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Events for the 4th week of November
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EiS Communications Hub - Tutoring for Engineering Ph.D. StudentsMon, Nov 18, 2024 @ 10:00 AM - 12:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Come to the EiS Communications Hub for one-on-one tutoring from Viterbi faculty for Ph.D. writing and speaking projects!
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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DREAM Industry Mentorship speaker series
Mon, Nov 18, 2024 @ 12:00 PM - 01:00 PM
USC Viterbi School of Engineering
University Calendar
DREAM connects students with experienced industry professionals from a variety of tech and destination companies who help them create a vision for their futures, align their careers around purpose, and build character in the context of growth, reinvention, and constant change. Industry mentors discuss how professional challenges present opportunities for character and leadership development. This event features actor and activist Emily Proctor on navigating life transitions and what she learned on her journey through Hollywood and beyond.
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Elisabeth Arnold Weiss
Event Link: https://cglink.me/2nB/r400352
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CSC/CommNetS-MHI Seminar: Cristian-Ioan Vasile
Mon, Nov 18, 2024 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Cristian-Ioan Vasile, Assistant Professor of Mechanical Engineering and Mechanics Department, Lehigh University
Talk Title: Robust and Relaxed Temporal Logic Planning for Robot Systems
Series: CSC/CommNetS-MHI Seminar Series
Abstract: Robots are deployed in an increasing number of environments and applications, and tasked with ever complex missions with temporal, logical, and timing constraints. Practical and safety considerations impose that solutions are robust to perturbations and noise, and able to handle infeasible scenarios as best as possible. A planner for a self-driving car may not just return without a solution, it still needs to steer the car as best possible. A multi-agent team should not abandon a mission if one robot fails during deployment. A delivery robot should find alternatives and swap unavailable groceries based on the user's preferences. In this talk, we present and clarify the robustness and relaxation of temporal logic specifications. We present automata- and mixed integer linear programming (MILP) methods to address them in various mission settings for single- and multi-robot systems. We use automata to capture multiple relaxation semantics and provide a model for abstraction of rich user-preferences. We achieve scalability with respect to number of agents and specification complexity in multi-robot missions via MILP encodings while ensuring robust satisfaction in case of feasibility and partial satisfaction otherwise. We apply these techniques to coordinate heterogeneous teams of robots, robot swarms, and modular aerial robotic systems.
Biography: Cristian-Ioan Vasile is an assistant professor in the Mechanical Engineering and Mechanics department, and Computer Science and Engineering (courtesy) at Lehigh University. He leads the Explainable Robotics Lab (ERL) as part of the Autonomous and Intelligent Robotics Lab (AIRLab) at Lehigh University. Previously, he was a postdoctoral associate in the Laboratory for Information and Decision Systems (LIDS), and the Computer Science and Artificial Intelligence Laboratory (CSAIL) at Massachusetts Institute of Technology (MIT). He obtained his PhD in 2016 from the Division of Systems Engineering at Boston University, where he worked in the Hybrid and Networked Systems (HyNeSs) Group of the BU Robotics Laboratory. He obtained a BS degree in Computer Science in 2009, a MEng in Intelligent Control Systems in 2011, and a second PhD in Systems Engineering in 2015, all from the Faculty of Automatic Control and Computers, Politehnica University of Bucharest. His research goal is to enable robot autonomy via scalable automated synthesis of explainable plans using motion planning and machine learning. His work employs techniques from sampling-based motion planning, formal methods, automata and graph theory, optimization, control theory, and machine learning.a Professor in the Department of Aerospace and Mechanical Engineering and the Department of Physics and Astronomy at the University of Southern California, where she also holds the named chair “Z. H. Kaprielian Fellow in Engineering”". Kanso earned PhD and Masters degrees in Mechanical Engineering (1999, 2003) and Applied Mathematics (2002) from UC Berkeley, followed by a post-doctoral training at Caltech (2003-2005). She served as a Program Director at the National Science Foundation (2021-2023). Kanso's research focuses on studying fundamental problems in the biophysics of cellular and subcellular processes and the physics of animal behavior, both at the individual and collective levels. A central theme in her work is the role of the mechanical environment, specifically the fluid medium and fluid-structure interactions, in shaping and driving biological functions.
Host: Dr. Lars Lindemann, llindema@usc.edu
More Information: 2024.11.18 CSC Seminar - Cristian-Ioan Vasile.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Miki Arlen
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USC CMAA Annual Symposium Future Foundations Intuit Dome A Fan Centric Innovation
Mon, Nov 18, 2024 @ 05:00 PM - 09:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Receptions & Special Events
This year marks the 29th anniversary of the symposium, providing students the opportunity to network and hear from industry professionals in the fields of construction, architecture, engineering, and more. The theme for the night — Future Foundations: Intuit Dome, A Fan-Centric Innovation — centers around the presentation of Los Angeles’s upcoming Intuit Dome Stadium, a state-of-the-art development designed to enhance the fan experience.
The symposium begins with a dinner and cocktail hour, followed by a panel and question-and-answer session with professionals involved in the stadium project. Keynote speakers, including the Mayor of Inglewood, Lead Architect, Community Benefits Director and Project Executives from the Turner-AECOM Joint Venture, share their respective roles and the innovative design features of the Intuit Dome.
We invite you to an evening of networking, learning, and insightful discussions at the USC CMAA’s 29th Annual Symposium, "Future Foundations: Intuit Dome, A Fan-Centric Innovation."
Date: November 18, 2024 Time: 5:00 - 9:00 PM Location: USC Town and GownWhat's in store?
· Cocktail Networking Session – Connect with professionals, alumni, and students from the industry.
· Dinner and Keynote Presentation – Gain exclusive insights into the new Intuit Dome Stadium, a cutting-edge, fan-centric development.
· Panel Discussion – Engage with keynote speakers, including the Mayor of Inglewood and project executives from the Turner-AECOM Joint Venture, as they discuss the innovative design features and transformative impact of the Intuit Dome on the community and the LA Clippers.
· ~$50,000 in Scholarships – Celebrate the achievements of USC students with their scholarship awards.
This symposium provides an excellent opportunity to network with leaders in the field and gain an in-depth understanding of advancements in stadium design and construction.Link to register for Students! (50$ for Non USC CMAA Members, 40$ Deposit for Members)
USC CMAA Symposium - Students Registration for faculty, industry professionals, and company representatives, please contact Brenda He: bbhe@usc.edu" target="_blank" rel="noopener">bbhe@usc.eduMark your calendars and join us for a remarkable evening that promises to inspire and inform.More Information: USC CMAA 29th Annual Symposium QR CODE.png
Location: Town & Gown (TGF) -
Audiences: Everyone Is Invited
Contact: Brenda He
Event Link: https://docs.google.com/forms/d/e/1FAIpQLScw1F0NHXtxJ0jklE_0YzeR5m-2r2WKmBcEaloTm7SY_qAOqQ/viewform
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PhD Thesis Proposal - Lixing Liu
Tue, Nov 19, 2024 @ 12:30 PM - 02:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Leveraging Organizational Hierarchies for Goal Management in Multi-Agent Reinforcement Learning
Date and Time: Nov. 19th, 2024 - 12:30p - 2:00p
Location: ICT 202
Committee Members: William Swartout (chair), Paul Rosenbloom, Kallirroi Georgila, Daniel O’Leary, Emilio Ferrara
Abstract: Effectively assigning credit and managing goals remain central challenges in Multi-Agent Reinforcement Learning (MARL), especially in stochastic environments with varying agent priorities across decision levels. Inspired by organizational hierarchies, this study structures multi-agent systems at different levels of abstraction and coordination. It hypothesizes that integrating a structured goal management mechanism within a MARL pipeline can: 1) improve the performance of prioritized, long-horizon tactical behaviors, 2) enhance the transferability of short-term operational behaviors, and 3) accelerate learning for faster MARL behavior model development. The proposed framework employs a hierarchy-aligned, soft-constraint goal-splitting strategy tailored to each agent’s capabilities, planning horizon, and organizational role. Furthermore, it enhances the manageability and interpretability of learned behaviors by incorporating sparse external graph networks to model environmental and inter-agent dynamics. This framework provides a solution for hierarchical goal management in MARL, evaluated for performance, efficiency and team coordination within two-team cooperative-competitive simulations involving complex maneuvers and engagements.
Zoom Link: https://usc.zoom.us/j/8634079147Location: Institute For Creative Technologies (ICT) - 202
Audiences: Everyone Is Invited
Contact: Lixing Liu
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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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WIE Mentorship Thanksgiving Social
Tue, Nov 19, 2024 @ 06:00 PM - 07:00 PM
USC Viterbi School of Engineering
Student Activity
Unwind after midterm season with your mentor/mentee to write and decorate Thanksgiving cards! Dinner will be provided.
Location: Sign into EngageSC to View Location
Audiences: Everyone Is Invited
Contact: Thelma Federico Zaragoza
Event Link: https://engage.usc.edu/WIE/rsvp?id=401186
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EiS Communications Hub - Tutoring for Engineering Ph.D. Students
Wed, Nov 20, 2024 @ 10:00 AM - 12:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Come to the EiS Communications Hub for one-on-one tutoring from Viterbi faculty for Ph.D. writing and speaking projects!
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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Computer Science General Faculty Meeting
Wed, Nov 20, 2024 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty and staff only. Event details emailed directly to attendees.
Location: Ginsburg Hall (GCS) - 107
Audiences: Invited Faculty Only
Contact: Julia Mittenberg-Beirao
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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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PhD Thesis Proposal - Hayley Song
Wed, Nov 20, 2024 @ 02:15 PM - 03:15 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Riemannian-Geometric Fingerprints of Generative Models
Date: November 20, 2024
Time: 2:15 pm - 3:15 pm
Location: KAP 209
Committee: Laurent Itti, Chair, Emilio Ferrara, Kyler Siegel, Robin Jia, and Willie Neiswanger
Abstract: Recent breakthroughs and rapid integration of generative models (GMs) have sparked interest in the problem of model attribution and their fingerprints.For instance, service providers need reliable methods of authenticating their models to protect their IP, while users and law enforcement seek to verify the source of generated content for accountability and trust. In addition, a growing threat of model collapse is arising, as more model-generated data are being fed back into sources (e.g., YouTube) that are often harvested for training ("regurgitative training''), heightening the need to differentiate synthetic from human data. Yet, a gap still exists in understanding generative models' fingerprints, we believe, stemming from the lack of a formal framework that can define, represent, and analyze the fingerprints in a principled way. To address this gap, we take a geometric approach and propose a new definition of artifact and fingerprint of generative models using Riemannian geometry, which allows us to leverage the rich theory of differential geometry.Our new definition generalizes previous work (Song et al, 2024) to non-Euclidean manifolds by learning Riemannian metrics from data and replacing the Euclidean distances and nearest-neighbor search with geodesic distances and kNN-based Riemannian center of mass. We apply our theory to a new gradient-based algorithm for computing the fingerprints in practice. Results show that it is more effective in distinguishing a large array of generative models, spanning across 4 different datasets in 2 different resolutions (64x64, 256x256), 27 model architectures, and 2 modalities (Vision, Vision-Language). Using our proposed definition can significantly improve the performance on model attribution, as well as a generalization to unseen datasets, model types, and modalities, suggesting its efficacy in practice.Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Ellecia Williams
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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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AME Special Seminar
Thu, Nov 21, 2024 @ 10:00 AM - 11:30 AM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Karen Mulleners, EPFL
Talk Title: Shaping up to Explore and Exploit Unsteady Fluid-structure Interactions
Abstract: Nature is full of thin, flexible objects that bend, flutter, or flap in the wind or the water such as leaves of trees and bushes, insect wings, and fish fins. A remarkable feature that is common to these objects is their ability to deform when interacting with the air or the water in a way that benefits them. Leaves of trees bend in the wind to reduce their resistance and the loads on their stems. The flexibility of insect wings and fish fins can reduce the effort the animals need to stay aloft or to propel themselves and increases their performance and agility. Leaves, insect wings, and fish fins come in a myriad of different shapes and sizes. Surprisingly, the influence of the shape of thin flexible objects on their fluid structure interactions has not yet received much attention. In our lab, we design unsteady fluid-structure interaction experiments to close that gap and fundamentally study how the shape of flexible structures and their ability to reconfigure changes their fluid dynamic performance and resilience in dynamic fluid environments. I will present recent work including experimental investigations of the fluid-structure interactions of deformable flapping wings, reconfiguring disks, and flapping flags.
Biography: Karen Mulleners is an associate professor in the institute of mechanical engineering in the school of engineering at EPFL. She is the head of the unsteady flow diagnostics laboratory (UNFoLD). She is an experimental fluid dynamicist who focuses on unfolding the origin and development of unsteady flow separation and vortex formation. Karen studied physics in Belgium (Hasselt University, previously Limburgs Universitair Centrum) and the Netherlands (TU Eindhoven). She received her PhD in mechanical engineering from the Leibniz Universität Hannover in Germany in 2010 for her work on dynamic stall on pitching airfoils that she conducted as a member of the German aerospace centre (DLR) in Göttingen. Before joining EPFL in 2016, Karen was a (non-tenure track) assistant professor at the Leibniz Universität Hannover in Germany.
Host: AME Department
Location: Olin Hall of Engineering (OHE) - 406
Audiences: Everyone Is Invited
Contact: Tessa Yao
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ECE Seminar: Daniel Neuhold
Thu, Nov 21, 2024 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Daniel Neuhold, CEO, LoconIQ R&D | Klagenfurt, Austria
Talk Title: Entrepreneurial Road Towards a Robust 3D Tracking Solution with UWB
Abstract: As industries strive to enhance quality control and to ensure thorough traceability, the demand for sophisticated 3D tracking solutions drastically increased over the last years. LoconIQ stands out with a robust solution to empower new applications with high-precision and real-time 3D tracking. The company’s main innovations are a time-of-flight based ranging algorithm that allows for sub-centimeter distances measurements and a proprietary sensor fusion that integrates ultra-wideband (UWB) data and auxiliary sensors. The solution utilizes UWB signal characteristics and noise/outlier classification models of sensors to facilitate a weighted unscented Kalman Filter (UKF) approach for the localization. With these innovations, LoconIQ delivers a robust 3D tracking solution at a centimeter level accuracy with latencies of only a few ms. The talk will provide insights into the technology and provide real-life examples, outlining step-by-step improvements from a simple Kalman Filter based localization approach to the company’s current UKF with weighting and an advanced sensor fusion. The talk will, furthermore, provide some insights into the applications for such a technology and address the entrepreneurial journey from a university spin-off to a million-dollar company.
Biography: The talk will be given by Daniel Neuhold, who embarked on his Ph.D. journey focusing on wireless communication for aeronautical applications. More particularly, working with Airbus in a project to eliminates wires from commercial airplanes and Ariane carrier rockets. Aiming to substitute data cables with wireless communication to drastically reduce the aircraft’s weight. Daniel then pivoted to the utilization of the used ultra-wide band (UWB) communication to facilitate real-time and high-precision wireless ranging. With this research topic, Daniel performed a seven-months long research stay at the University of Southern California in 2018. After which, he pursued his entrepreneurial path and patented algorithms for precise and low-latency ranging. These efforts culminated in a first prototype solution, which demonstrated the capabilities of the developed technology to raise millions in funding, leading to the incorporate and scale-up of the company. LoconIQ now enables robust and high-precision 3D tracking with a small and battery-powered sensor device, that comes as a turnkey solution right out-of-the-box.
Host: Dr. Andreas F. Molisch
More Information: 2024.11.21 ECE Seminar - Daniel Neuhold.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 248
Audiences: Everyone Is Invited
Contact: Miki Arlen
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NL Seminar- Weakly Supervised Learning for Adaptive LLM Agents
Thu, Nov 21, 2024 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Da Yin, UCLA
Talk Title: Weakly Supervised Learning for Adaptive LLM Agents
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/98977559622?pwd=IK59VbdZJiGIPV9xjUjabrjEauRDai.1 Meeting ID: 989 7755 9622 Passcode: 307452 LLM agents are revolutionizing complex task-solving through multi-step planning, reasoning, and real-world or simulated interactions. However, their adaptability to unseen tasks and environments remains a challenge, especially with limited training resources. In this talk, I will first introduce Agent Lumos (ACL 2024), a foundational framework for training general-purpose, open-source LLM agents that enables better generalization across domains, by the unified training over the trajectories converted from the ubiquitous, unstructured annotated reasoning rationales. I will also discuss Trial and Error (ACL 2024) and Q* Agent, which foster self-exploration, and collect trajectories for preference optimization and process reward modeling based on environmental feedback. Finally, I will outline future directions, including agent critique and world models, to enhance LLM adaptability with minimal effort.
Biography: Da Yin is a final-year PhD student in Computer Science at UCLA, advised by Prof. Kai-Wei Chang, working in the UCLA NLP lab. He was awarded Amazon PhD Fellowship and Best Paper Award at EMNLP Pan-DL workshop in 2023. He was also the co-organizer of 1st ACL MML workshop, publicity chair of 4th SocalNLP Symposium, and area chair at ACL ARR from 2023. His research interest is building generalizable, adaptive, and inclusive language processing models that can be applied across applications and regions.
Host: Jonathan May and Katy Felkner
More Info: https://www.isi.edu/research-groups-nlg/nlg-seminars/
Webcast: https://www.youtube.com/watch?v=dT-Gaolql1cLocation: Information Science Institute (ISI) - Conf Rm#689
WebCast Link: https://www.youtube.com/watch?v=dT-Gaolql1c
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://www.isi.edu/research-groups-nlg/nlg-seminars/
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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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NOVA Building Stuff: Screening and Panel Discussion
Thu, Nov 21, 2024 @ 06:00 PM - 08:30 PM
USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Join USC Viterbi and PBS SoCal for a special screening of NOVA's Building Stuff!
Humans are the most innovative species on Earth. See how engineers are supercharging our abilities, reaching beyond our horizons, and altering our environment in the upcoming NOVA Building Stuff series.
On Thursday, November 21, join NOVA at the USC Viterbi School of Engineering for a screening of selected clips from the 3-part Building Stuff series paired with a panel discussion featuring experts from the film and a catered reception.
Location: Sign into EngageSC to View Location
Audiences:
Contact: Melissa Medeiros
Event Link: https://engage.usc.edu/viterbi/rsvp?id=401170
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EiS Communications Hub - Tutoring for Engineering Ph.D. Students
Fri, Nov 22, 2024 @ 10:00 AM - 02:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
Come to the EiS Communications Hub for one-on-one tutoring from Viterbi faculty for Ph.D. writing and speaking projects!
Location: Ronald Tutor Hall of Engineering (RTH) - 222A
Audiences: Viterbi Ph.D. Students
Contact: Helen Choi
Event Link: https://sites.google.com/usc.edu/eishub/home
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AME Special Seminar
Fri, Nov 22, 2024 @ 10:00 AM - 11:30 AM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Serhiy Yarusevych, University of Waterloo, Canada
Talk Title: Lifting Surfaces at Aerodynamically low Reynolds numbers: Recent Advances
Abstract: Flow development over lifting surfaces in aerodynamically low Reynolds number flows (Re<500,000) is largely governed by boundary layer separation and subsequent separated sear layer development on the suction side. In the time-averaged sense, rapid laminar-to-turbulent transition in the separated shear layer leads to the formation of a closed recirculating flow region referred to as the Laminar Separation Bubble (LSB). However, LSBs feature rich dynamics associated with the formation and evolution of shear layer roll up vortices leading to laminar-to-turbulent transition. Linear stability analysis confirms that there is a continuous stability spectrum spanning laminar boundary later and separated shear layer regions, linking LSB transition and shear layer vortex shedding to upstream amplification of disturbances that originate from free-stream perturbations in the receptivity region. Flow development in the aft portion of the bubble is highly three-dimensional even on nominally two-dimensional geometries. It manifests in progressive deformation of shear layer vortices and subsequent vortex breakdown. On a finite wing, an open LSB forms due to wing tip and root effects. Away from the affected regions, however, LSB topology and dynamics appear to be quasi two-dimensional despite effective angle of attack variation across the span. Changes in operating conditions, including velocity and angle of attack, can lead to significant transient flow developments associated with bubble bursting (i.e., sudden lengthening or full separation without subsequent reattachment) and LSB re-formation, accompanied by substantial changes in aerodynamic loads.
Biography: Dr. Serhiy Yarusevych is a full professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, Canada. He is directing the Fluid Mechanics Research Laboratory focused on multidisciplinary applications of fluid mechanics in engineering and science, including operation of lifting surfaces at low Reynolds numbers, flows over bluff bodies, free shear flows, flow induced vibrations and noise, and flow control. The associated research involves a combination of experimental, analytical, and numerical tools, with the main emphasis placed on experiments involving particle image velocimetry. His research in Canada was interposed by sabbatical leaves at TU Delft and the University of Bundeswehr Munich, in 2013-2014 and 2019-2020, respectively, involving collaborative research with advanced flow diagnostic tools and volumetric measurements. Dr. Yarusevych is an Alexander von Humboldt Fellow, Mercator Fellow, and Associate Fellow of AIAA. Since 2018, Dr. Yarusevych has been serving as an Editor-in-Chief of Experimental Thermal and Fluid Science, Elsevier.
Host: AME Department
Location: Olin Hall of Engineering (OHE) - 406
Audiences: Everyone Is Invited
Contact: Tessa Yao
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Tom Goldstein- AI Safety Issues in Generative Models: Memorization and Detection
Fri, Nov 22, 2024 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Tom Goldstein, Volpi-Cupal Professor of Computer Science at the University of Maryland, and director of the Maryland Center for Machine Learning
Talk Title: AI Safety Issues in Generative Models: Memorization and Detection
Abstract: Machine learning systems are built using large troves of training data that may contain private or copyrighted content. In this talk, I'll survey a number of data memorization issues that arise when sensitive data is used. I'll begin by talking about data privacy issues that arise when using generative models. These models are often created using a training objective that explicitly promotes their ability to regenerate their training data. I'll discuss how diffusion models can reproduce their training data, leading to potential legal issues. I'll also discuss methods for detecting large language model content and explore ways in which the ability to reproduce training data complicates our ability to detect LLM-produced text.
Biography: Tom Goldstein is the Volpi-Cupal Professor of Computer Science at the University of Maryland, and director of the Maryland Center for Machine Learning. His research lies at the intersection of machine learning and optimization, and targets applications in computer vision and signal processing. Professor Goldstein has been the recipient of several awards, including SIAM’s DiPrima Prize, a DARPA Young Faculty Award, a JP Morgan Faculty award, an Amazon Research Award, and a Sloan Fellowship.
Host: Mahdi Soltanolkotbi
More Information: ECE AIF4S Seminar Series Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) -
Audiences: Everyone Is Invited
Contact: Ana Hernandez
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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://www.youtube.com/watch?v=_7v5ICY0L_cLocation: Information Science Institute (ISI) - Virtual Only
WebCast Link: https://www.youtube.com/watch?v=_7v5ICY0L_c
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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Alfred E.Mann Department of Biomedical Engineering - Seminar series
Fri, Nov 22, 2024 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Charles Murry, Professor of Stem Cell Biology and Regenerative Medicine, KSOM, USC
Talk Title: Regenerating the Heart: Peeling an Onion
Abstract: The concept of human heart regeneration has progressed from a quixotic aspiration to a realistic possibility. Fundamental discoveries in stem cell biology, cell cycle control, and cellular reprogramming have opened new therapeutic avenues into the world’s number one cause of death. In this lecture, I will focus on pluripotent stem cell-based approaches to heart regeneration, touching on key advances in cell sourcing, scaled manufacturing, delivery, efficacy, mechanism of action, engraftment arrhythmias, and immune rejection.
Biography: Dr. Charles (Chuck) Murry received his bachelor’s degree in chemistry from the University of North Dakota, followed by MD-PhD training at Duke University, where he studied myocardial ischemia-reperfusion injury (heart attacks). He did residency training in Anatomic Pathology at the University of Washington, followed by fellowship training in vascular biology and diagnostic cardiovascular pathology. At the UW, Murry was the founding director of the Center for Cardiovascular Biology, and he cofounded and for many years directed the Institute for Stem Cell and Regenerative Medicine. Murry recently was recruited to the University of Southern California Keck School of Medicine, where he chairs the department of Stem Cell Biology and Regenerative Medicine and directs the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research.
Dr. Murry’s research focuses on stem cell biology, with an emphasis on understanding differentiation of the human cardiovascular system and using these cells to study diseases and to regenerate damaged tissues. His group is a world leader in heart regeneration and is working toward a clinical trial using cardiomyocyte therapy. He has served on many local, national and international committees, spoken widely about stem cells and cardiovascular medicine, and he has received numerous awards for teaching and scientific achievement. Dr. Murry is a past member of the International Society for Stem Cell Research Board of Directors and currently serves on its Manufacturing, Clinical Translation, and Industry Committee.
In addition to his academic work, Murry has worked to promote commercialization of novel cardiovascular therapies. He cofounded BEAT Biotherapeutics, Sana Biotechnology, and most recently a Los Angeles-based startup called StemCardia.
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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ISSS - Dr. Farhana Sheikh, Friday, Nov. 22nd at 2pm in EEB 132
Fri, Nov 22, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Farhana Sheikh, Principal Engineer, Intel
Talk Title: FPGA-Chiplet Architectures and Circuits for 2.5D/3D 6G Intelligent Radios
Series: ISSS
Abstract: The number of connected devices is expected to reach 500 billion by 2030, which is 59-times larger than the expected world population. Objects will become the dominant users of next-generation communications and sensing at untethered, wireline-like broadband performance, bandwidths, and throughputs. This sub-terahertz 6G communication and sensing will integrate security and intelligence. It will enable a 10x to 100x increase in peak data rates. FPGAs are well positioned to enable intelligent radios for 6G when coupled with high-performance chiplets incorporating RF circuits, data converters, and digital baseband circuits incorporating machine learning and security. This talk presents use of 2.5D and 3D heterogeneous integration of FPGAs with chiplets, leveraging Intel's EMIB/Foveros technologies with focus on one emerging application driver: FPGA-based 6G sub-THz intelligent wireless systems. Nano-, micro-, and macro-3D heterogeneous integration is summarized, and previous research in 2.5D chiplet integration with FPGAs is leveraged to forge a path towards new 3D-FPGA based 6G platforms. Challenges in antenna, packaging, power delivery, system architecture design, thermals, and integrated design methodologies/tools are briefly outlined. Opportunities to standardize die-to-die interfaces for modular integration of internal and external circuit IPs are also discussed.
Biography: Farhana Sheikh is a Principal Engineer and Research Manager at Altera (Intel), where she leads technology pathfinding and the Advanced Chiplet Technologies Team. With over 15 years of experience in ASIC and DSP/communications research, she specializes in 2D/3D chiplet and FPGA integration for wireless and sensing applications. She initiated the AIB-3D open-source specification, published over 50 papers, and filed 22 patents. She has received multiple IEEE ISSCC Outstanding Paper Awards (2020, 2019, 2012) and serves as IEEE SSCS Distinguished Lecturer (2023-2024). Dr. Sheikh earned her M.Sc. and Ph.D. from UC Berkeley in 1996 and 2008 respectively, and actively promotes women in circuits through IEEE SSCS.
Host: MHI - ISSS, Hashemi, Chen and Sideris
More Info: https://usc.zoom.us/j/94125605508
More Information: MHI_Seminar_Flyer_Farhana_Sheikh_Nov22_2024.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
Event Link: https://usc.zoom.us/j/94125605508
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PhD Thesis Defense - Pengmiao Zhang
Fri, Nov 22, 2024 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Defense: Pengmiao Zhang
Committee: Prof. Murali Annavaram, Prof. Rajgopal Kannan, Prof. Viktor K. Prasanna (Chair), Prof. Cauligi Raghavendra, Prof. Vatsal Sharan
Title:Machine Learning for Memory Access Prediction and Data Prefetching
Abstract:
Modern applications often experience performance bottlenecks due to memory system limitations. Data prefetching can hide memory access latency by predicting and loading data before it is needed. Machine Learning (ML) algorithms present a promising opportunity to enhance prefetching strategies. However, developing a high-performance ML-based prefetcher presents the following challenges: 1. ML modeling for memory access prediction, including extracting features from historical patterns, identifying future access targets, and designing models to capture their correlations. 2. Domain specific irregular memory access patterns due to multi-core execution and processing phases. 3. Balancing ML model complexity with hardware constraints, ensuring low-latency predictions while maintaining high performance. 4. Coordinated management of multiple prefetchers for ensemble prefetching. In this dissertation, we develop highly optimized ML models for data prefetching. First, to efficiently predict memory accesses for prefetching, we propose TransFetch, a novel attention-based approach that models prefetching as a multi-label classification problem. Second, we introduce a Domain Specific Machine Learning approach for prefetching, utilizing the context of architecture and computation to build high-performance ML-based prefetchers. Using this approach, we develop MPGraph and GraFetch to accelerate the execution of graph applications. Third, towards practical hardware deployment of ML-based prefetchers, we propose a novel tabularization approach that uses table hierarchies to approximate neural networks. We introduce DART, a table-based neural network prefetcher, and Net2Tab, a flexible tabularization framework. Lastly, we present ReSemble, an adaptive framework that uses reinforcement learning to optimize the coordination of multiple prefetchers. Our ML-based prefetchers show significant IPC improvements, demonstrating their performance advantages.
Bio: Pengmiao Zhang is a sixth-year PhD candidate in Computer Engineering, advised by Professor Viktor K. Prasanna. He received his BS degree in Electrical Engineering from Northeastern University (China) and MEng degree in Electrical Engineering from Harbin Institute of Technology. His research interests include machine learning for computer systems, memory system optimizations, and efficient machine learning.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Julia Mittenberg-Beirao
Event Link: https://usc.zoom.us/j/9379439223
