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Events for October 22, 2024
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Startup Stories- Alex Lee
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Tue, Oct 22, 2024 @ 12:00 AM - 01:00 PM
Viterbi Technology Innovation and Entrepreneurship
Workshops & Infosessions
Every startup has a story. Uncover the blueprint of success in the words of our very own Viterbi Alumni, Alex LEE and hear about resources available to you start a business while at USC.
Alex Lee, USC Viterbi School of Engineering alumnus, is the Co-founder and CEO of Truewind, an AI-powered accounting software startup. Launched in 2023, Truewind has raised $3 million in seed funding and aims to be the virtual CFO for startups by streamlining financial data with AI.Come and hear Alex’s story!
<a href="https://cglink.me/2nB/r397845">RSVP</a>Location: Michelson Center for Convergent Bioscience (MCB) - 101
Audiences: Everyone Is Invited
Contact: Viterbi TIE
Event Link: https://cglink.me/2nB/r397845
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Computational Science Distinguished Seminar Series
Tue, Oct 22, 2024 @ 09:00 AM - 10:30 AM
USC School of Advanced Computing
Conferences, Lectures, & Seminars
Speaker: Vikram Gavini, University of Michigan
Talk Title: Large-scale electronic structure calculations of extended defects in materials
Abstract: Defects play a crucial role in influencing the macroscopic properties of solids—examples include the role of dislocations in plastic deformation, dopants in semiconductor properties, and domain walls in ferroelectric properties. These defects are present in very small concentrations (few parts per million), yet, produce a significant macroscopic effect on the materials behavior through the long-ranged elastic and electrostatic fields they generate. Notably, the strength and nature of these fields, as well as other critical aspects of the defect-core are all determined by the electronic structure of the material at the quantum-mechanical length-scale. However, carefully converged electronic structure studies on extended defects, such as dislocations, have been out of reach due to the cell-size and periodicity limitations of the widely used electronic structure codes.
This talk will discuss the recent developments that have enabled large-scale density functional theory (DFT) calculations, paving the way for electronic structure studies of defects. The first part of the talk will discuss the development of computational methods and numerical algorithms for conducting fast and accurate large-scale DFT calculations using adaptive finite-element discretization, which form the basis for the recently released DFT-FE open-source code. The second part of the talk will focus on electronic structure studies of dislocations using the developed methods and the insights obtained into fundamental questions such as: What is the core size of a dislocation? Are forces on dislocations solely from elastic interactions? Recent studies on using DFT-FE to understand the energetics of <c+a> dislocations in Mg, and the energetics and nucleation kinetics of quasicrystals (ScZn7.33) will be discussed
Biography: Vikram Gavini is Professor of Mechanical Engineering and Materials Science & Engineering at the University of Michigan. He received his Ph.D. from California Institute of Technology in 2007. His interests are in developing methods for large-scale and quantum-accurate electronic structure calculations, numerical analysis of PDEs and scientific computing. DFT-FE, a massively parallel open-source code for large-scale real-space DFT calculations, has been developed in his group. He is the recipient of NSF CAREER Award in 2011, AFOSR Young Investigator Award in 2013, Humboldt Research Fellowship for Experienced Researchers (2012-14), USACM Gallagher Award in 2015, among others. He led the team that received the 2023 ACM Gordon Bell Prize in high performance computing.
Host: The School of Advanced Computing
More Info: https://sac.usc.edu/events/
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://sac.usc.edu/events/
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ECE Seminar: A plug-and-play acceleration framework for generative AI models on the edge
Tue, Oct 22, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Yanzhi Wang, Associate Professor and Faculty Fellow, Dept. of ECE, Northeastern University
Talk Title: A plug-and-play acceleration framework for generative AI models on the edge
Abstract: In the generative AI era, general users need to apply different base models, fine tuned checkpoints, and LoRAs. Also the data privacy and real-time requirement will favor on-device, local deployment of large-scale generative AI models. It is desirable to develop a "plug-and-play" framework such that users can download any generative AI model, click and run on their own device. This poses significant challenge to the current AI deployment frameworks, which are typically time-consuming and requires human expertise of hardware and code generation. We present our effort of OminiX, which is a first step towards unified library and acceleration of generative AI models across various hardware platforms. Integrating our unique front-end library and back-end instantaneous acceleration techniques, which will be open-source soon, we show capability of plug-and-play deployment and state-of-the-art acceleration of various generative AI models, starting from image generation, large language models, multi-model language models, speech generation and voice cloning, real-time chatting engine, real-time translation, video generation, real-time avatar, to name a few. This can be achieved on everyone's own platform.
Biography: Yanzhi Wang is Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University, a senior member of IEEE. His research interests focus on real-time and energy-efficient deep learning and artificial intelligence systems, especially on efficient large language models and large-scale generative AI systems. His research works have been published broadly in (i) machine learning conferences such as AAAI, CVPR, NeurIPS, ICML, ICCV, ICLR, IJCAI, ECCV, KDD, ICRA, ACM MM, ICDM, etc., (ii) architecture and system conferences such as ASPLOS, ISCA, MICRO, HPCA, CCS, VLDB, PLDI, WWW, ICS, PACT, CGO, IPDPS, INFOCOM, ICDCS, DAC, ICCAD, FPGA, FCCM, ISSCC, CICC, RTAS, RTSS, etc., and (iii) IEEE and ACM transactions. His research works have been cited over 20,500 times. He has received six Best Paper Awards and another 12 Best Paper Nominations. He has received the U.S. Army Research Office Young Investigator Program Award (YIP), IEEE TC-SDM Early Career Award, Asia Pacific Signal and Information Processing Association Distinguished Leader Award, Massachusetts Acorn Innovation Award, design contest awards from multiple conferences, and other research awards from Google, MathWorks, etc. His research work has been reported and cited by around 500 media. He has 13 academic descendants as tenure-track faculty members at University of Minnesota, Michigan State University, University of Georgia, Clemson University, etc.
Host: Dr. Sandeep Gupta, sandeep@usc.edu
Webcast: https://usc.zoom.us/j/98817797740?pwd=OfzLgQ5S1Gbb7b7mxxXe9FgST9u99L.1 (USC NetID Login Required)Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
WebCast Link: https://usc.zoom.us/j/98817797740?pwd=OfzLgQ5S1Gbb7b7mxxXe9FgST9u99L.1 (USC NetID Login Required)
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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Generative Models and the Transport of Measure
Tue, Oct 22, 2024 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Gavin Kerrigan, PhD Candidate - Department of Computer Science, UC Irvine
Talk Title: Generative Models and the Transport of Measure
Abstract: A key theme in contemporary generative modeling is the continuous transport of measure, in which a simple reference distribution is gradually transformed into the data distribution. Many recent models, including diffusions and flows, can be viewed through this unifying lens. In this talk, we will first explore some geometric tools for studying dynamics in the space of probability measures. We will then leverage these tools to design generative models, with a focus on applications to inverse problems and complex data structures such as function-valued data.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
In-person ONLY; recording available post-presentation.
Biography: Gavin Kerrigan is a final year PhD candidate in the Department of Computer Science at UC Irvine, where he is advised by Padhraic Smyth. Prior to joining UCI, he obtained a BSc in mathematics from the Schreyer Honors College at Penn State University. His research focuses on advancing the theory and practice of deep generative models, ranging from fundamental methodology to applications in climate science. His work has been recognized through a best paper award at AISTATS'23 for contributions to function-space generative modeling.
Host: USC Machine Learning Center
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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The Algorithmic Abyss: Exploring Autonomy without Robotic Horror
Tue, Oct 22, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Juan Wachs , Professor & University Faculty Scholar, Industrial Engineering School - Purdue University
Talk Title: The Algorithmic Abyss: Exploring Autonomy without Robotic Horror
Abstract: Robots can already solve sophisticated problems ranging from playing games, autonomous driving, and dancing—given enough observational data for training. The core of such success resides in efficient algorithms, compliant hardware and robust computing, all implemented using carefully curated data collected before the training phase. Thus, robots learn in a “sterile” domain, under clean, controlled and to some extent supervised environments. As the target domain changes, however, moving to more quotidian scenarios, robots struggle to perform well. It is hard to think of an autonomous car trained in Silicon Valley being able to successfully navigate the crowded streets of New Delhi. – this is the “algorithm abyss”. Ideally, we would like to robots adapt to challenging settings while immersed in mundane settings, and learn from few observations. To address this hurdle, my work in the area of robotics and autonomous systems focuses on transferring skills and knowledge from controlled settings to the wild. In this talk, I emphasize strategies and techniques to address fundamental challenges in emergent, high-risk, high-stakes scenarios. Specifically, I will discuss work related to telesurgery, skill augmentation and bioinspired designs. While healthcare is one of the research domains discussed, the outcomes and findings are applicable to the range field of autonomous robotics. Progress in these directions will contribute to the public purpose of creating the knowledge for developing robots that are more accessible, effective and sensitive to social needs.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Zoom Details: https://usc.zoom.us/j/99548396089
Biography: Dr. Juan Wachs is a Professor and University Faculty Scholar in the Industrial Engineering School at Purdue University, Professor of Biomedical Engineering (by courtesy), an Adjunct Associate Professor of Surgery at IU School of Medicine, and Adjunct Professor at Johns Hopkins University. He recently served at NSF as a Program Director for Robotics and AI programs at CISE. He is also the director of the Intelligent Systems and Assistive Technologies (ISAT) Lab at Purdue, and he is affiliated with the Regenstrief Center for Healthcare Engineering. He completed postdoctoral training at the Naval Postgraduate School’s MOVES Institute under a National Research Council Fellowship from the National Academies of Sciences. Dr. Wachs received his B.Ed.Tech in Electrical Education in ORT Academic College, at the Hebrew University of Jerusalem campus. His M.Sc and Ph.D in Industrial Engineering and Management from the Ben-Gurion University of the Negev, Israel. He is the recipient of the 2013 Air Force Young Investigator Award, and the 2015 Helmsley Senior Scientist Fellow, and 2016 Fulbright U.S. Scholar, the James A. and Sharon M. Tompkins Rising Star Associate Professor, 2017, and the ACM Distinguished Speaker 2018. Since 2020 he has been elected University Faculty Scholar. He is also the Associate Editor of IEEE Transactions in Human-Machine Systems, Frontiers in Robotics and AI.
Host: Prof. Stefanos Nikolaidis
Webcast: https://usc.zoom.us/j/99548396089Location: Ronald Tutor Hall of Engineering (RTH) - 217
WebCast Link: https://usc.zoom.us/j/99548396089
Audiences: Everyone Is Invited
Contact: Thomas Lord Department of Computer Science
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**No Epstein Institute, ISE 651 Seminar Class - Due to INFORMS**
Tue, Oct 22, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: NO CLASS- INFORMS, NO CLASS- INFORMS
Talk Title: NO CLASS-INFORMS
Host: NO CLASS- INFORMS
Location: Social Sciences Building (SOS) - B2
Audiences: Everyone Is Invited
Contact: Casi Jones/ ISE
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