic and multiple technical competencies, ARL welcomes collaboration with external partners to further its mission of operationalizing science. The talk will provide an overview of ARL followed by a description of select opportunities and current research efforts.
Biography: Dr. Raghuveer Rao is the Chief of the Intelligent Perception Branch at the DEVCOM Army Research Laboratory (ARL) in Adelphi, Maryland, where he oversees R&D in multimodal computer vision and applications, mainly to autonomous systems and scene understanding. Prior to joining ARL, Dr. Rao was a professor of electrical engineering and imaging science at the Rochester Institute of Technology. He has held visiting appointments with the Indian Institute of Science, the US Air Force Research Laboratory, the US Naval Surface Warfare Center, and Princeton University. He has made multiple research contributions to signal & image processing, communication, and computer vision, and serves as an ABET program evaluator for electrical engineering. Dr. Rao is a life fellow of IEEE and an elected fellow of SPIE.
Host: Richard Leahy
More Information: Raghuveer Rao Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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AME Seminar
Wed, Nov 13, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Robert Kohn, New York University
Talk Title: Mechanism-based mechanical metamaterials
Abstract: The design and analysis of mechanism-based mechanical metamaterials is a relatively new and rapidly growing research area. It studies artificial "materials" that take advantage of "mechanisms" (that is, nontrivialenergy-free deformations) to achieve interesting macroscopic behavior.The relevant mechanics is nonlinear, since mechanisms involve large rotations. While there have been insightful studies of specific examples, some fundamental issues remain poorly understood. This talk will address two of them, namely (a) how to analyze a metamaterial's macroscopic behavior, and (b) whether linear elastic calculations can still be of use in the analysis of such systems, despite the fact that their mechanisms involve large rotations? My talk will start with a broad introduction to this area; then I'll discuss some recent work with Xuenan Li, which focuses on a particular (very rich) example -- the Kagome metamaterial. This system is interesting because it has infinitely many mechanisms, yet it behaves macroscopically as anonlinear elastic material whose stress-free states are compressive conformal maps.
Biography: Robert V. Kohn is Professor Emeritus of Mathematics at New YorkUniversity's Courant Institute of Mathematical Sciences. He received his PhD in Mathematics from Princeton in 1979, then held a two-year NSFPostdoctoral Fellowship which took him to the Courant Institute. He joined the faculty of the Courant Institute 1981, becoming Full Professor in 1988 and Silver Professor in 2017 before choosing to retire in 2022. Much of his work has addressed problems from mechanics and physics using methods from the calculus of variations and partial differential equations. He has, in particular, studied many examples of energy-driven pattern formation, in diverse systems ranging from shape-memory materials to thin elastic sheets. Professor Kohn's recognitions include selection as a member of the American Academy of Arts and Sciences, receipt of the American Mathematical Society's 2014 Leroy P. Steele Award, and being selected as both a SIAM Fellow and a Fellow of the American Mathematical Society.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Nov 15, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Lidan You, Ph.D., Professor of Mechanical and Materials Engineering/Queen's University
Talk Title: Bone Mechanobiology On-a-Chip
Abstract: Bone has the remarkable ability to adapt its composition and structure to suit its mechanical environment. Osteocytes, bone cells embedded in the calcified matrix, are believed to be the mechanosensors and are responsible for orchestrating the bone remodeling process. However, the detailed cellular and molecular mechanisms underlying osteocyte mechanobiology are not well understood. Furthermore, how osteocytes communicate with other cell populations under mechanical loading remains unclear. Recently, several microfluidic platforms were developed to address these questions. In this talk, we will discuss intercellular communication between cell populations under mechanical loading and its implications in managing bone disorders such as bone metastasis prevention. Specifically, we studied the effects of vibration on breast cancer extravasation using our novel microfluidic co-culture platform. Our findings showed that vibration could reduce breast cancer migration by directly co-culturing osteocytes with cancer cells. Vibration also reduced trans-endothelial breast cancer migration (extravasation), suggesting that it may inhibit the early stages of bone metastasis. Additionally, we demonstrated that ZA, the standard treatment for osteolytic bone metastasis, could decrease breast cancer extravasation, and the effect was further enhanced under vibration. This is the first research that targets osteocyte-cancer interactions under vibration using an organ-on-chip system, which is an essential step toward developing a safe treatment for the high-risk population
Biography: Dr. You is a Tier 1 Canadian Research Chair in Cell Mechanics and Mechanobiology, and a Professor of Mechanical and Materials Engineering (MME) at Queen’s University. She earned her Ph.D. from the City University of New York and completed her postdoctoral training at Stanford University. Dr. You joined the MME at Queen’s University in 2024. Prior to joining MME, she held cross-appointed positions at the University of Toronto as the Erwin Edward Hart Professor in Mechanical and Industrial Engineering and as a Professor in the Institute of Biomedical Engineering. Dr. You has received numerous awards and recognitions, including the Early Researcher Award from the Ontario Ministry of Research and Innovation, the Duggan Medal from the Canadian Society of Mechanical Engineering, and has been elected a Fellow of both the Canadian Society of Mechanical Engineering (CSME) and the American Society of Bone and Mineral Research (ASBMR). She has been serving on grant review panels, including those for the National Institutes of Health (NIH) (SBSR), the Canadian Institutes of Health Research (CIHR) (BME, CIB), and Arthritis Society Canada (Innovation, Strategic Operating). Additionally, Dr. You have been a faculty mentor for the Young Investigator Initiative (YII) Workshop, organized by the United States Bone and Joint Initiative (USBJI), since 2017, where she supports and guides early-career investigators in musculoskeletal research.Her research focuses on solving biomechanical questions in the musculoskeletal system at the cellular level. Specifically, her team is working on understanding the anti-resorptive effect of mechanical loading on bone tissue, investigating breast cancer bone metastasis and prostate cancer bone metastasis, studying osteocyte mechanosensitivity in diabetic conditions, and developing advanced microfluidic systems for bone cell mechanotransduction studies.
Host: Peter Wang
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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ISSS - Dr. Matthew Johnston, Friday, Nov. 15th at 2pm in EEB 132
Fri, Nov 15, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Matthew Johnston, Accociate Professor, Oregon State University
Talk Title: Worth the Squeeze: Power and Packaging Approaches for Biosensors and Bioelectronics
Series: ISSS
Abstract: The integration of new materials, sensing modalities, and intelligence in CMOS-based sensor platforms will enable a broad range of miniaturized diagnostic, therapeutic, and monitoring systems. In addition, such devices will require new approaches for long-term powering and operation that avoid battery replacement/recharging. Achieving these goals will require continued chip-level and system-level advancements, as well as new integration and packaging approaches. In this talk, I will focus on two challenges: 1) Thermoelectric energy harvesting applied to wearable devices, including true battery-less, bioelectronic sensors powered by body heat, as well as other ultra-low-power sensors for chemistry and biology; and, 2) emerging Lab-on-CMOS platforms enabled by IC-based sensors and advanced packaging techniques that combine electronics and microfluidics in a single substrate for biosensing applications.
Biography: Dr. Matthew Johnston received the B.S. degree in electrical engineering from the California Institute of Technology, and the M.S. and Ph.D. degrees in electrical engineering from Columbia University. He was a Co-Founder and Manager of Research with Helixis, a Caltech-based spinout developing instrumentation for real-time PCR, from 2007 to its acquisition by Illumina in 2010. Dr. Johnston joined Oregon State University in 2014, where he is currently an Associate Professor with the School of Electrical Engineering and Computer Science. His research interests include the integration of sensors and transducers with silicon CMOS integrated circuits, lab-on-CMOS platforms, ultra-low-power sensors, stretchable circuits, and bio-energy harvesting. Dr. Johnston was the recipient of the 2020 Semiconductor Research Corporation (SRC) Young Faculty Award. He is currently an Associate Editor of the IEEE Transactions on Circuits and Systems II, and he has also served as an Associate Editor for the IEEE Open Journal of Circuits and Systems and the IEEE Transactions on Biomedical Circuits and Systems.
Host: Hossein Hashemi, Mike Chen and Constantine Sideris
More Info: https://usc.zoom.us/j/96947583326
More Information: MHI_Seminar_Flyer_Johnston_Nov15_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/96947583326
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Epstein Institute, ISE 651 Seminar Class
Tue, Nov 19, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Fatma Kilinc-Karzan, Associate Professor of Operations Research & Associate Professor of Computer Science Carnegie Melon University
Talk Title: TBD
Host: Dr. Meisam Razaviyayn
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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Algorithmic Tools for Redistricting: Fairness via Analytics
Wed, Nov 20, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. David Shmoys, Laibe/Acheson Professor and Director of the Center for Data Science for Enterprise & Society - Cornell University
Talk Title: Algorithmic Tools for Redistricting: Fairness via Analytics
Abstract: The American winner-take-all congressional district system empowers politicians to engineer electoral outcomes by manipulating district boundaries. To date, most computational solutions focus on drawing unbiased maps by ignoring political and demographic input, and instead simply optimize for compactness and other related metrics. However, we maintain that this is a flawed approach because compactness and fairness are orthogonal qualities; to achieve a meaningful notion of fairness, one needs to model political and demographic considerations, using historical data. We will discuss a series of papers that explore and develop this perspective. We first present a scalable approach to explicitly optimize for arbitrary piecewise-linear definitions of fairness; this employs a stochastic hierarchical decomposition approach to produce an exponential number of distinct district plans that can be optimized via a standard set partitioning integer programming formulation. This enables a large-scale ensemble study of congressional districts, providing insights into the range of possible expected outcomes and the implications of this range on potential definitions of fairness. Further work extending this shows that many additional real-world constraints can be easily adapted in this framework (such as minimal county splits as was recently required in Alabama legislation in response to the US Supreme Court decision Milligan v. Alabama). In addition, one can adapt the same framework to heuristically optimize for other fairness-related objectives, such achieving a targeted number of majority minority districts (and in taking this approach, achieving stronger results than obtained by a prominent randomized local search approach known as “short bursts”).
We also show that our optimization infrastructure facilitates the study of the design of multi-member districts (MMDs) in which each district elects multiple representatives, potentially through a non-winner-takes-all voting rule (as was proposed in H.R. 4000 in an earlier session of Congress). We carry out large-scale analyses for the U.S. House of Representatives under MMDs with different social choice functions, under algorithmically generated maps optimized for either partisan benefit or proportionality. We find that with three-member districts using Single Transferable Vote, fairness-minded independent commissions can achieve proportional outcomes in every state (up to rounding), and this would significantly curtail the power of advantage-seeking partisans to gerrymander.
This is joint work with Wes Gurnee, Nikhil Garg, David Rothschild, Julia Allen, Cole Gaines, David Domanski, Rares-Stefan Bucsa, and Daniel Brous.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: David Shmoys is the Laibe/Acheson Professor and Director of the Center for Data Science for Enterprise & Society at Cornell University. He obtained his PhD in Computer Science from the University of California at Berkeley in 1984, and held postdoctoral positions at MSRI in Berkeley and Harvard University, and a faculty position at MIT before joining the faculty at Cornell University. He was Chair of the Cornell Provost’s “Radical Collaborations” Task Force on Data Science and was co-Chair of the Academic Planning Committee for Cornell Tech. His research has focused on the design and analysis of efficient algorithms for discrete optimization problems, with applications including scheduling, inventory theory, computational biology, computational sustainability, and data-driven decision-making in the sharing economy. His work has highlighted the central role that linear programming plays in the design of approximation algorithms for NP-hard problems. He was awarded the 2022 INFORMS Optimization Society Khachiyan Prize, the 2023 INFORMS Morse Lectureship, and the 2024 INFORMS Kimball Medal. His book (co-authored with David Williamson), The Design of Approximation Algorithms, was awarded the 2013 INFORMS Lanchester Prize and his work on bike-sharing (joint with Daniel Freund, Shane Henderson, and Eoin O’Mahony) was awarded the 2018 INFORMS Wagner Prize. David is a Fellow of the ACM, INFORMS, and SIAM, and was an NSF Presidential Young Investigator.
Host: CAIS
More Info: https://cais.usc.edu/events/usc-cais-seminar-with-dr-david-shmoys/
Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Hailey Winetrobe Nadel, MPH, CHES
Event Link: https://cais.usc.edu/events/usc-cais-seminar-with-dr-david-shmoys/
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AME Seminar
Wed, Nov 20, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Adrian Lew, Stanford
Talk Title: The Art and the Science of Metal 3D Printing
Abstract: This is the title of a class I teach at Stanford on metal 3D printing, and it reflects my perspective on where metal 3D printing is today: part art and part science, because of the complexities and multiple physical processes at play. Printing strategies are inspired in science, but when it comes time to print a new alloy or a complex geometry, the art storms in to help bridge the gaps in understanding. A goal in metal 3D printing research is to shift this balance towards science.
In this talk I will first describe the main physical processes involved one of the most widely adopted metal 3D printing technologies, Laser Powder Bed Fusion (LPBF), and then showcase three vignettes of contributions we made: (a) in-situ alloying and printing of tantalum-tungsten alloys, (b) the “surprising” behavior of some martensitic steels under 3D printing conditions, (c) two ways to alter the optical absorptivity of highly-reflective metallic powders to facilitate printing of copper in some standard printers. The art and the science are interweaved in the three contributions.
Biography: Adrian J. Lew is a Professor of Mechanical Engineering and the Institute for Computational and Mathematical Engineering at Stanford University. He graduated with the degree of Nuclear Engineer from the Instituto Balseiro in Argentina, and received his master of science and doctoral degrees in Aeronautics from the California Institute of Technology. He is a fellow of the International Association for Computational Mechanics, and has been awarded Young Investigator Award by the International Association for Computational Mechanics, the ONR Young Investigator Award, the NSF Career Award, and the Ferdinand P. Beer & Russel Johnston, Jr., Outstanding New Mechanics Educator Award from the American Society of Engineering Education. He has also received an honorable mention by the Federal Communication Commission for the creation of the Virtual Braille Keyboard. He was the first USACM Technical Thrust Area Lead for Manufacturing, and still serves it as a member. He is currently member of the Technical Advisory Board for Velo 3D, a metal 3D printing start-up located in Campbell, CA, and consultant to other metal 3D printing companies.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Webcast: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/96060458816?pwd=8LmoG2q6vBCQubqqWpcizd2F1bxqsH.1
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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ECE Seminar: Advanced Algorithms for Physical Design Automation Targeting 2D and 3D ICs
Thu, Nov 21, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Sung Kyu Lim, Motorola Solutions Foundation Professor, Georgia Institute of Technology
Talk Title: Advanced Algorithms for Physical Design Automation Targeting 2D and 3D ICs
Abstract: In this talk, we present advanced algorithms, both conventional and AI-driven, developed to automate the manufacturing-ready layout generation of high-performance 2D and 3D integrated circuits. We utilize traditional algorithms such as graph search, mathematical programming, stochastic optimization, and dynamic programming to automate and refine the physical layouts of 2D and 3D ICs, focusing on power, performance, area (PPA), and electro-thermo-mechanical reliability. Our AI-driven methodologies include the use of generative AI, reinforcement learning enhanced by active learning, graph neural networks, and transformers. We demonstrate how these cutting-edge algorithms address complex challenges in physical design automation for 2D and 3D ICs.
Biography: Prof. Sung Kyu Lim earned his Ph.D. in Computer Science from UCLA in 2000. Since 2001, he has been a faculty member at the School of Electrical and Computer Engineering at the Georgia Institute of Technology. His research explores the architecture, design, and electronic design automation (EDA) of 2.5D and 3D integrated circuits, contributing to over 400 published papers. He received the Best Paper Awards from the IEEE Transactions on CAD in 2022 and the ACM Design Automation Conference in 2023. He is an IEEE Fellow and served as a program manager at DARPA's Microsystems Technology Office from 2022 to 2024.
Host: Dr. Peter Beerel, pabeerel@usc.edu
Webcast: https://usc.zoom.us/j/94963582840?pwd=Sf9z2kOLhLbBUl5Z7FBeOiGbbJI0Tx.1 (USC NetID login required to join seminar)Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/94963582840?pwd=Sf9z2kOLhLbBUl5Z7FBeOiGbbJI0Tx.1 (USC NetID login required to join seminar)
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Semiconductors & Microelectronics Technology Seminar - Azadeh Ansari, Thursday, Nov. 21st at 2:15pm in EEB 248
Thu, Nov 21, 2024 @ 02:15 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Azadeh Ansari, Georgia Institute of Technology
Talk Title: MEMS for Next Generation Radio Frequency and Biomedical Applications
Series: Semiconductors & Microelectronics Technology
Abstract: With the ever-increasing number of wireless devices, the frequency spectrum is getting more crowded and the need for signal filtering at emerging wireless bands is ever more critical. Recent advances in thickness downscaling of piezoelectric transducers have opened up new horizons for resonator operation at the millimeter wave frequencies; and enabled the use of nonlinearities in nanomechanical devices. I will present my group's work on developing novel Aluminum Scandium Nitride acoustic resonators, as well as nanomechanical frequency combs. In the second part of the talk, I will present my group's work on the fabrication, actuation and control of micro robotics systems. The recent advances in the nanofabrication and 3D printing at the nanoscale offer robotic solutions at exceedingly small scales that are instrumental for biomedical applications.
Biography: Azadeh Ansari is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Tech. Her research focuses on resonant MEMS, acoustics, micromachined integrated sensors, and micro-robotics. She earned the M.S and Ph.D. degrees in Electrical Engineering from University of Michigan, Ann Arbor in 2013 and 2016. Prior to joining Georgia Tech, she was a postdoctoral scholar in the Physics Department at Caltech. She is the recipient of the 2023 IEEE Transducers Early Career Award, 2021 Roger Webb Outstanding Junior Faculty Award from Georgia Tech, 2020 NSF CAREER award, 2017 ProQuest Distinguished Dissertation Award from the University of Michigan, as well as 2016 University of Michigan Richard and Eleanor Towner Prize for outstanding Ph.D. research.
Host: J Yang, C Zhou, S Cronin, W Wu
More Information: Azadeh Ansari Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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AI Seminar- Do We Need Large Language Models for Time Series?
Fri, Nov 22, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Vinayak Gupta, Lawrence Livermore National Laboratory
Talk Title: Do We Need Large Language Models for Time Series?
Abstract: Abstract-Join Zoom Meeting: https://usc.zoom.us/j/98248194762?pwd=KCPIsauraEJDFnw102leuBjxehbbiM.1 Meeting ID: 982 4819 4762 Passcode: 470845 Register in advance for this webinar: https://usc.zoom.us/webinar/register/WN_78--B06ZRNub3zx6WKvfmg After registering, you will receive a confirmation email containing information about joining the webinar. Visit links below to subscribe and for details on upcoming seminars: https://www.isi.edu/isi-seminar-series/ https://www.isi.edu/events/ Recent large language models (LLMs) have only shown potential for reasoning with text and image data. We explore this reasoning ability with one of the most important data formats: time-series. Capturing the sequential nature of time-series data is crucial to power applications in finance and healthcare. This talk presents a first-of-its-kind benchmark that focuses on truly understanding time-series data and goes beyond the existing evaluations. Additionally, we will discuss the notable limitations of existing works claiming that LLMs can perform forecasting. Our analysis across such models finds that simply removing the LLMs or replacing them with a basic attention layer improved results in most cases, and also led to better scalable solutions.
Biography: Vinayak Gupta is a researcher in the AI Research Group at the Lawrence Livermore National Laboratory. Prior to this, he was a postdoctoral scholar at the University of Washington, Seattle, and an AI Scientist at IBM Research. His research focuses on mining large-scale time-series data, and more recently, he has been working on leveraging LLMs to jointly understand text+time-series. He received his PhD from the Indian Institute of Technology, Delhi in 2022. He was a runner-up in the AI Gamechangers of India and was featured as an AI expert in India AI, the AI initiative of the Government of India. Host: Abel Salinas, POC: Pete Zamar If speaker approves to be recorded for this AI Seminar talk, it will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.
Host: Abel Salinas and Pete Zamar
More Info: https://www.isi.edu/events/5181/do-we-need-large-language-models-for-time-series/
Webcast: https://usc.zoom.us/j/98248194762?pwd=KCPIsauraEJDFnw102leuBjxehbbiM.1Location: Information Science Institute (ISI) - Virtual Only
WebCast Link: https://usc.zoom.us/j/98248194762?pwd=KCPIsauraEJDFnw102leuBjxehbbiM.1
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/events/5181/do-we-need-large-language-models-for-time-series/
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Automatic Evaluation of Clinical Notes Generated from Doctor-Patient-Conversations
Mon, Nov 25, 2024 @ 11:00 AM - 11:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Mojtaba Elyaderani, Data Science Specialist - Solventum Corporation, Health Information Systems Business
Talk Title: Automatic Evaluation of Clinical Notes Generated from Doctor-Patient-Conversations
Abstract: Detailed detailed clinical documentation based on doctor-patient conversations is a necessary yet burdensome task for physicians and is often cited as one of the leading causes of physician burn-out. One way to reduce the documentation workload on physicians is to hire medical scribes, who assist in writing clinical notes. However, this option is costly and difficult to scale, putting it beyond the reach of many practitioners. This has led to the emergence of the ``ambient clinical documentation'' framework, where the conversation between doctor and patient is recorded and transcribed (with the patient's permission) and passed to a clinically trained Language Model (LM) which generates the corresponding note. Despite the recent improvements in their performance, modern LMs still make many errors that are unacceptable in a medical setting and can generate clinical notes that are of poor quality. For example, they may miss critical information, contain hallucinated content, or include important information in wrong note sections. Delivering poor-quality notes to physicians can be an extra burden, potentially resulting in a more time-consuming note creation process than simply starting from scratch. This proves the necessity of evaluating LM-generated clinical notes in a scalable and efficient manner. In this presentation we will introduce few such approaches and examine their weaknesses and strengths.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Zoom Link: https://usc.zoom.us/j/95154565194?pwd=LMaaRHXgKCeabJ7UxufaOW3HUu5Ys2.1
Host: Associate Prof. Meisam Razaviyayn
Webcast: https://usc.zoom.us/j/95154565194?pwd=LMaaRHXgKCeabJ7UxufaOW3HUu5Ys2.1Location: Olin Hall of Engineering (OHE) - 136
WebCast Link: https://usc.zoom.us/j/95154565194?pwd=LMaaRHXgKCeabJ7UxufaOW3HUu5Ys2.1
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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**No Epstein Institute, ISE 651 Seminar Class - Thanksgiving Recess**
Tue, Nov 26, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
