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DTSTART;TZID=America/Los_Angeles:20251104T140000
DTEND;TZID=America/Los_Angeles:20251104T150000
DTSTAMP:20261027T171446Z
CREATED:20251014T210226Z
LAST-MODIFIED:20261027T171446Z
UID:16540-1762264800-1762268400@www.cecs.uci.edu
SUMMARY:Autonomy on a Budget: Enabling Intelligent Monitoring Through Low-Cost Embedded Systems
DESCRIPTION:Title: Autonomy on a Budget: Enabling Intelligent Monitoring Through Low-Cost Embedded Systems \nSpeaker:  Dr. Prabha Sundaravadivel \nDate and Time: Tuesday\, November 4\, 2:00pm \nLocation: EH 2430 \nAbstract: \nThe next generation of environmental monitoring frameworks demands intelligent\, autonomous systems that are affordable\, scalable\, and resilient. However\, high-performance autonomy has traditionally relied on expensive sensors and computational hardware\, limiting deployment in resource-constrained or remote environments. This talk presents recent advances in low-cost embedded autonomy\, where edge AI\, sensor fusion\, and adaptive control enable real-time decision-making within compact\, power-efficient platforms. Drawing on case studies from underwater robots\, UAV-based agricultural monitoring\, and IoT-enabled field systems\, the discussion will highlight how autonomy can be achieved through cost-aware design\, leveraging open-source tools\, lightweight deep learning models\, and modular architectures. The presentation will also explore challenges in integrating computer vision\, localization\, and control on embedded hardware\, and propose pathways toward scalable\, intelligent monitoring frameworks for environmental and industrial applications. \nBiography: \nDr. Prabha Sundaravadivel received her Ph.D. in Computer Science and Engineering from the University of North Texas (UNT)\, Denton\, in 2018. She earned her B.Tech in Electronics and Communication Engineering from SRM University\, Chennai\, in 2011\, and her M.Tech in VLSI Design from VIT University\, India\, in 2015. She is currently working as an Associate Professor in the Department of Electrical and Computer Engineering at the University of Texas at Tyler\, Tyler\, Texas\, USA. She leads a multidisciplinary research group as the Director of the Center for Robotics and Intelligent Systems (CeRIS)\, mentoring graduate\, undergraduate\, and high school students. Her team has received multiple accolades\, including Best Paper\, Poster and Pitch awards\, at both regional and international conferences sponsored by IEEE and ACM. \nHer research has led to successful funded projects totaling over $1.7 Million from organizations like NSF\, NASA\, Oracle\, USDA\, and the Venturewell Foundation. Her research is in the emerging areas of the Internet of Things (IoT)\, on-device learning\, bio-inspired robotics\, Agricultural Robotics and Applied ML. Dr. Sundaravadivel has been recognized as a “Faculty Scholar” at the 2019 Grace Hopper Celebration for Women in Computing and 2022 ACM Richard Tapia Conference and was named as “Innovation Fellow” by Venturewell Foundation in 2023. In 2022\, she was recognized as “Outstanding Early Career Researcher” in the IEEE Bio-Inspired Technical Community. \nHosted By: Prof. Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/autonomy-on-a-budget-enabling-intelligent-monitoring-through-low-cost-embedded-systems/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2025/10/Prabha_Sundaravadivel_11_4_25-e1793121283651.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260213T103000
DTEND;TZID=America/Los_Angeles:20260213T113000
DTSTAMP:20261027T171407Z
CREATED:20260115T203609Z
LAST-MODIFIED:20261027T171407Z
UID:16669-1770978600-1770982200@www.cecs.uci.edu
SUMMARY:GOAL: An Industrially Validated Global Optimization Framework for Advanced Macro Placement in Semiconductor Design
DESCRIPTION:Title: GOAL: An Industrially Validated Global Optimization Framework for Advanced Macro Placement in Semiconductor Design \nSpeaker: Jooyoung Lee \nDate and Time: Friday\, February 13\, 10:30am \nLocation: EH 2430 \nAbstract: \nMost current AI solutions in industry rely on LLM architectures\, which are fundamentally unsuited for high-dimensional combinatorial optimization. In contrast\, we target problem classes that LLMs and conventional reinforcement learning (RL) cannot solve. System-level macro placement in advanced semiconductor design represents an extremely large-scale combinatorial optimization space\, with a search complexity exceeding astronomical scales. Prior RL-based approaches from major EDA vendors and research groups have not translated into production-level performance\, largely due to sparse and ambiguous reward structures in real-world design constraints. \nOur CSA global-optimization framework is engineered specifically for such non-convex\, high-dimensional search problems. Its performance has been validated through back-to-back victories in The Critical Assessment of Protein Structure Prediction (CASP) and through “Badugi\,” the first Korean AI system to defeat a professional Go player?both demonstrating its capability to navigate vast\, rugged solution landscapes. \nWe have collaborated with a leading global semiconductor manufacturer to evaluate our technology on a top-tier\, cutting-edge semiconductor device. The CSA-based macro-placement engine produced layouts superior to those of veteran human designers and showed strong potential to reduce overall physical-design cycle time by more than half. \nUnlike costly RL-driven\, general-purpose optimization tools\, our solution is built on a dedicated combinatorial-optimization engine that directly models the search space rather than relying on proxy rewards. We are advancing AI that can reliably solve the hardest optimization problems in semiconductor design and beyond. \nBiography: \nProf. Jooyoung Lee\, Good Intelligence CEO\, received his PhD in Physics in 1990 from Brown University under the supervision of Prof. JM Kosterlitz (2016 Nobel laureate in Physics). Since 1994\, his research focused on solving the protein folding problem\, and he led a KIAS (Korea Institute for Advanced Study) team in the CASP (protein structure modeling) competition for CASP5-CASP12 (2002-2016). Motivated by the superhuman performance of AlphaGo\, with an ultimate eye towards improvements in protein folding prediction\, Prof. Lee’s research interest temporarily turned to deep learning. He started with its application to the game of Go\, and implemented a unique deep learning method to compete in world Go AI competitions (2nd place in the 2019 Fuzhou Go AI competition; 3rd place in the 11th Computer Go UEC Cup). \nProf. Lee\, a professor in the school of computational sciences at KIAS\, has published more than 120 peer-reviewed papers in various SCI journals. Many of these papers are well cited [(over 4700 citations from SCI journals and over 3900 citations to his first/corresponding-authored papers (as of Sept. 2018)]. His publication H-Index is 34. \nHosted By: Prof. Ian Harris \nMore Information
URL:https://www.cecs.uci.edu/event/goal-an-industrially-validated-global-optimization-framework-for-advanced-macro-placement-in-semiconductor-design/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2026/01/JooyoungLee_Photo-e1793121242113.jpg
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DTSTART;TZID=America/Los_Angeles:20260723T100000
DTEND;TZID=America/Los_Angeles:20260723T110000
DTSTAMP:20261027T171214Z
CREATED:20260711T000304Z
LAST-MODIFIED:20261027T171214Z
UID:16839-1784800800-1784804400@www.cecs.uci.edu
SUMMARY:The Brave New (Quantum) World
DESCRIPTION:Title: The Brave New (Quantum) World \nSpeaker: Dr. Anupam Chattopadhyay \nDate and Time: Thursday\, July 23\, 10:00am \nLocation: ISEB 1310 \nAbstract: \nMajor advances across all the design stack of Quantum computing – algorithm\, software\, and hardware – has brought us to a realm where\, it is impossible to ignore the effect of Quantum computing in the world around us. We will discuss two aspects of Quantum computing in this talk. First\, efficient circuit design and automation challenges – and how we can borrow some knowledge from classical computing for that. We will conclude this part with case studies on experimental Quantum computers. Second\, the most important practical threat from a large-scale Quantum computer is on public-key cryptography. This is countered by developing and standardizing Post-Quantum Cryptography (PQC) primitives. We will talk about various PQC candidates and the perils of migration to a Quantum-safe environment. \nBiography: \nAnupam Chattopadhyay is currently an Associate Professor (with tenure) in College of Computing & Data Science\, Nanyang Technological University (NTU). He received his B.E. degree from Jadavpur University\, India\, MSc. from ALaRI\, Switzerland and PhD from RWTH Aachen in 2000\, 2002 and 2008\, respectively. His research in the broad domains of Electronic Design Automation\, Cyber Security\, Internet-of-Things (IoT) and Application-Specific Instruction-Set Processors (ASIPs) has been published in 200+ IEEE/ACM conferences and journals and has led to multiple spinoffs and technology transfers. Anupam has served in the TPCs of major EDA/VLSI conferences and edited a Springer Major Reference Work on Computer Architectures. Anupam’s research has garnered several best paper awards\, most recently in VLSI-SoC 2024 for Quantum adders\, and in CHES 2025 for side-channel attack on PQC standard Kyber. He was awarded fellowship of Japanese Society for Promotion of Science (JSPS)\, fellowship of Intercontinental Academia and was awarded NTU Innovation and Entrepreneurship award in 2025. \nHosted By: Prof. Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/the-brave-new-quantum-world/
LOCATION:ISEB 1310
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2026/07/anupam_headshot-e1784669594620.png
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DTSTART;TZID=America/Los_Angeles:20260729T110000
DTEND;TZID=America/Los_Angeles:20260729T120000
DTSTAMP:20260727T155342Z
CREATED:20260721T213151Z
LAST-MODIFIED:20260727T155342Z
UID:16859-1785322800-1785326400@www.cecs.uci.edu
SUMMARY:Software-Defined Accelerator-Centric Systems - A Journey to AI and Big Data Acceleration
DESCRIPTION:Title: Software-Defined Accelerator-Centric Systems – A Journey to AI and Big Data Acceleration \nSpeaker: Dr. Zhenman Fang \nDate and Time: Wednesday\, July 29\, 11:00am \nLocation: ISEB 4020 \nAbstract: \nWith the end of CPU scaling due to dark silicon limitations\, customizable hardware accelerators have gained increasing attention in modern datacenters and edge devices\, due to their low power\, high performance\, and high energy-efficiency. Unfortunately\, not everyone can design hardware accelerators and there remains a substantial gap for the large community of software developers to effectively leverage the benefits of domain-specific hardware acceleration. \nIn this talk\, I will share my research on software-defined accelerator-centric systems. First\, I will give an overview of the unique advantages of hardware accelerators using the roofline model and illustrate common hardware customization techniques that can be defined by software. Next\, I will share my research journey to AI and big data acceleration\, and demonstrate two successful case studies of accelerator-centric systems: 1) HeatViT\, a hardware-efficient image-adaptive token pruning framework for efficient yet accurate vision transformer (ViT) acceleration on edge FPGAs\, with a key focus on algorithm/hardware codesign; and 2) SQL2FPGA\, a compiler that automatically compiles big data queries onto datacenter FPGA accelerators\, with a key focus on improving software programmability. Finally\, I will discuss future research directions of software-defined accelerator-centric systems. \nBiography: \nDr. Zhenman Fang is an Associate Professor in Department of Electrical and Computer Engineering\, University of Minnesota\, Twin Cities. He is on leave from School of Engineering Science\, Simon Fraser University\, Canada\, where he joined since Apr 2019. Zhenman founded and directs the HiAccel lab. Zhenman’s recent research focuses on customizable computing with software-defined hardware acceleration\, which aims to sustain the ever-increasing performance and energy-efficiency demands of important application domains in post-Moore’s law era. It spans the entire computing stack\, including emerging application characterization and acceleration (including machine learning\, big data analytics\, high-performance computing\, and precision medicine)\, novel accelerator-rich and near-data computing architecture designs\, and corresponding programming\, runtime\, and tool support. \nZhenman has published over 80 papers in top-tier conferences and journals and holds two US patents\, including the ICCAD 10 Year Retrospective Most Influential Paper Award in 2025\, three best paper awards (FPL 2024 Stamatis Vassiliadis Best Paper\, TCAD 2019 Donald O. Pederson Best Paper\, and MEMSYS 2017 Best Paper)\, four best paper nominees (ICCAD 2025\, FCCM 2025\, HPCA 2017 and ISPASS 2018)\, and an invited paper from Proceedings of the IEEE 2019. His research has also been recognized with the inaugural SFU Research Excellence Award – Horizon Award (2025)\, a NSERC (Natural Sciences and Engineering Research Council of Canada) Alliance Award (2020)\, a CFI JELF (Canada Foundation for Innovation John R. Evans Leaders Fund) Award (2019)\, a Xilinx University Program Award (2019)\, a Team Award from Xilinx Software and IP Group (2018)\, and a Postdoc Fellowship from UCLA Institute for Digital Research and Education (2016-2017). Zhenman has also actively served in the organizing and program committee of top-tier conferences in the areas of FPGA and reconfigurable computing\, design automation\, and computer architecture. Recently\, he has served as Program Vice Chair of FCCM 2026\, Journal Track Chair of FPL 2026\, General Chair of ASAP 2025\, Program Chair of RAW 2024 and RAW 2025. More details can be found in his website: https://zhenman.github.io/. \nHosted By: Prof. Sitao Huang \nMore Information
URL:https://www.cecs.uci.edu/event/software-defined-accelerator-centric-systems-a-journey-to-ai-and-big-data-acceleration/
LOCATION:ISEB 4020\, Interdisciplinary Science and Engineering Building\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2026/07/Zhenman-Fang.jpg
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DTSTART;TZID=America/Los_Angeles:20260730T103000
DTEND;TZID=America/Los_Angeles:20260730T113000
DTSTAMP:20260915T171945Z
CREATED:20260711T001319Z
LAST-MODIFIED:20260915T171945Z
UID:16849-1785407400-1785411000@www.cecs.uci.edu
SUMMARY:From Domain-Specific Accelerators to Spatial Architecture Exploration
DESCRIPTION:Title: From Domain-Specific Accelerators to Spatial Architecture Exploration \nSpeaker: Dr. Jongeun Lee \nDate and Time: Thursday\, July 30\, 10:30am \nLocation: ISEB 1310 \nAbstract: \nEmerging scientific and machine learning workloads increasingly benefit from domain-specific hardware accelerators\, yet designing efficient architectures for these applications requires both effective implementations and scalable methods for architectural exploration. In this talk\, I will present our recent research on accelerator design and architecture exploration for spatial computing systems. \nI will first introduce AccelOrb\, an FPGA accelerator for Orb v2\, a graph neural network-based machine learning force field (MLFF) used in molecular dynamics simulations. By analyzing the application’s computational bottlenecks and memory requirements\, we develop a memoryaware streaming architecture that substantially improves performance while operating within the resource constraints of a modern FPGA. \nBuilding on the lessons learned from accelerator implementation\, I will then discuss FlowSpec\, a flexible framework for modeling and simulating coarse-grained spatial architectures. Rather than targeting a single accelerator design\, FlowSpec provides a scalable interface between application mapping and architectural simulation\, enabling rapid exploration of diverse compute organizations and communication networks. \nTogether\, these efforts highlight a research direction that bridges application-driven accelerator design with the systematic exploration of future spatial architectures. \nBiography: \nJongeun Lee received his B.S. and M.S. degrees in Electrical Engineering and his Ph.D. in Electrical Engineering and Computer Science from Seoul National University\, Korea. In 2009\, he joined Ulsan National Institute of Science and Technology (UNIST)\, Ulsan\, Korea\, where he is currently a Professor at the Department of Electrical Engineering. Before joining UNIST\, he was a postdoctoral research associate at Arizona State University in Tempe\, Arizona\, USA\, and also worked at Samsung Electronics\, Korea. \nProfessor Lee has authored more than 100 peer-reviewed journal and conference publications. He currently serves as Editor-in-Chief of IEEE Embedded Systems Letters and has served on the technical program and organizing committees of numerous conferences and workshops in computer-aided design and reconfigurable computing. His research interests include hardware/software co-design\, reconfigurable architectures\, deep learning\, and computer-aided design for emerging technologies. \nHosted By: Prof. Fadi Kurdahi \nMore Information
URL:https://www.cecs.uci.edu/event/from-domain-specific-accelerators-to-spatial-architecture-exploration/
LOCATION:ISEB 1310
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2026/07/2023-jlee4-l.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261109T140000
DTEND;TZID=America/Los_Angeles:20261109T150000
DTSTAMP:20261103T223607Z
CREATED:20260914T234517Z
LAST-MODIFIED:20261103T223607Z
UID:16913-1794232800-1794236400@www.cecs.uci.edu
SUMMARY:Perception/Control Co-Design for Autonomous Vehicles
DESCRIPTION:Title: Perception/Control Co-Design for Autonomous Vehicles \nSpeaker: Dr. Marilyn Wolf\, University of Nebraska – Lincoln \nDate and Time: Monday\, November 9\, 2:00 pm \nLocation: EH 2430 \nAbstract: \nPerception is a critical computational task in autonomous vehicles. Autonomous vehicles place stringent and somewhat conflicting demands on perception systems: high accuracy\, low latency\, and performance on limited computational resources. The conflict between these requirements is particularly acute in the case of unmanned aerial vehicles (UAVs). This talk will describe two related efforts on efficiency and accuracy in perception for autonomous vehicles. Work with Krishna Muuva and Justin Bradley of UNL looks at UAV-UAV tracking. We show that tracking performance saturates above a given level of perceptual accuracy. Work with Deep Samal\, Thomas Walton\, and Dung Tran of UNL builds a\nMarkovian model for perception errors and shows their effect on tracking. \nBiography: \nMarilyn Wolf is Elmer E. Koch Professor of Engineering at the University of Nebraska – Lincoln where she served as Founding Director of the School of Computing. She received her BS\, MS\, and PhD in electrical engineering from Stanford University in 1980\, 1981\, and 1984\, respectively. She was with AT&T Bell Laboratories from 1984 to 1989. She was on the faculty of Princeton University from 1989 to 2007 and was Farmer Distinguished Chair at Georgia Tech from 2007 to 2019. Her research interests include cyber-physical systems\, embedded computing\, embedded video and computer vision\, and VLSI systems. She has received the IEEE Kirchmayer Graduate Education Award\, the IEEE Computer Society Goode Memorial Award\, the ASEE Terman Award\, the IEEE Circuits and Systems Society Education Award\, and the ACM SIGDA Distinguished Service Award. She is a Fellow of the IEEE and ACM and an IEEE Computer Society Golden Core member. \nHosted By: Prof. Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/perception-control-co-design-for-autonomous-vehicles/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2026/09/mwolf-e1793120941480.jpeg
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