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Conferences, Lectures, & Seminars
Events for December
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Epstein Institute, ISE 651 Seminar Class _LAST CLASS for FALL SEMESTER
Tue, Dec 03, 2024 @ 03:30 AM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Lu Lu, Assistant Professor, Department of Statistics and Data Science, Yale University
Talk Title: Physics-Informed Deep Learning: Blending Data and Physics for Learning Functions and Operators
Host: Dr. Qiang Huang
More Information: FLYER 651 Dr. Lu Lu 12.3.24.png
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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ECE Seminar: Biologically Inspired Algorithm and Hardware Co-Design for Efficient Machine Intelligence
Wed, Dec 04, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Priya Panda, Assistant Professor, Electrical & Computer Engineering Department, Yale University
Talk Title: Biologically Inspired Algorithm and Hardware Co-Design for Efficient Machine Intelligence
Abstract: Artificial Intelligence (AI) is poised to revolutionize society, yet its escalating energy demands pose a formidable challenge to its long-term sustainability. The staggering gap in energy consumption between biological (Human Brain @20watts) and artificial intelligence (ChatGPT @100KWatts) is striking. My research aims to bridge this gap with a bio-inspired, integrative approach, where algorithm-hardware co-design and neuromorphic computing converge to create intelligent, energy-efficient systems. In this talk, I will talk about my group’s recent efforts towards enabling and democratizing spike-based machine intelligence design, simulation, and evaluation across different applications. I’ll explore the distinctive benefits of Spiking Neural Networks (SNNs), especially the use of temporal dynamics, which enhances robustness while offering significant gains in latency, energy efficiency, and accuracy in tasks like video segmentation, human activity recognition, and event sensing. From a hardware perspective, I’ll examine how memory and sparsity management can accelerate SNNs on general-purpose platforms, introducing techniques like input-aware dynamic temporal exit and scaling-free quantization for efficient weight and activation compression. Finally, I will share a vision for the future of energy-efficient AI, where our ongoing efforts in input-aware adaptive computation for large foundation models hold promise for developing end-to-end edge cloud intelligent systems capable of visual, language and multi-faceted visual-language processing. This approach opens the door to deploying low-power embodied AI and robotics.
Biography: Priya Panda is an assistant professor in the Electrical & Computer Engineering department at Yale University, USA and a Visiting Faculty Researcher at Google DeepMind with the vision and compilers/architectures team. She received her B.E. and Master's degree from BITS, Pilani, India in 2013 and her Ph.D. from Purdue University, USA in 2019. During her PhD, she interned in Intel Labs where she developed large scale spiking neural network algorithms for benchmarking the Loihi chip. She is the recipient of the 2019 Amazon Research Award, 2022 Google Research Scholar Award, 2022 DARPA Riser Award, 2023 NSF CAREER Award, 2023 DARPA Young Faculty Award, and the inaugural 2024 Purdue Engineering 38 under 38 award. She has also received the 2022 ISLPED Best Paper Award, 2022 IEEE Brain Community Best Paper Award and 2024 ASP-DAC Best Paper Nomination. Her research interests lie in Spiking Neural Networks, Efficient AI algorithm and hardware design.
Host: Dr. Peter Beerel, pabeerel@usc.edu
Webcast: https://usc.zoom.us/j/96755228104?pwd=NR5BYktbr3Yw36DWAtj5cakkt1qQR0.1 (USC NetID login required)Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/96755228104?pwd=NR5BYktbr3Yw36DWAtj5cakkt1qQR0.1 (USC NetID login required)
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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AME Seminar
Wed, Dec 04, 2024 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Moumita Das, Rochester Institute of Technology
Talk Title: Rigidity and Resilience of Network-like Soft Materials: Insights from Biopolymer Networks and Circadian Colloids
Abstract: Living systems exhibit unique emergent properties such as self-assembly, rigidity, resilience, and robustness. In this talk, I will present results from projects that underscore the importance of understanding these collective properties in network-like soft materials and help to address key questions in the rational design of biomimetic soft materials: Can we engineer composite soft matter to display life-like emergent properties? How can we enhance the tunability and control of such soft matter systems? And, is it feasible to activate synthetic soft materials using biological processes? I will begin by examining potential physical mechanisms that underlie robust and resilient mechanical properties in biopolymer networks in cells and tissues. Utilizing rigidity percolation theory, we explore how composite and heterogeneous composition influence cell and tissue mechanics and suggest design principles for artificial constructs with tunable and robust mechanics. Following this, I will discuss the formation and manipulation of colloidal networks using functionalized clock proteins—proteins that regulate biological clocks—to engineer robust self-assembly kinetics and material properties in colloidal systems. Leveraging such protein-based reaction networks allows us to endow synthetic systems with life-like properties. Our findings demonstrate how understanding the emergent structure-function properties in biological and bio-hybrid systems can support the development of biomimetic materials that not only mirror the robustness and adaptability of living systems but also offer enhanced control over their physical properties and functions.
Biography: Moumita Das is a Professor of Physics at the Rochester Institute of Technology in Rochester, New York, and a Fellow of the American Physical Society. Das received her PhD from the Indian Institute of Science, Bangalore, and did postdoctoral research at Harvard University, University of California Los Angeles, and Vrije Universiteit, Amsterdam, before joining RIT as faculty in 2012. Her research focuses on the interplay of statistical physics, mechanics, and geometry in systems with network-like structures such as the cytoskeleton of cells, the extracellular matrix of soft tissues. Her group uses analytical and computational methods to study their emergent properties and dynamics, aiming to understand the biophysical rules of life and replicate these in synthetic biology systems with experimental collaborators. Her work is supported by awards from the National Science Foundation, the National Institutes of Health, the Keck Foundation, the Moore Foundation, and the Research Corporation. Das also currently serves on the American Physical Society's Committee for the Status of Women in Physics.
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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OKRA Forum: Ranjit Singh Atwal
Thu, Dec 05, 2024 @ 10:00 AM - 11:00 AM
Alfred E. Mann Department of Biomedical Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Ranjit Singh Atwal, Moderna Global Fellow and Research Assistant Professor in Kelley Laboratories at Northwestern University Feinberg School of Medicine
Talk Title: LeaPFrog: Highly Scalable Cell Profiling for Druggable Target Discovery and Therapeutics Development
Abstract: Registration is required for this event: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
Large-scale genetic perturbation and cell profiling technologies have revolutionized the field of molecular biology and has the potential to transform many aspects of healthcare and biotechnology in the coming decade. Nowadays, CRISPR/Cas9-based genome-scale functional genetic screens are being routinely used to identify key genetic regulators of a phenotype of interest. However, the identification of genetic modifications that lead to a phenotypic change requires sorting large numbers of cells, which increases operational times and costs and often limits cell viability. To fully realize the potential of whole-genome CRISPR screening, advances in high-throughput cell sorting technologies are needed. Over the last 5 years, our research group has developed the use of immunomagnetic cell sorting facilitated by microfluidic chips as a rapid and scalable screening platform (termed LeaPFroG) for efficiently and accurately analyzing large numbers of CRISPR-edited cells. I will present how we have leveraged the high-throughput cell sorting capabilities of our LeaPFroG platform as a discovery engine to identify and validate novel checkpoint inhibitors for modulating tumor cell/immune cell interactions and elucidating allele-specific functional regulators of previously undruggable proteins. Lastly, I will outline how the experiences and lessons from these functional studies are being applied to the identification of cellular determinants impacting the mesangial cells in IgA Nephropathy.
Biography: Dr. Ranjit Singh Atwal is a Moderna Global Fellow and Research Assistant Professor in Kelley Laboratories at Northwestern University Feinberg School of Medicine in the Department of Biochemistry and Molecular Genetics. Dr. Atwal received his Ph.D. from McMaster University (Canada) and was a postdoctoral fellow at the Center for Genomic Medicine and faculty member at Massachusetts General Hospital and Harvard Medical School. His research investigations are focused on expanding the use of large-scale phenotypic screening technologies to address unmet needs across diverse biological realms. Current research investigations include the identification of functional regulators of undruggable proteins, rare-cell enrichment based in vivo phenotypic CRISPR screening to identify genetic regulators of metastasis and the use of tissue-selective delivery systems for therapeutic genome editing applications. He is also a founding scientist of a pre-seed startup focused on translating findings at the bench towards the development of targeted therapeutics. As part of the NU-OKRA/NUGokidney Resource Development Core, he is supporting the adaptation of the LeaPFroG platform to enable rapid enrichment of disease-relevant population of kidney cells to empower functional studies to better understand the mechanisms of kidney disease.
Host: Northwestern University & University of Southern California George M. O'Brien Kidney Resource Center
More Info: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
Webcast: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXAMore Information: Webinar graphic - 12.05.24.png
WebCast Link: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
Audiences: Everyone Is Invited
Contact: Greta Harrison
Event Link: https://northwestern.zoom.us/webinar/register/8017315250267/WN_6P8qnb64Qn-VQM84m3tbXA
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NL Seminar-The Duality of Bias in Large Language Models: Leveraging Community Perspectives and Uncovering Ideological Vulnerabilities
Thu, Dec 05, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Zihao He, USC/ISI
Talk Title: The Duality of Bias in Large Language Models: Leveraging Community Perspectives and Uncovering Ideological Vulnerabilities
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. Join Zoom Meeting https://usc.zoom.us/j/98068942358?pwd=MYU6jzrZIjaIYPEuIHG0C61g3BTEXB.1 Meeting ID: 980 6894 2358 Passcode: 716186 Large language models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text. As these models become increasingly integrated into various applications, it is crucial to understand their potential for both beneficial and problematic impacts on society. In this talk, I will explore the dual nature of bias in LLMs through two recent studies that employ similar methodologies but reveal contrasting implications. First, I will discuss COMMUNITY-CROSS-INSTRUCT, an innovative framework that aligns LLMs with online community perspectives to create “digital twins” for efficient public opinion analysis. Then, I will present findings on LLMs’ susceptibility to ideological influences through targeted instruction tuning. By examining these complementary perspectives, I aim to showcase the innovative potential of LLMs in social science research while also highlighting the importance of understanding their malleability. This presentation will contribute to the ongoing dialogue on responsible AI development, illustrating how careful application of LLM capabilities can lead to valuable insights while also emphasizing the need for awareness of their limitations and vulnerabilities.
Biography: Zihao He is a final-year PhD candidate in computer science at University of Southern California (USC). He is advised by Prof. Kristina Lerman. His research interests lie at the intersection of natural language processing and computational social science. Specifically, Zihao has been focusing on evaluating the societal impacts of large language models (LLMs) and investigating their vulnerability to ideological influences. His work has been published in top-tier conferences like ACL, EMNLP, and ICWSM. Previously, Zihao received his undergraduate degree from Beijing University of Posts and Telecommunications (BUPT). He spent one year of master’s studies at Tsinghua University. He has interned at TikTok, Amazon, and DiDi Global. If speaker approves to be recorded for this NL Seminar talk, it will be posted on the 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/ For more information on the NL Seminar series and upcoming talks, please visit: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://www.youtube.com/watch?v=Egqk3ZfbyQ8Location: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=Egqk3ZfbyQ8
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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Is Data All You Need?: Large Robot Action Models and Good Old Fashioned Engineering
Thu, Dec 05, 2024 @ 03:00 PM - 05:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ken Goldberg, Ph.D., William S. Floyd Distinguished Chair of Engineering - UC Berkeley
Talk Title: Is Data All You Need?: Large Robot Action Models and Good Old Fashioned Engineering
Abstract: Enthusiasm has been skyrocketing for humanoids based on recent advances in "end-to-end" large robot action models. Initial results are promising, and several collaborative efforts are underway to collect the needed demonstration data. But is data really all you need?
Although end-to-end Large Vision, Language, Action (VLA) Models have potential to generalize and reliably solve all problems in robotics, initial results have been mixed[1]. It seems likely that the size of the VLA state space and dearth of available demonstration data, combined with challenges in getting models to generalize beyond the training distribution and the inherent challenges in interpreting and debugging large models, will make it difficult for pure end-to-end systems to provide the kind of robot performance that investors expect in the near future.
In this presentation, I share my concerns about current trends in robotics, including task definition, data collection, and experimental evaluation. I propose that to reach expected performance levels, we will need "Good Old Fashioned Engineering (GOFE)" – modularity, algorithms, and metrics. I'll present MANIP[2], a modular systems architecture that can integrate learning with well-established procedural algorithmic primitives such as Inverse Kinematics, Kalman Filters, RANSAC outlier rejection, PID modules, etc. I’ll show how we are using MANIP to improve performance on robot manipulation tasks such as grasping, cable untangling, surgical suturing, motion planning, and bagging, and propose open directions for research.
Presented at:
>Stanford Robotics Seminar, 19 April, 2024 4-min video clip
>Berkeley AI Research (BAIR) Seminar, 24 April, 2024
>IEEE ICRA Workshop, Yokohama Japan, 16 May 2024
>Berkeley Sky Lab Retreat Keynote, Santa Cruz, 29 May 2024
>Amazon Lab 126, Sunnyvale, CA, 18 June 2024
>Apple Park, Cupertino, CA, 24 July 2024
>Toyota Research Lab, San Jose, CA, 31 July 2024
>ICRA@40 Keynote, Rotterdam, 23 Sept 2024
>WAFR Keynote, Chicago, 7 Oct 2024
>Univ of Southern California (USC) Computer Science Distinguished Lecture Seminar, 5 Dec 2024
[1] Nishanth J. Kumar. Will Scaling Solve Robotics? The idea of solving the biggest robotics challenges by training large models is sparking debate. IEEE Spectrum. 28 May 2024.
[2] MANIP: A Modular Architecture for iNtegrating Iteractive Perception into Long-Horizon Robot Manipulation Systems. Justin Yu*, Tara Sadjadpour*, Abby O’Neill, Mehdi Khfifi, Lawrence Yunliang Chen, Richard Cheng, Ashwin Balakrishna, Thomas Kollar, Ken Goldberg. IEEE/RSJ International Conference on Robots and Systems (IROS), Abhu Dhabi, UAE. Oct 2024. Paper
**LOCATION CHANGE**
GINSBURG COMPUTATION HALL (GCS)
AUDITORIUM
This lecture satisfies requirements for CSCI 591: Research Colloquium.
This lecture will be presented as a HYBRID presentation, but will not be recorded.
Zoom details below: https://usc.zoom.us/j/94205149719?pwd=LjETcnHLvCzyDbB6LjjxfknZaab3Dm.1
Meeting ID: 942 0514 9719 | Passcode: 400232
Biography: Ken Goldberg is William S. Floyd Distinguished Chair of Engineering at UC Berkeley and Chief Scientist of Ambi Robotics and Jacobi Robotics. Ken leads research in robotics and automation: grasping, manipulation, and learning for applications in warehouses, industry, homes, agriculture, and robot-assisted surgery. He is Professor of IEOR with appointments in EECS and Art Practice. Ken is Chair of the Berkeley AI Research (BAIR) Steering Committee (60 faculty) and is co-founder and Editor-in-Chief emeritus of the IEEE Transactions on Automation Science and Engineering (T-ASE). He has published ten US patents, over 400 refereed papers, and presented over 600 invited lectures to academic and corporate audiences.
http://goldberg.berkeley.edu
Host: USC Thomas Lord Department of Computer Science
More Info: https://forms.gle/w1r6Yo3se3WU8Bou7
Webcast: https://usc.zoom.us/j/94205149719?pwd=LjETcnHLvCzyDbB6LjjxfknZaab3Dm.1Location: Ginsburg Hall (GCS) - Auditorium
WebCast Link: https://usc.zoom.us/j/94205149719?pwd=LjETcnHLvCzyDbB6LjjxfknZaab3Dm.1
Audiences: Everyone Is Invited
Contact: USC Thomas Lord Department of Computer Science
Event Link: https://forms.gle/w1r6Yo3se3WU8Bou7
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PhD Defense
Fri, Dec 06, 2024 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Talk Title: Efficient and Accurate 3D FISP=MRF at 0.55 T
Abstract: Magnetic Resonance Fingerprinting (MRF) are a set of popular multiparametric quantitative MRI techniques. With the resurgence of interest in mid- and low-field MRI, such as the 0.55 T MR system in Dynamic Imaging Science Center in USC, these techniques have gained growing research and clinical tractions. At 0.55 T, a basic fast imaging with steady-state free precession (FISP)-MRF approach has been shown feasible with promising but unexplored improvements, however, also with substantial quantification biases from reference measurements and literature values. Therefore, how to perform this approach in a more Signal-to-Noise Ratio(SNR) efficiency optimized way and how to improve its quantification accuracy have become interesting research problems.
In this dissertation, I propose a more efficient and accuracy FISP-MRF approach at 0.55 T. I start with improving 0.55 T FISP-MRF SNR efficiency and the approach produces more precise results (up to 50% smaller standard deviation values) but temporarily with unaddressed biases. It includes higher readout duty cycle, constrained reconstruction and artifacts mitigation algorithms. Then, I focus on refining RF excitation designs, which helps to partially suppress the sources of bias, resulting in more accurate quantification (~75% less bias).
Biography: Zhibo Zhu is a PhD candidate in Electrical and Computer Engineering in University of Southern California, advised by Prof. Krishna S. Nayak. He received Bachelor of Science degree in Nanjing University of Post and Telecommunication in 2015 and Master of Science degree in University of Southern California in 2017. His current research interest is improved FISP-MRF at 0.55 T MRI.
Host: Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Bella Schilter
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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Dec 06, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Carla Woods, President of Mann Healthcare Partners and Board member of USC Viterbi
Talk Title: Medical Device Companies: From Idea to a Business, and Everything in Between
Abstract: When an idea is born for a product, few face the opportunities and challenges of Medical Devices. Due diligence and planning are paramount to success. Most of the success of a new idea is not the idea itself, but all that goes into driving a successful venture and understanding how to fit the product in a dynamic existing and highly regulated environment. The opportunity that ideas generate in the medical space is to help people with health issues and improve or even save lives. These opportunities also generate jobs and economic success for collaborators, investors and businesses. Getting there involves mitigating risks, overcoming obstacles, and crossing “the valley death.” This requires investment, knowhow and talent of all types coming together. This talk will walk through examples and considerations to set up the development of an idea for success!
Biography: A USC graduate in Business Administration and Entrepreneurship, Carla has been developing and marketing medical devices for over twenty years. At Advanced Bionics Corporation, she was a key executive building the company up to and through its acquisition by Boston Scientific. She began her career at Pacesetter Systems where she planned new technology applications and product needs for pacemakers. During her tenure at Advanced Bionics/Boston Scientific, she led the business development, product development, industrial design, education, clinical research and marketing for the company and its products including the Precision Spinal Cord Stimulator, the BION® microstimulator, implantable infusion pumps, and the cochlear implant. For these products she holds over 60 U.S. patents. Carla was the recipient of the Boston Scientific Patent Milestone Award and the Advanced Bionics Business Leadership Award. She was a senior executive on the company's intellectual property review board and was the shareholder representative in the Boston Scientific acquisition of Advanced Bionics. In 2007, she became the Vice President of Program Development and Strategic Planning for the Alfred Mann Foundation for Biomedical Engineering. Carla is on the Board of the USC Viterbi School of Engineering and has served on the board of the Pacific Neuroscience Institute, AMI Institutes at USC and Purdue University, the Center for Global Innovation at the USC Marshall School of Business, the National Pain Foundation and the Fulfilment Fund.
Host: Peter Yingxiao Wang- Chair of Alfred E. Mann Department of Biomedical Engineering
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Carla Stanard
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MHI - Physics Joint Seminar Series, Mark Saffman, Friday, Dec. 6th at 2pm in SSL 202
Fri, Dec 06, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mark Saffman, Department of Physics, University of Wisconsin-Madison
Talk Title: Gate Model Quantum Computing with Atom Arrays
Series: MHI Physics Joint Seminar Series
Abstract: Quantum computing with neutral atom qubits has advanced rapidly with the development of large 2D arrays and high-fidelity entangling gates. We have used atomic qubits for a variational simulation of the Lipkin-Meshkov-Glick model incorporating noise mitigation techniques. The talk will provide an overview of architectural options for neutral atom qubit arrays and present new approaches for implementing nonlocal QEC codes and fast measurements, as well as progress towards photonic remote entanglement.
Biography: Mark Saffman is an experimental physicist working in the areas of atomic physics, quantum and nonlinear optics, and quantum information processing. His research team was the first to demonstrate a quantum CNOT gate for the deterministic entanglement of a pair of neutral atoms. This was done using dipole mediated interactions between highly excited Rydberg atoms. He is currently developing scalable arrays of neutral atoms for quantum computation, communication, and sensing applications. He is the Johannes Rydberg Professor of Physics at the University of Wisconsin-Madison and has been recognized with an Alfred P. Sloan fellowship, a Vilas Associate Award, the WARF Innovation Award, and is a fellow of the American Physical Society, and Optica. He has been active in professional service including two decades as an Associate Editor at the Physical Review and is the director of The Wisconsin Quantum Institute. He also serves as Chief Scientist for Quantum Information at Infleqtion, Inc.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Info: https://usc.zoom.us/j/92584409725
More Information: Mark Saffman -Dec 6.pdf
Location: Seaver Science Library (SSL) - 202
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/92584409725
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MHI ISSS Seminar - Dr. Alyosha Molnar, Friday, December 6th at 2pm in EEB 248
Fri, Dec 06, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Alyosha Molnar, Professor, Cornell University
Talk Title: Analog at the Extremes: Circuits from the Edge
Series: Integrated Systems
Abstract: For at least 3 decades techno-polemicists have been predicting the end of analog circuits, even as the field has exploded both commercially and academically. What is true, however, is that analog circuits have changed, as digital computation and analog-to-digital converters have improved by leaps and bounds, pushing many traditionally analog problems into the digital, and even software domain. Some problems, however, remain beyond the reach of purely digital solutions. These problems are characterized by either extremely constrained power and size, or by very high frequency, very high dynamic range requirements. At the same time, such circuits must be designed with a much more algorithm-aware mindset, as they rarely exist in a computation-free environment. I will discuss two examples of such circuits. The first example is a tiny (60um x 300um) neural implant, able to measure and transduce electrophysiological signals from neurons and transmit them wirelessly. These microscale optoelectronically transduced electrodes (MOTEs) can be entirely powered by light (from a 2-photon imaging setup, for example), at levels safe for the brain, while reporting both spiking and synaptic activity in-vivo. The second problem is high dynamic-range RF and mm-Wave receivers. I will discuss our work in N-path mixers and filters which have been shown to enable flexible, interference tolerant receivers, and discuss our recent work mapping N-path designs to mmWave frequencies, while maintaining the mixers' linearity and noise without burning excessive power. I will finish up by discussing of a new style of flexible receiver, which leverages circuit and algorithm co-design to generate diverse combinations of signal and interference artifact. These diverse channels then allow simple algorithms to identification and remove interference artifacts without prior knowledge of the interference itself.
Biography: Alyosha Molnar received his B.S. in Engineering from Swarthmore College and his Ph.D. in Electrical Engineering from UC Berkeley. At Conexant Systems (1998-2002), he co-led the development of the first commercially successful cellular direct conversion receiver and fully integrated quad-band GSM transceiver. Currently the Ilda and Charles Lee Professor of Engineering at Cornell University, his research encompasses RF and mmWave integrated circuits, novel image sensors and processing, neural interface systems, and microscale autonomous systems. His graduate work included pioneering sub-milliwatt radios for "smart dust" and studying biological circuits in the mammalian retina. Since joining Cornell in 2007, his contributions have been recognized with several prestigious honors including the NSF CAREER Award, DARPA Young Faculty Award, ISSCC Lewis Winner Award, and the Darlington Best Paper Award.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Info: https://usc.zoom.us/j/93310952640
More Information: MHI_Seminar_Flyer_Molnar_Dec6_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/93310952640
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World models beyond autoregressive next state prediction
Mon, Dec 09, 2024 @ 03:00 PM - 04:00 PM
Ming Hsieh Department of Electrical and Computer Engineering, Thomas Lord Department of Computer Science, USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Abhishek Gupta, Ph.D., Assistant Professor of Computer Science and Engineering, Paul G. Allen School at the University of Washington
Talk Title: World models beyond autoregressive next state prediction
Series: CSC@USC/CommNetS-MHI Seminar Series
Abstract: Learned models of system dynamics provide an appealing way of predicting the future outcomes in a system, enabling downstream usage for planning or off-policy evaluation in applications such as robotics. However, the prevalent paradigm of autoregressive, next-state prediction in learning dynamics models is challenging to scale to environments with high dimensional observations and long horizons. In this talk, I will present alternative techniques for model learning that go beyond directly predicting next states. Firstly, we will discuss a reconstruction-free class of models that go beyond next-observation prediction by learning the evolution of task-directed latent representations for high dimensional observation spaces. We will then show how this can be generalized to learning a new class of models that avoid autoregressive prediction altogether by directly modeling long-term cumulative outcomes, while remaining task agnostic. In doing so, this talk will propose alternative ways of thinking about model learning that retain the benefits of transferability and efficiency from model-based RL, while going beyond next-state prediction.
Biography: Abhishek Gupta is an assistant professor of computer science and engineering at the Paul G. Allen School at the University of Washington. Prior to joining University of Washington, he was a post-doctoral scholar at MIT, collaborating with Russ Tedrake and Pulkit Agarwal. He completed his Ph.D. at UC Berkeley working with Pieter Abbeel and Sergey Levine, building systems that can leverage reinforcement learning algorithms to solve robotics problems. He is interested in research directions that enable directly performing reinforcement learning directly in the real world — reward supervision in reinforcement learning, large scale real world data collection, learning from demonstrations, and multi-task reinforcement learning. He has also spent time at Google Brain. He is a recipient of the NDSEG and NSF graduate research fellowships, and several of his works have been presented as spotlight presentations at top-tier machine learning and robotics conferences.
Host: Erdem Biyik
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Erdem Biyik
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MHI - Physics Joint Seminar Series - Daniel Sank, Tuesday, December 10th at 2pm in EEB 248 & Zoom
Tue, Dec 10, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Daniel Sank, Quantum AI, Google
Talk Title: Fast and Orderly Decoherence: A Systems Engineering View of Superconducting Qubit Readout and Reset
Series: MHI Physics Joint Seminar Series
Abstract: This presentation is a systems engineer's look at the superconducting qubit system, with focus on the two parts where we need fast and orderly decoherence: readout and reset. We introduce the basic theory of operation of the transmon qubit with focus on readout and reset and discuss the constraints placed by these operations on the off-chip physical apparatus, including package, wiring, cryostat, and the control electronics. Then, we give an in-depth tour of the mechanism, known as Measurement Induced State Transitions (MIST), through which the readout process kicks the qubit out of the computational subspace and into so-called "leakage states" which are poisonous for quantum error correction. Finally, we bring everything together to show how we design devices to respect the constraints introduced by readout and reset while still performing with sufficient speed and accuracy to support quantum error correction.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Info: https://usc.zoom.us/j/92584409725
More Information: Daniel Sank -Dec 10.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/92584409725
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NL Seminar-Harmful Speech Detection by Language Models Exhibits Gender-Queer Dialect Bias
Thu, Dec 12, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Becca Dorn, USC/ISI
Talk Title: Harmful Speech Detection by Language Models Exhibits Gender-Queer Dialect Bias
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. Join Zoom Meeting https://usc.zoom.us/j/98709918457?pwd=sVnp7kgGtL42MLRYEPaGjofzrjJFHL.1 Meeting ID: 987 0991 8457 Passcode: 592675 Content moderation on social media platforms shapes the dynamics of online discourse, influencing whose voices are amplified and whose are suppressed. Recent studies have raised concerns about the fairness of content moderation practices, particularly for aggressively flagging posts from transgender and non-binary individuals as toxic. In this study, we investigate the presence of bias in harmful speech classification of gender-queer dialect online, focusing specifically on the treatment of reclaimed slurs. We introduce a novel dataset, QueerReclaimLex, based on 109 curated templates exemplifying non-derogatory uses of LGBTQ+ slurs. Dataset instances are scored by gender-queer annotators for potential harm depending on additional context about speaker identity. We systematically evaluate the performance of five off-the-shelf language models in assessing the harm of these texts and explore the effectiveness of chain-of-thought prompting to teach large language models (LLMs) to leverage author identity context. We reveal a tendency for these models to inaccurately flag texts authored by gender-queer individuals as harmful. Strikingly, across all LLMs the performance is poorest for texts that show signs of being written by individuals targeted by the featured slur (F1 ≤ 0.24). We highlight an urgent need for fairness and inclusivity in content moderation systems. By uncovering these biases, this work aims to inform the development of more equitable content moderation practices and contribute to the creation of inclusive online spaces for all users.
Biography: Rebecca Dorn is a PhD candidate at the University of Southern California's Information Science Institute where they are co-advised by Kristina Lerman and Fred Morstatter. Previously, they earned their B.S. in Computer Science at UC Santa Cruz, advised by Lise Getoor. Their research focuses on the intersection between AI fairness, natural language processing and computational social science. Lately, their focus has surrounded how NLP systems treat dialects of historically marginalized communities. If speaker approves to be recorded for this NL Seminar talk, it will be posted on the 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/ For more information on the NL Seminar series and upcoming talks, please visit: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://www.youtube.com/watch?v=S82tUYf2ezQLocation: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=S82tUYf2ezQ
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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MHI - Physics Joint Seminar Series - Karan Mehta, Friday, December 13th at 2pm in SSL 202
Fri, Dec 13, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Karan Mehta, Electrical and Computer Engineering, Cornell University
Talk Title: Enhanced Trapped-Ion Quantum Control with Integrated Photonics
Series: MHI Physics Joint Seminar Series
Abstract: Practical quantum information processing requires significant advances over current systems in error and robustness of basic operations, and in scale. Despite the fundamental promise of trapped atomic ion qubits, the optics required pose a major challenge in scaling. Interfacing low-noise atomic qubits with scalable integrated photonics [1] offers a route to scale, enabling extensibility while simultaneously lending robustness to noise in sensitive quantum operations [2]. Beyond scaling, though, such techniques further allow generation of optical field profiles enabling improvements to coherent and incoherent processes [3]. I will discuss modeling work from our group predicting substantially increased cooling rates as well as motional mode bandwidths for ground-state laser cooling in structured light fields [4], routes to quantum logic leveraging related ideas, and early results from recent foundry-fabricated trap devices with fully integrated delivery to realize these schemes. I will also touch on challenges and opportunities for novel photonic materials and devices motivated by atomic quantum systems. [1] K.K. Mehta, C.D. Bruzewicz, R. McConnell, R.J. Ram, J.M. Sage, and J. Chiaverini. "Integrated optical addressing of an ion qubit." Nature Nanotechnology 11, 1066-1070 (2016). [2] K.K. Mehta, C. Zhang, M. Malinowski, T.-L. Nguyen, M. Stadler, and J.P. Home. "Integrated optical multi-ion quantum logic." Nature 586, 533-537 (2020). [3] A. Ricci Vasquez, et al. "Control of an atomic quadrupole transition in a phase-stable standing wave." PRL 130, 133201 (2023). [4] Z. Xing and K.K. Mehta. "Trapped-ion laser cooling in structured light fields." arXiv: 2411.08844 (2024).
Biography: Karan Mehta received BS. Degrees from UCLA in Electrical Engineering and Physics in 2010 and completed his PhD in Electrical Engineering and Computer Science at MIT in 2017, with the support of a DOE Science Graduate Fellowship. From 2017 to 2021 he was an ETH Postdoctoral Fellow and subsequently senior scientist at ETH Zurich. He joined Cornell ECE in January of 2022 where he leads the Photonics and Quantum Electronics group. He is recipient of an NSF CAREER award and a Sloan Research Fellowship in Physics.
Host: Quntao Zhuang, Eli Levinson-Falk, Jonathan Habif, Daniel Lidar, Kelly Luo, Todd Brun, Tony Levi, Stephan Haas
More Information: Karan Mehta -Dec. 13.pdf
Location: Seaver Science Library (SSL) - 202
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
