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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230126T140000
DTEND;TZID=America/Los_Angeles:20230126T150000
DTSTAMP:20231011T032353Z
CREATED:20231011T032353Z
LAST-MODIFIED:20231011T032353Z
UID:14150-1674741600-1674745200@www.cecs.uci.edu
SUMMARY:"Complex Systems Engineering Theory is a Scientific Theory"
DESCRIPTION:Speaker: Prof. Eric Feron\, King Abdullah University of Science and Technology (KAUST)\nDate and Time: Thursday\, January 26th\, 2:00pm \nLocation: EH 2430 \nAbstract: \nComplex systems engineering and associated challenges become increasingly important for the well-being and safety of our society of humans. Motivated by this formidable push towards ever more complex systems of all sizes\, spectacular failures\, and decades of questioning in a variety of contexts and endeavors\, this talk presents a theory of complex systems engineering that is\, as a scientific theory in which an engineered system can be seen as a validated scientific hypothesis arising from a convergent mix of mathematical and validated experimental constructs. In its simplest form\, it is a manufactured\, validated scientific hypothesis arising from a mathematical theorem similar to those found in theoretical physics. The talk begins with the scientific hypothesis underlying this theory\, and arguments in favor of it are displayed\, as well as some of its practical consequences in terms of complex system design and future research. Then\, a limited set of experiments is presented to try and invalidate the theory by confronting it to existing educational programs in systems engineering in the United States of America. Concurrent with these invalidation efforts\, this talk also argues that there is a serious and growing lack of education in mathematics and/or engineering ecience in most\, if not all\, systems engineering programs. Such weaknesses challenge the industrial value of all corporate or government institutions in the pursuit of complex engineered systems excellence. \nBio: \nEric Feron is a Professor of Biological\, Electrical (main)\, Computer\, and Mechanical Engineering at King Abdullah University of Science and Technology\, where he co-directs the Robotics\, Intelligent Systems\, and Control laboratory (RISClab). Prior to that or concurrently\, Eric Feron has had appointments with Ecole Nationale de l’Aviation Civile\, France; the Georgia Institute of Technology\, USA; the Institut Supérieur de l’Aéronautique et de l’Espace\, Sup’Aéro campus\, France; the Massachusetts Institute of Technology\, USA; and the Office National d’Etudes et Recherches Aérospatiales\, France. Eric Feron trained as a naval officer of the watch on nuclear submarines (France)\, and as a private pilot (USA). Feron’s research focuses on leveraging his knowledge and contributions to control theory\, computer science\, and optimization to address problems having to do with autonomy\, robotic agility\, transportation\, and other complex systems-level challenges. Feron’s work includes analytical and experimental activities and it has supported the training of dozens of doctoral\, master and undergraduate students. Eric Feron relaxes by operating sailboats of all sizes with his wife Christine-Marie\, including Casa del Mar\, their off-shore bluewater cruiser. \nHosted By: Fadi Kurdahi \n 
URL:https://www.cecs.uci.edu/event/complex-systems-engineering-theory-is-a-scientific-theory/
LOCATION:EH 2429\, Engineering Hall University of California\, Irve\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230306T140000
DTEND;TZID=America/Los_Angeles:20230306T150000
DTSTAMP:20231011T032353Z
CREATED:20231011T032353Z
LAST-MODIFIED:20231011T032353Z
UID:14151-1678111200-1678114800@www.cecs.uci.edu
SUMMARY:“Perception and Computational Efficiency for Autonomous Vehicles”
DESCRIPTION:Speaker: Prof. Marilyn Wolf\nDate and Time: Monday\, March 6th\, 2:00pm \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) but is also true of ground vehicles.  This talk will describe two related efforts to improve and manage efficiency 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 and Saibal Mukhopodhyay of Georgia Tech compares the results of multiple evaluators to improve the accuracy of LIDAR tracking. \nBiography: \nMarilyn Wolf is Elmer E. Koch Professor of Engineering and Director of the School of Computing at the University of Nebraska – Lincoln.  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\, and the IEEE Circuits and Systems Society Education Award. She is a Fellow of the IEEE and ACM and an IEEE Computer Society Golden Core member. \nHosted By: Prof. Mohammad Al Faruque \n 
URL:https://www.cecs.uci.edu/event/perception-and-computational-efficiency-for-autonomous-vehicles/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230426T150000
DTEND;TZID=America/Los_Angeles:20230426T160000
DTSTAMP:20231011T032408Z
CREATED:20231011T032408Z
LAST-MODIFIED:20231011T032408Z
UID:14154-1682521200-1682524800@www.cecs.uci.edu
SUMMARY:"Intuitive\, Interoperable\, Intelligent – A Look into Current Automation Engineering Research"
DESCRIPTION:Speaker: Dr. Gustavo Quiros\nDate and Time: Wednesday\, April 26th\, 3:00pm \nLocation: EH 2430 \nAbstract:   \nIntuitive\, Interoperable\, Intelligent – The future of automation engineering will embrace these basic characteristics to continuously reduce the effort and expertise required by engineers to implement industrial automation solutions while increasing the flexibility and the capabilities of engineering tools. This talk will give an overview of several research activities in the area of industrial automation engineering\, showing how they aim to realize these three basic characteristics\, and provides a vision for automation engineering in the near future. \nBiography: \nDr. Gustavo Quiros A. is a Research and Technology Manager at Siemens Technology. He specializes in industrial automation engineering\, programming languages and software engineering. He holds a B.Sc. degree in Computer Engineering from Instituto Tecnologico de Costa Rica\, a M.Sc. degree in Software Systems Engineering and a Dr.rer.nat. degree in Process Control Engineering from RWTH Aachen University. He obtained summa cum laude and the Borchers-Badge of RWTH Aachen University for his doctoral dissertation “Model-based Decentralized Automatic Management of Product Flow Paths in Processing Plants”. He also obtained the NAMUR Award “Process Automation” 2010 from the User Association of Automation Technology in Process Industries.
URL:https://www.cecs.uci.edu/event/intuitive-interoperable-intelligent-a-look-into-current-automation-engineering-research/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230714T100000
DTEND;TZID=America/Los_Angeles:20230714T230000
DTSTAMP:20231011T032435Z
CREATED:20231011T032435Z
LAST-MODIFIED:20231011T032435Z
UID:14159-1689328800-1689375600@www.cecs.uci.edu
SUMMARY:"Requirements and Applications of  Cloud-based Services within the Automotive Edge"
DESCRIPTION:Speaker: Prof. Dr. Achim Rettberg\nDate and Time: Friday\, July 14th\, 10:00am \nLocation: EH 2430 \nAbstract: \nThe architectures in today’s vehicles are usually still based on decentralized or domain-centric architecture concepts that place a strong focus on individual control units. New applications and services\, which may only be used or required temporarily\, are very difficult to implement with these vehicle architectures. This applies in particular when external data sources and services are also involved\, e.g. a bidirectional exchange of information between vehicles and their infrastructure. The dynamic adaptation to new circumstances\, such as the availability of new data sources or the use of specific vehicle functions by third-party applications\, is hardly or not at all feasible here. These concepts are being investigated in the GAIA-X4AGEDA joint research project\, which aims to develop a software architecture in the edge device vehicle that makes use of the concepts of the cloud initiative “GAIA-X” and “by-design” data-driven applications and the dynamic adaptation of a vehicle with its functions over the entire life cycle of the vehicle. The modeling of this approach with digital twins plays a central role here\, on the one hand to be able to show early statements about characteristics such as real time etc. and on the other hand to make predictions about the state of the system \nBiography: \nProf. Dr. Achim Rettberg works since December 2017 as Professor for Human Machine Interface Technologies at University of Applied Science Hamm/Lippstadt. Previously\, he worked since end of 2014 for HELLA as Methodology expert and for inventing a PhD program. Furthermore\, he is still extraordinary Professor at Carl von Ossietzky University Oldenburg. He received his M.S. (Dipl.-Inform.) in computer science and economics in 1997 and his Ph. D. (Dr. rer. nat.) degree in 2006 from the University of Paderborn\, Germany\, where he studied computer science and economics. He worked from 2007 until 2008 as Post-Doc at C-LAB and managed EU-Projects. In 2008 he became professor of complex integrated systems/embedded systems at the Computer Science department at Carl von Ossietzky University Oldenburg. Prof. Rettberg is founder and General Chair of the International Embedded Systems Symposium (IESS). He is chair of the IFIP working group 10.2 for Embedded Systems still April 2012 and chair of IFIP TC 10  Computer Systems Technology since October 2019. Since September 2022 he is member of the IFIP board. His general research interests are real-time systems and HW/SW architectures. His current focus lies on design methods\, optimization for embedded systems and architectures\, and for human machine interface technologies for embedded devices. \nHosted By: Nikil Dutt
URL:https://www.cecs.uci.edu/event/requirements-and-applications-of-cloud-based-services-within-the-automotive-edge/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230714T110000
DTEND;TZID=America/Los_Angeles:20230714T120000
DTSTAMP:20231011T043621Z
CREATED:20231011T032435Z
LAST-MODIFIED:20231011T043621Z
UID:14160-1689332400-1689336000@www.cecs.uci.edu
SUMMARY:"An Integrated Environment for Modeling and Deploying Digital Twins"
DESCRIPTION:Speaker: Charles Steinmetz\nDate and Time: Friday\, July 14th\, 11:00am \nLocation: EH 2430 \nAbstract: \nThe Digital Twin (DT) has been the focus of researchers from academia and industry in the last few years. It is one of the key enablers of the current and next industrial revolutions\, such as Industry 4.0\, Industry 5.0\, and Metaverse. The idea of digitalizing real-world “things” can bring many benefits since it can allow monitoring\, simulation\, predictions\, optimizations and so on. However\, representing real-world systems can be complex\, since assets might have several ways of being represented and several stakeholders with different experiences might be involved. Also\, keeping models updated with the current state of the system can also be challenging. In this context\, this thesis proposes an environment that integrates all these perspectives in a common language that different stakeholders can use\, covering different system levels from the device level up to process and workflow levels. To support the creating of semantic DT models\, a methodology has been proposed\, starting from the identification of the real-world assets\, creating the semantic models and linking external ones\, and ending with the deployment of the system. Furthermore\, a 4-layers architecture is presented to help designers to identify the responsibilities of each part of the system. Use cases related with a simulated industrial plant and in the automotive area have been developed to demonstrate the proposed approach.\nBiography: \nCharles Steinmetz received the B.S. degree in Information Systems from the Franciscan University (UFN)\, Santa Maria\, Brazil\, in 2015\, and the M.Sc. degree in Computer Science from the Federal University of Rio Grande do Sul (UFRGS)\, Porto Alegre\, Brazil\, in 2018. He is currently working toward the Ph.D. degree in Computer Science with the University of Oldenburg\, Oldenburg\, Germany. He also works as Research Assistant at the University of Applied Science Hamm-Lippstadt\, Lippstadt\, Germany. His research interests are Internet of Things\, Digital Twins\, semantic models and industry 4.0.\nHosted By: Nikil Dutt
URL:https://www.cecs.uci.edu/event/an-integrated-environment-for-modeling-and-deploying-digital-twins/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2023/07/charles-image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230807T110000
DTEND;TZID=America/Los_Angeles:20230807T120000
DTSTAMP:20231011T033045Z
CREATED:20231011T032546Z
LAST-MODIFIED:20231011T033045Z
UID:14162-1691406000-1691409600@www.cecs.uci.edu
SUMMARY:"Capstone: A Capability-based Foundation for Trustless Secure Memory Access"
DESCRIPTION:Speaker: Jason Zhijingcheng Yu\nDate and Time: Monday\, August 7th\, 11:00 am \nLocation: EH 2430 \nAbstract: \nCapability-based memory isolation is a promising new architectural primitive. Software can access lowlevel memory only via capability handles rather than raw pointers\, which provides a natural interface to enforce security restrictions. Existing architectural capability designs such as CHERI provide spatial safety but fail to extend to other memory models that security-sensitive software designs may desire. In this paper\, we propose Capstone\, a more expressive architectural capability design that supports multiple existing memory isolation models in a trustless setup\, i.e.\, without relying on trusted software components. We show how Capstone is well-suited for environments where privilege boundaries are fluid (dynamically extensible)\, memory sharing/delegation are desired both temporally and spatially\, and where such needs are to be balanced with availability concerns. Capstone can also be implemented efficiently. We present an implementation sketch and through evaluation show that its overhead is below 50% in common use cases. We also prototype a functional emulator for Capstone and use it to demonstrate the runnable implementations of six real-world memory models without trusted software components: three types of enclave-based TEEs\, a thread scheduler\, a memory allocator\, and Rust-style memory safety—all within the interface of Capstone.\nBiography: \nJason Zhijingcheng Yu is a 4th-year PhD student working with Prof Prateek Saxena at the School of Computing\, National University of Singapore (NUS). He works on operating system and architectural security\, with a focus on trusted computing and capability-based security in architectures. His first-authored work has been published at venues including ACM CCS 2021\, USENIX Security 2022\, and USENIX Security 2023. Homepage: https://www.comp.nus.edu.sg/~yuz1996/\nHosted By: Zhou Li
URL:https://www.cecs.uci.edu/event/capstone-a-capability-based-foundation-for-trustless-secure-memory-access/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2023/07/Jason-Yu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230926T140000
DTEND;TZID=America/Los_Angeles:20230926T150000
DTSTAMP:20241014T182326Z
CREATED:20231010T222422Z
LAST-MODIFIED:20241014T182326Z
UID:13934-1695736800-1695740400@www.cecs.uci.edu
SUMMARY:Pareto Exploration Methodology for Future Logic Technology Options in Domain-Specific Processors
DESCRIPTION:Speaker: Dr. Francky Catthoor \nDate and Time: Tuesday\, September 26th\, 2:00 pm \nLocation: EH 2430 \nAbstract:   \nScaling of Si-CMOS based logic processor circuits is hitting limits on application-level performance (throughput and latency)\, dynamic and leakage power\, and even cost characteristics. For that reason\, several researchers have started to study alternatives based on so-called beyond CMOS devices. Many emerging devices have been studied in the last decade\, especially in academia. And some of these looks promising for specific figures of-merit\, like only dynamic power (but not energy)\, only leakage (but not dynamic power) and so on. Hence\, they are almost never simultaneously improving several axes (the desirable figures-of-merit) in the Pareto trade-off space. And as a result\, they rarely improve the true Pareto front in that space. A need exists to better compare potential options in a systematic way\, with emphasis on their system-level impact\, and as much as possible in a future-proof way\, including the link to the processor architecture design and hence to the overall processing platform. In this talk\, a systematic approach will be advocated to characterize these options in a multi-dimensional Pareto exploration space\, and a few interesting directions will be positioned in this space to highlight the potential of this approach. The main architecture context will be domain-specific processor instances. \nBiography: \nFrancky Catthoor received a Ph.D. in EE from the Katholieke Univ. Leuven\, Belgium in 1987. Between 1987 and 2000\, he has headed several research domains in the area of synthesis techniques and architectural methodologies. Since 2000 he is strongly involved in other activities at IMEC including deep submicron technology aspects\, IoT and biomedical platforms\, and smart photovoltaic modules\, all at IMEC Leuven\, Belgium. Currently\, he is an IMEC fellow. He is also a part-time full professor at the EE department of the KULeuven. He has been associate editor for several IEEE and ACM journals and was elected IEEE fellow in 2005. \nHosted By: Prof. Nikil Dutt \nMore Information
URL:https://www.cecs.uci.edu/event/pareto-exploration-methodology-for-future-logic-technology-options-in-domain-specific-processors/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/webp:https://cecs.uci.edu/files/2023/09/Francky_Catthoor_1-e1728930196231.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231012T110000
DTEND;TZID=America/Los_Angeles:20231012T120000
DTSTAMP:20231011T203102Z
CREATED:20231010T174533Z
LAST-MODIFIED:20231011T203102Z
UID:13955-1697108400-1697112000@www.cecs.uci.edu
SUMMARY:Human-Centered Visual Computing: Harnessing Symbiosis Between Computer Architecture\, Imaging\, and Biological Perception
DESCRIPTION:Title: Human-Centered Visual Computing: Harnessing Symbiosis Between Computer Architecture\, Imaging\, and Biological Perception \nSpeaker: Dr. Yuhao Zhu \nDate and Time: Thursday\, October 12th\, 11:00 am \nLocation: EH 2430 \nAbstract:  \nEmerging platforms such as Augmented Reality (AR)\, Virtual Reality (VR)\, and autonomous machines\, while are of a computing nature\, intimately interact with both the environment and humans. They must be built\, from the ground up\, with principled considerations of three main components: imaging\, computer systems\, and human perception. This talk will make a case for this tenet and discuss some of our recent work on this front. I will first talk about in-sensor visual computing\, the idea that co-designing the image sensor with the computer systems will significantly improve the overall system efficiency and\, perhaps more importantly\, unlock new machine capabilities. We will show a number of case studies in AR/VR and autonomous machines. I will then discuss our work on human-systems co-optimizations\, where we 1) exploit human color vision to build energy-efficient AR/VR devices and 2) computationally “cure” color blindness without gene therapy. \nBiography:  \nYuhao Zhu is an Assistant Professor in the Department of Computer Science and a Bridging Fellow faculty in the Department of Brain and Cognitive Sciences at University of Rochester. He graduated from The University of Texas at Austin\, and previously held visiting researcher positions at Arm Research and Harvard University. Yuhao Zhu does software and hardware research for visual computing\, an exciting area where a challenging\nproblem in computing might become significantly easier when one considers how computing interacts with conventionally non-computing domains such as imaging and human perception at the system level. \nHosted By: Prof. Hyoukjun Kwon \nMore Information
URL:https://www.cecs.uci.edu/event/human-centered-visual-computing-harnessing-symbiosis-between-computer-architecture-imaging-and-biological-perception/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2023/10/Yuhao-Zhu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231103T103000
DTEND;TZID=America/Los_Angeles:20231103T113000
DTSTAMP:20231101T164120Z
CREATED:20231031T234255Z
LAST-MODIFIED:20231101T164120Z
UID:15894-1699007400-1699011000@www.cecs.uci.edu
SUMMARY:Sparse Computing and Large Language Model: from AI 1.0 to AI 2.0
DESCRIPTION:Title: Sparse Computing and Large Language Model: from AI 1.0 to AI 2.0 \nSpeaker: Prof. Guohao Dai \nDate and Time: Friday\, November 3rd\, 10:30 am \nLocation: ISEB 4020 \nAbstract: \nGeneral Artificial Intelligence is going through a new development stage from Computation AI\, Perception AI\, to Cognition AI\, with the new trends of big data\, multi-modality\, and multi-task. However\, due to the slowdown of Moore's Law\, there are bottlenecks in hardware computility\, leaving a huge gap between the supply of computility and the demand for the computility in intelligent computing. Because the AI function has the learnable characteristics\, the amount of calculation can be reduced through the sparsification method\, thereby breaking through the hardware computility bottleneck of intelligent computing while ensuring task accuracy. This report will focus on the software and hardware co-design method of sparse computing. This report will introduce the definition and process of sparse computing\, as well as the challenges faced in intelligent computing from algorithm\, compilation\, and architecture perspectives. This report will elaborate on the multi-level design method for sparse computing in AI\, and introduce three typical models in the AI ​​1.0 era (Graph Neural Networks\, Point Cloud Networks\, and Conventional Convolution Neural Networks). Finally\, this report takes the Large Language Models (LLMs) algorithm in the AI ​​2.0 era as an example to illustrate the application of the above design method in large language model inference optimization. Compared with the existing model\, the calculation speed on dense hardware architecture is increased by 2 times. \nBiography: \nGuohao Dai is a tenure-track Associate Professor at Shanghai Jiao Tong University\, he received his B.S. and Ph.D. (with honor) degrees from Tsinghua University\, Beijing\, in 2014 and 2019. Prof. Guohao Dai has published more than 50\nhigh-level international journals and conference papers in the fields of Electronic Design Automation (EDA)\, heterogeneous computing\, and system/architecture design. He has received more than 1000 citations in Google Scholar. The published paper won the ASP-DAC 2019 Best Paper Award\, DATE 2023/DAC 2022/DATE 2018 Best Paper Nomination\, and WAIC 2022 Outstanding Youth Paper Award. He has personally won honors such as the WAIC 2022 Yunfan Award\, the global champion of the NeurIPS21 BIGANN competition\, Beijing’s outstanding doctoral graduates\, Tsinghua University's outstanding doctoral graduates\, and Tsinghua University’s outstanding doctoral thesis. Professor Dai has participated in guiding students to rank third in the world in ACM 2021 SRC and first in the world in MICRO 2020 SRC. Currently\, he serves as PI/Co-PI for several projects with a personal share of over RMB 10 million. \nHosted By: Sitao Huang \nMore Information
URL:https://www.cecs.uci.edu/event/sparse-computing-and-large-language-model-from-ai-1-0-to-ai-2-0/
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/2023/10/Guohao_Dai_smaller_11-3-23.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20231207T143000
DTEND;TZID=America/Los_Angeles:20231207T153000
DTSTAMP:20231101T164355Z
CREATED:20231031T205713Z
LAST-MODIFIED:20231101T164355Z
UID:15888-1701959400-1701963000@www.cecs.uci.edu
SUMMARY:Systematic Security Analysis of Cellular Network Specifications and Implementations
DESCRIPTION:Title: Systematic Security Analysis of Cellular Network Specifications and Implementations \nSpeaker: Dr. Imtiaz Karim \nDate and Time: Thursday\, December 7th\, 2:30 pm \nLocation: EH 2430 \nAbstract: \nCellular networks are the bedrock of modern communication. The recent deployment of the 5G has generated further enthusiasm and opportunities in both academia and industry\, because of its promise of enabling\ninnovative applications\, such as autonomous vehicles\, industrial IoT\, and augmented reality. Therefore\, the security of cellular network protocols is critical. In this talk\, I will elaborate on the critical challenges of ensuring cellular\nnetwork security and move on to the research we are doing to enhance the resilience of the networks. I will detail our developed techniques for both white-box and black-box analysis of cellular implementations. On the whole\, using\nthese approaches we have found 24 critical issues in both commercial and open-source implementations. Lastly\, I will talk about our recent work SPEC5G\, the first-ever public 5G dataset for NLP research\, and discuss how using\nSPEC5G and state-of-the-art Large Language Models (LLMs) we are detecting inconsistencies in the cellular protocol specifications. \nBiography: \nImtiaz Karim is a postdoctoral research associate in the Department of Computer Science at Purdue University working with Prof. Elisa Bertino. He received his Ph.D. degree from the same department in Spring\n2023. His research interests lie in analyzing the security and privacy of wireless communication protocols (e.g.\, 4G\, 5G\, Bluetooth\, VoWiFi\, vehicular\, WiFi\, and IoT)\, their implementations\, networked systems\, and mobile\ncomputing. His research has led to several changes in the design of 4G and 5G cellular standards\, and commercial implementations. He has been inducted into the GSMA Mobile Security Research Hall of Fame\nthree times and has received numerous bug bounties\, CVDs\, and CVEs. He received the best paper award at ACSAC 2019\, and the best paper award nomination at ICDCS 2021. For outstanding security research\, he has\nreceived the Maurice H. Halstead Memorial Award and the Bilsland Dissertation Fellowship Award from Purdue University in 2020 and 2022 respectively. He worked as an Applied Scientist Intern at Amazon (Summer 2021)\nand a Security Researcher Intern at Intel (Summer 2020\, 2019). \nHosted By: Zhou Li \nMore Information
URL:https://www.cecs.uci.edu/event/systematic-security-analysis-of-cellular-network-specifications-and-implementations/
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/2023/10/ImtiazKarim-smaller.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240126T140000
DTEND;TZID=America/Los_Angeles:20240126T150000
DTSTAMP:20240118T174157Z
CREATED:20240118T163958Z
LAST-MODIFIED:20240118T174157Z
UID:15949-1706277600-1706281200@www.cecs.uci.edu
SUMMARY:Modeling\, Analysis\, Simulation\, and Optimization. The Bedrock of Engineering
DESCRIPTION:Title: Modeling\, Analysis\, Simulation\, and Optimization. The Bedrock of Engineering \nSpeaker: Dr. Sani Nassif \nDate and Time: Friday\, January 26th\, 2:00 pm \nLocation: EH 2430 \nAbstract: \nVLSI\, Circuit Design\, Technology Scaling\, Moore’s Law\, EDA. They are our own highly specialized areas of expertise\, and it often feels like our discipline is quite different from other fields in engineering. Indeed\, the many decades of exponential growth are unique to our field and have presented numerous challenges that were met by researchers in this area with clever solutions. But at the core of our work\, we find four steps that we take over and over again. We observe phenomena\, make physical or empirical models for them\, analyze their behavior as it impacts our goals\, create mathematical models that we can use to simulate and predict the behaviors\, and finally apply optimization or improvement techniques to create the best possible outcome. These four activities are universal across engineering practice\, and it is useful to reflect on how our own tricks and techniques -many innovated in response to the severe scaling challenges the community has had to go through\, are good lessons to apply in other fields of engineering or even in medicine. \nBiography: \nSani received his PhD from Carnegie-Mellon university in the eighties. He worked for ten years at Bell Laboratories on various aspects of design and technology coupling. He then joined IBM Research where he was for eighteen years working on DFM in various technical and management roles. In 2014 he formed Radyalis to apply EDA techniques to Cancer Radiation Therapy. Sani is a fellow of the IEEE\, a member of the IBM Academy of Technology\, and an IBM master inventor with 70+ patents. He was the president of IEEE CEDA in 2014-2016\, and has published and presented widely. \nHosted By: Fadi Kurdahi \nMore Information
URL:https://www.cecs.uci.edu/event/modeling-analysis-simulation-and-optimization-the-bedrock-of-engineering/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2024/01/Sani-Nassif-picture.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240206T150000
DTEND;TZID=America/Los_Angeles:20240206T160000
DTSTAMP:20240205T182606Z
CREATED:20240124T051514Z
LAST-MODIFIED:20240205T182606Z
UID:15960-1707231600-1707235200@www.cecs.uci.edu
SUMMARY:Electrification of Mobilities\, the Challenges and Opportunities
DESCRIPTION:Title: Electrification of Mobilities\, the Challenges and Opportunities \nSpeaker: Dr. Naehyuck Chang \nDate and Time: Tuesday\, February 6th\, 3:00 pm \nLocation: EH 2430 \nAbstract: \nThe electrification of mobilities is essential for sustainability\, and governments are pushing hard to expedite electric vehicle penetration. As a result\, it is not surprising to see a large proportion of electric vehicles on the road today. Nevertheless\, the battery industry faces significant challenges starting from late 2023\, which will continue years from now. \nIn this talk\, we will introduce industry perspective challenges and opportunities for mobility electrification in both the technical and business aspects. The technical aspects to be covered are energy density\, charging time\, lifetime\, cost\, and safety. We will also bring up infrastructure issues for electric vehicle charging. As per the business aspects\, we will discuss the electrification roadmap\, government support\, marketing challenges\, supply chain\, circularity\, expected battery costs\, raw material costs\, and profit margin. In conclusion\, we will summarize the expected academic contributions to the electrification of mobilities. \nBiography: \nNaehyuck Chang is an Executive Vice President at Samsung SDI America. He was the previous Head of Development at Samsung SDI Headquarters from 2021 to 2023. Dr. Chang was in charge of all the automotive and energy-storage product developments\, from cells to systems. Samsung SDI is one of the world’s leading high-performance battery companies. He is the Founder of EMVcon\, Inc.\, Irvine\, CA\, for vehicle electrification\, funded by Samsung. \nDr. Chang received the B.S.\, M.S.\, and Ph.D. degrees from the Department of Control and Instrumentation\, Seoul National University\, Seoul\, South Korea\, in 1989\, 1992\, and 1996\, respectively. From 1997 to 2014\, he was with the Department of Computer Science and Engineering at Seoul National University. From 2011 to 2013\, Dr. Chang was the Vice Dean of the College of Engineering at Seoul National University. Since 2014\, he has been a Full Professor at the Department of Electrical Engineering\, Korea Advanced Institute of Science and Technology\, Daejeon\, South Korea. He was the Strategy Planning Committee Chair at the College of Engineering\, Korea Advanced Institute of Science and Technology. Dr. Chang was a visiting professor at the Arizona State University and the University of Southern California in 2005 and 2009\, respectively. Dr. Chang’s research interests include low-power cyber-physical systems and Design Automation of Things\, such as systematic design and optimization of fuel cell systems\, energy storage systems\, electric vehicles\, drones\, and energy harvesting. Dr. Chang is specifically interested in mobility electrification in terms of design\, optimization\, and management of optimizing the power\, energy\, and lifetime of the battery cells. Dr. Chang’s initial research also includes nuclear power plant monitoring and control systems\, high-speed train monitoring systems\, and real-time systems. \nHosted By: Fadi Kurdahi \nMore Information
URL:https://www.cecs.uci.edu/event/electrification-of-mobilities-the-challenges-and-opportunities/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2024/01/naehyuck-pic.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240220T103000
DTEND;TZID=America/Los_Angeles:20240220T113000
DTSTAMP:20240130T180258Z
CREATED:20240130T161022Z
LAST-MODIFIED:20240130T180258Z
UID:15965-1708425000-1708428600@www.cecs.uci.edu
SUMMARY:Searching for Digital Evidence in Industrial Control Systems
DESCRIPTION:Title: Searching for Digital Evidence in Industrial Control Systems \nSpeaker: Prof. Irfan Ahmed \nDate and Time: Tuesday\, February 20th\, 10:30am \nLocation: EH 2430 \nAbstract: \nIndustrial control systems (ICS) control significant portions of the U.S. critical infrastructure (e.g.\, power grid\, pipelines\, and water management). These systems are known to be vulnerable to cyberattacks\, as demonstrated in the past\, such as CrashOverride\, Havex\, and HatMan. More recently\, DHS CISA reported Russian state-sponsored cyber operations against Ukrainian critical infrastructure\, causing denial-of-service and deployment of KillDisk and other destructive malware. In case of a security breach or catastrophic event\, digital forensics investigation is crucial to answering questions about an attack. This talk will explore how malicious actors can exploit the vulnerabilities in common design features in real-world field devices into successful attacks on physical processes. It will further discuss research challenges and opportunities to investigate an ICS environment effectively. \nBiography: \nIrfan Ahmed is a VCU NIRA scholar and an Associate Professor of Computer Science at Virginia Commonwealth University (VCU)\, where he runs the Security and Forensics Engineering (SAFE) Lab in the College of Engineering\, focusing on the cybersecurity of industrial control systems (ICS). He has an extensive track record of ICS offensive and defensive research\, including eleven ICS-CERT CVEs for the programmable logic controllers of five vendors\, i.e.\, Siemens\, Schneider Electric\, Rockwell Automation\, SEL\, and Automation Direct. Ahmed is a steering team member of the DHS Industrial Control Systems Joint Working Group (ICSJWG) to engage asset owners\, vendors\, state and local governments\, industry associations\, and consultants/integrators to improve ICS cybersecurity. His work has received three Best Paper Awards\, three Best Student Paper Awards\, and two Outstanding Poster Awards in digital forensics and cybersecurity conferences. He is also the recipient of an Outstanding Research Award from the American Academy of Forensic Sciences\, the ORAU Ralph E. Powe Junior Faculty Enhancement Award\, and the CCI Innovation Award from the Virginia Commonwealth Cyber Initiative. Ahmed has also developed laboratory-scale\, fully functional ICS testbeds on a gas pipeline and a wastewater treatment plant initially funded by the Army Research Office. His research work is regularly funded by the DHS\, NSA\, DOE\, and NSF. For more information\, https://people.vcu.edu/~iahmed3/ \nHosted By: Yasser Shoukry and Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/searching-for-digital-evidence-in-industrial-control-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/2024/01/Irfan-Ahmed-pic.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240222
DTEND;VALUE=DATE:20240224
DTSTAMP:20240425T214255Z
CREATED:20240205T192719Z
LAST-MODIFIED:20240425T214255Z
UID:16010-1708560000-1708732799@www.cecs.uci.edu
SUMMARY:Self-Awareness in Cyber-Physical Systems 2024
DESCRIPTION:Event: Self-Awareness in Cyber-Physical Systems (SelPhyS) 2024\nDate: February 22-23\, 2024\nLocation: San Diego State University (SDSU) \nRegister by: Wednesday\, February 7\, 2024\nLink to Register: https://www.eventbrite.com \nView Details
URL:https://www.cecs.uci.edu/event/self-awareness-in-cyber-physical-systems-2024/
LOCATION:San Diego State University\, San Diego\, CA\, United States
CATEGORIES:Other Events,Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2024/02/SDSU.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240401T110000
DTEND;TZID=America/Los_Angeles:20240401T120000
DTSTAMP:20240425T213942Z
CREATED:20240327T223424Z
LAST-MODIFIED:20240425T213942Z
UID:16167-1711969200-1711972800@www.cecs.uci.edu
SUMMARY:Hardware for ML and ML for Hardware
DESCRIPTION:Title: Hardware for ML and ML for Hardware \nSpeaker: Prof. Aman Arora \nDate and Time: Monday\, April 1st\, 11:00am \nLocation: EH 2430 \nAbstract: \nThis talk delves into the exciting intersection of hardware design and machine learning\, showcasing how these fields are mutually benefiting each other. The presentation will feature cutting-edge research projects that exemplify this dynamic. In the first half\, I will discuss two research projects focused on optimizing hardware for machine learning (ML): the first involves architecting ML-specialized Field Programmable Gate Arrays (FPGAs)\, while the second focuses on designing a processing-in-memory (PIM) accelerator for ML. Then\, in the second half\, I will share two innovative projects in which ML is being used to revolutionize hardware design: one employing machine learning for power\, performance\, and area (PPA) prediction for FPGAs\, and another utilizing large language models (LLMs) for hardware design and verification. I will share both published results and ongoing work in these projects. This talk highlights how the interplay between these two fields can be leveraged to advance both fields\, promising a future of intelligent computing. \nBiography: \nAman Arora is an assistant professor in the School of Computing and Augmented Intelligence at Arizona State University. He directs the Advent lab\, where he and his students work on developing computer systems that can efficiently process modern workloads like Machine Learning\, with a special focus on reconfigurable systems. He graduated with a Ph.D. from the University of Texas at Austin in 2023. He has over 10 years of experience in the semiconductor industry in design\, verification\, testing and architecture roles. \nHosted By: Prof. Sitao Huang \nMore Information
URL:https://www.cecs.uci.edu/event/hardware-for-ml-and-ml-for-hardware/
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/2024/03/Aman-Arora-3.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240425T100000
DTEND;TZID=America/Los_Angeles:20240425T110000
DTSTAMP:20240425T213745Z
CREATED:20240405T212937Z
LAST-MODIFIED:20240425T213745Z
UID:16183-1714039200-1714042800@www.cecs.uci.edu
SUMMARY:Towards Self-Sustainable Wearable IoT Devices for Reliable Mobile Health Applications
DESCRIPTION:Title: Towards Self-Sustainable Wearable IoT Devices for Reliable Mobile Health Applications \nSpeaker: Prof. Ganapati Bhat \nDate and Time: Thursday\, April 25th\, 10:00am \nLocation: EH 2430 \nAbstract: \nElectronic systems experience a major shift in their form factor every 10 to 15 years\, as evidenced by the popularity of heterogeneous mobile systems in the last decade. Wearable internet of things (IoT) devices are the next big evolution in computing systems. Wearable sensors and IoT devices\, along with smart home technologies\, have the potential to transform healthcare by enabling cost-effective\, reliable\, continuous\, and data-driven monitoring of users in a free-living environment. Despite the impressive potential of wearable technology\, widespread adoption of wearable devices has been limited due to several technology and adaptation challenges. First\, wearable devices have small batteries that necessitate frequent recharging to prolong their operation. Ambient energy sources are promising to tackle this problem\, but they are highly stochastic and must be managed optimally. Second\, wearable devices operate in dynamic environments with potential changes in data distribution. Sensor data could go missing due to energy constraints as well. This must be handled in an energy-efficient manner to enable reliable applications. I will present our solutions towards these challenges in this talk. First\, I will describe imitation learning and uncertainty aware algorithms to enable recharge-free operation of wearable devices that harvest energy from the environment. After that\, I will go over our research on algorithms to handle sensor data shifts and missing data in mobile health applications. I will conclude with some ongoing research and future directions. \nBiography: \nGanapati Bhat is an Assistant Professor in the School of Electrical Engineering and Computer Science at Washington State University. He received his B.Tech degree in Electronics and Communication from Indian Institute of Technology (ISM)\, Dhanbad\, India in 2012 and the PhD degree in Computer Engineering from Arizona State University in 2020. From 2012-2014\, he worked as a software engineer at Samsung Research and Development Institute\, Bangalore\, India. His research interests include energy optimization in computing systems\, dynamic thermal and power management\, and energy management for wearable systems. Dr. Bhat received the NSF CAREER award (2023)\, 2022 ACM Outstanding Ph.D. Dissertation Award in Electronic Design Automation\, the 2021 ACM Transactions on Design Automation of Electronic Systems (TODAES) best paper award\, and 2019 Best Paper Award at CASES: International Conference on Compilers\, architecture\, and Synthesis for Embedded Systems during the Embedded Systems Week (ESWEEK). He serves as an Associate Editor of IEEE Embedded Systems Letters and IEEE Design & Test. He regularly serves as technical program committee member top-tier conferences including DAC\, ICCAD\, ISLPED\, and ESWEEK. \nHosted By: Prof. Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/towards-self-sustainable-wearable-iot-devices-for-reliable-mobile-health-applications/
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/2024/04/ganapatibhat-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240501T110000
DTEND;TZID=America/Los_Angeles:20240501T120000
DTSTAMP:20240425T214117Z
CREATED:20240425T183332Z
LAST-MODIFIED:20240425T214117Z
UID:16212-1714561200-1714564800@www.cecs.uci.edu
SUMMARY:Agile Hardware Specialization
DESCRIPTION:Title: Agile Hardware Specialization \nSpeaker: Prof. Yun Eric Liang \nDate and Time: Wednesday\, May 1st\, 11:00am \nLocation: ISEB 4020 \nAbstract: \nAs Moore’s law is approaching to the end\, designing specialized hardware accelerator along with the software that map the applications onto the specialized hardware is a promising solution. However\, the hardware is very difficult to design and optimize due to the low-level programming and huge design space. In this talk\, I will introduce AHS\, an Agile framework for Hardware specialization. AHS can automatically partition the hardware and software space\, generate the hardware accelerator\, and map the software onto the hardware efficiently. \nBiography: \nProf. Yun Eric Liang is currently an Endowed Boya Distinguished Professor in the School of Integrated Circuit and School of EECS at Peking University. His research interest is at the hardware-software interface with work spanning electronic design automation (EDA)\, reconfigurable computing\, computer architecture. He has authored over 100 scientific publications in the leading international journals and conferences. His research has been recognized with two Best Paper Awards (FCCM 2011 and ICCAD 2017)\, six Best Paper Award Nominations. He currently serves as Associate Editor of the ACM Transactions on Embedded Computing Systems (TECS) and ACM Transactions on Reconfigurable Technology and Systems (TRETS). He is the program chair of International Conference on Field Programmable Technology (FPT) 2022 and International Conference on Application-specific Systems\, Architecture and Processors (ASAP) 2019. He also serves in the program committees in the premier conferences including DAC\, ICCAD\, FPGA\, FCCM\, HPCA\, MICRO\, DATE\, ASPDAC\, SysML\, etc. \nHosted By: Prof. Sitao Huang \nMore Information
URL:https://www.cecs.uci.edu/event/agile-hardware-specialization/
LOCATION:ISEB 4020\, Interdisciplinary Science and Engineering Building\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2024/04/Yun-Eric-Liang.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240523T100000
DTEND;TZID=America/Los_Angeles:20240523T110000
DTSTAMP:20240528T214031Z
CREATED:20240516T161556Z
LAST-MODIFIED:20240528T214031Z
UID:16284-1716458400-1716462000@www.cecs.uci.edu
SUMMARY:Dissecting the Software Supply Chain of Modern Industrial Control Systems
DESCRIPTION:Title: Dissecting the Software Supply Chain of Modern Industrial Control Systems \nSpeaker: Prof. Michail Maniatakos \nDate and Time: Thursday\, May 23rd\, 10:00am \nLocation: Zoom \nAbstract: \nRecent years have been pivotal in the field of Industrial Control Systems (ICS) security\, with a large number of high-profile attacks exposing the lack of a design-for-security initiative in ICS. The evolution of ICS abstracting the control logic to a purely software level hosted on a generic OS\, combined with hyperconnectivity and the integration of popular open source libraries providing advanced features\, have expanded the ICS attack surface by increasing the entry points and by allowing traditional software vulnerabilities to be repurposed to the ICS domain. In this seminar\, we will shed light to the security landscape of modern ICS\, dissecting firmware from the dominant vendors and motivating the need of employing appropriate vulnerability assessment tools. We will present methodologies for blackbox fuzzing of modern ICS\, both directly using the device and by using the development software. We will then proceed with methodologies on hotpatching\, since ICS cannot be easily restarted in order to patch any discovered vulnerabilities. We will demonstrate our proposed methodologies on various critical infrastructure testbeds. \nBiography: \nMichail (Mihalis) Maniatakos is an Associate Professor of Electrical and Computer Engineering at New York University (NYU) Abu Dhabi\, UAE\, and a Research Associate Professor at the NYU Tandon School of Engineering\, New York\, USA. He is the Director of the MoMA Laboratory (nyuad.nyu.edu/momalab)\, NYU Abu Dhabi. He received his Ph.D. in Electrical Engineering\, as well as M.Sc.\, M.Phil. degrees from Yale University. He also received the B.Sc. and M.Sc. degrees in Computer Science and Embedded Systems\, respectively\, from the University of Piraeus\, Greece. His research interests\, funded by industrial partners\, the US government\, and the UAE government include privacy-preserving computation and industrial control systems security. \nHosted By: Prof. Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/dissecting-the-software-supply-chain-of-modern-industrial-control-systems/
LOCATION:Zoom
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2024/05/MichailManiatakos_5-23-24-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20241017T150000
DTEND;TZID=America/Los_Angeles:20241017T160000
DTSTAMP:20241014T182231Z
CREATED:20241011T160628Z
LAST-MODIFIED:20241014T182231Z
UID:16367-1729177200-1729180800@www.cecs.uci.edu
SUMMARY:Storage-Centric Computing for Genomics and Metagenomics
DESCRIPTION:Title: Storage-Centric Computing for Genomics and Metagenomics \nSpeaker: Nika Mansouri Ghiasi \nDate and Time: Thursday\, October 17th\, 3:00pm \nLocation: DBH 4011 \nAbstract: \nGenomics and metagenomics applications have enabled significant advancements in many critical areas. The exponential growth of genomic data poses unprecedented challenges in genomics and metagenomic applications. These applications suffer from significant data movement overheads from the storage system. To fundamentally address these overheads\, we make a case for storage-centric computing. \nFirst\, we propose GenStore\, the first in-storage processing system designed for genome sequence analysis that greatly reduces both data movement and computational overheads of genome sequence analysis by exploiting low-cost and accurate in-storage filters. We address the challenges of in-storage processing\, supporting reads with 1) different read lengths and error rates\, and 2) different degrees of genetic variation. Through rigorous analysis of read mapping processes\, we design low-cost hardware accelerators and data/computation flows inside a NAND flash-based SSD. Our evaluation using a wide range of real genomic datasets shows that GenStore significantly improves the read mapping performance of state-of-the-art software (hardware) baselines by 2.07-6.05× (1.52-3.32×) for read sets with high similarity to the reference genome and 1.45-33.63× (2.70-19.2×) for read sets with low similarity to the reference genome. \nSecond\, we propose MegIS\, the first in-storage processing system designed to significantly reduce the data movement overhead of the end-to-end metagenomic analysis pipeline. MegIS is enabled by our lightweight design that effectively leverages and orchestrates processing inside and outside the storage system. Through our detailed analysis of the end-to-end metagenomic analysis pipeline and careful hardware/software co-design\, we address in-storage processing challenges for metagenomics via specialized and efficient 1) task partitioning\, 2) data/computation flow coordination\, 3) storage technology-aware algorithmic optimizations\, 4) data mapping\, and 5) lightweight in-storage accelerators. MegIS’s design is flexible\, capable of supporting different types of metagenomic input datasets\, and can be integrated into various metagenomic analysis pipelines. Our evaluation shows that MegIS outperforms the state-of-the-art performance- and accuracy-optimized software metagenomic tools by 2.7×–37.2× and 6.9×–100.2×\, respectively\, while matching the accuracy of the accuracy-optimized tool. MegIS achieves 1.5×–5.1× speedup compared to the state-of-the-art metagenomic hardware-accelerated (using processing-in-memory) tool\, while achieving significantly higher accuracy. \nBiography: \nNika Mansouri Ghiasi is a Ph.D. candidate in the SAFARI Research Group at ETH Zürich\, working with Professor Onur Mutlu. Her current research interests are in computer architecture\, emerging technologies\, bioinformatics\, and their interactions. \nHosted By: Prof. Alex Veidenbaum \nMore Information
URL:https://www.cecs.uci.edu/event/storage-centric-computing-for-genomics-and-metagenomics/
LOCATION:DBH 4011\, Donald Bren Hall\, University of California\, Irvine\, Irvine\, CA\, 92617\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2024/10/OIP-e1728930126635.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20241018T140000
DTEND;TZID=America/Los_Angeles:20241018T150000
DTSTAMP:20250404T180934Z
CREATED:20241014T181841Z
LAST-MODIFIED:20250404T180934Z
UID:16376-1729260000-1729263600@www.cecs.uci.edu
SUMMARY:In Vitro Biological Neural Networks
DESCRIPTION:Title: In Vitro Biological Neural Networks \nSpeaker: Prof. Lawrence Rauchwerger \nDate and Time: Friday\, October 18th\, 2:00pm \nLocation: EH 2430 \nAbstract: \nA computing stack powered by living neurons could unlock self-organizing and dynamically rewiring systems with extreme connectivity and parallel processing power\, all while running on sugar with unprecedented energy efficiency. In this presentation we outline a framework that leverages in-silico simulation to establish an engineering testbed with the ultimate goal of learning to harness neural in-vitro systems for computational purposes. We describe an optimization approach to uncover reproducible neural activity present in a system that can be leveraged to carry out basic information processing tasks. We demonstrate the feasibility of this approach by optimizing a simulated neural system to perform digit classification\, offering a proof-of-concept for a potential pathway to leveraging neural computation in vitro. \nBiography: \nLawrence Rauchwerger is a professor in the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign. He holds a doctoral degree in computer science from the University of Illinois Urbana-Champaign and an M.S. in electrical engineering from Stanford University. Rauchwerger is known for his approach to auto-parallelization\, thread-level speculation and parallel library (STAPL). His research interests are in compilers for parallel computing\, parallel and distributed C++ libraries\, adaptive runtime optimizations\, and architectures for parallel computing. Lately he has become active in neurocomputing. He received an IBM Faculty Award\, an Intel Faculty Award\, and the NSF Faculty Early Career Development\n(CAREER) Award. He is an IEEE Fellow and a AAAS Fellow. \nHosted By: Prof. Alex Veidenbaum \nMore Information
URL:https://www.cecs.uci.edu/event/in-vitro-biological-neural-networks/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2024/10/Lawrence-Rauchwerger-e1728930349485.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250312T140000
DTEND;TZID=America/Los_Angeles:20250312T150000
DTSTAMP:20250404T180622Z
CREATED:20250306T194035Z
LAST-MODIFIED:20250404T180622Z
UID:16409-1741788000-1741791600@www.cecs.uci.edu
SUMMARY:Optimizing AI Performance: Bridging Algorithmic and Hardware Innovations from Inference to Training
DESCRIPTION:Title: Optimizing AI Performance: Bridging Algorithmic and Hardware Innovations from Inference to Training \nSpeaker: Prof. Yu Bai \nDate and Time: Wednesday\, March 12\, 2:00pm \nLocation: ISEB 1200 \nAbstract: \nArtificial intelligence (AI) continues to reshape industries and research\, but its rapid growth comes with significant computational and energy costs. This talk explores the challenges and innovations in optimizing AI efficiency\, bridging algorithmic advancements and hardware design to enhance performance from inference to training. The presentation covers two main avenues for improving AI efficiency: model optimization techniques and hardware specialization. Algorithmic strategies such as low-rank tensor decomposition\, structured sparsity\, quantization-aware training\, and compression of large-scale models (e.g.\, LLMs and diffusion models) are discussed. These methods aim to reduce memory requirements\, computational overhead\, and energy consumption while maintaining model accuracy. On the hardware side\, the talk highlights cutting-edge AI accelerators\, dataflow optimizations\, and emerging techniques like in-storage computing for AI hardware. Novel architectures such as the Tensor-Train-based Inference and energy-efficient training solutions are presented\, demonstrating substantial improvements in model compression\, multi-modal AI\, and real-time generative AI tasks. The talk also touches on the broader implications of AI efficiency\, including its impact on embedded AI platforms\, cloud-based AI\, and future developments in efficient AI hardware and software co-design. Through interdisciplinary collaboration and Industry and NSF-supported research\, this work aims to advance the next generation of AI technology\, making it both powerful and sustainable. \nBiography: \nDr. Yu Bai is an Associate Professor and Director of the Intelligent Computing Research Lab at California State University. His research focuses on emerging AI techniques\, energy-efficient AI systems\, and interdisciplinary AI applications\, spanning neuromorphic computing\, generative AI\, deep learning for IoT devices\, and high-performance computing. Dr. Bai has authored over 50 peer-reviewed publications in top AI conferences and journals\, contributing significantly to efficient neural network optimization\, AI hardware-software co-design\, and hyperspectral imaging. His work has been recognized with numerous accolades\, including the Best Researcher Award (2023) from Citation Award\, the Faculty Scholarly and Creative Activity Award (2021)\, and inclusion in Who’s Who in America. With a proven track record in securing research funding\, Dr. Bai has received over $4 million in competitive grants from agencies such as the National Science Foundation (NSF)\, the Army Research Office\, and industry-academic collaborations. His funded projects include pioneering efforts in edge AI architectures\, AI applications in biological systems\, and inclusive AI education strategies. A National Academies of Sciences\, Engineering\, and Medicine (NASEM) awardee\, Dr. Bai is dedicated to advancing AI research and fostering a diverse\, inclusive STEM community through his teaching\, mentorship\, and collaborative initiatives. \nHosted By: Prof. Fadi Kurdahi and Prof. Mohammad Al Faruque \nMore Information
URL:https://www.cecs.uci.edu/event/optimizing-ai-performance-bridging-algorithmic-and-hardware-innovations-from-inference-to-training/
LOCATION:ISEB 1200\, Interdisciplinary Science and Engineering Building University of California\, Irve\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/jpeg:https://cecs.uci.edu/files/2025/03/Yu-Bai-800x500-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250421T110000
DTEND;TZID=America/Los_Angeles:20250421T120000
DTSTAMP:20250417T173945Z
CREATED:20250415T195856Z
LAST-MODIFIED:20250417T173945Z
UID:16437-1745233200-1745236800@www.cecs.uci.edu
SUMMARY:Security in Heterogeneous Systems
DESCRIPTION:Title: Security in Heterogeneous Systems \nSpeaker: Yicheng Zhang \nDate and Time: Monday\, April 21\, 11:00am \nLocation: EH 2430 \nAbstract: \nTo improve the performance and efficiency of modern computing systems\, architects increasingly adopt heterogeneous designs that tightly integrate specialized accelerators such as GPUs and FPGAs. These accelerators enable substantial speedups for compute-intensive workloads like machine learning and AR/VR. However\, they also diverge fundamentally from traditional CPU-based systems and introduce a new class of security risks. Unlike prior work that focused on CPU vulnerabilities such as Spectre and Meltdown\, heterogeneous systems expose new attack surfaces due to their architectural complexity and shared resource usage. In this talk\, I will present my research efforts to uncover and mitigate security vulnerabilities in these heterogeneous platforms. First\, I will introduce a set of side-channel attacks targeting AR/VR devices\, leveraging rendering performance counters to recover sensitive user inputs such as virtual keystrokes and voice commands. I will then shift to large-scale cloud environments\, where I demonstrate the first end-to-end side-channel attack that exploits NVLink\, NVIDIA’s high-speed GPU interconnect\, through contention-based and performance-counter-based microarchitectural channels. To conclude\, I will present a defense framework that uses GPU side-channel signatures to validate kernel execution integrity. This approach detects tampering from attacks like buffer overflows and Rowhammer\, turning side channels into a practical tool for runtime verification. Together\, these efforts lay the groundwork for securing future heterogeneous computing platforms across both edge and cloud environments. \nBiography: \nYicheng Zhang is a fourth-year Ph.D. candidate at the University of California\, Riverside\, advised by Prof. Nael Abu-Ghazaleh. Prior to that\, he received his M.Sc. from UC Irvine and his B.S. from Sichuan University. His research interests lie in computer architecture and system security\, with a focus on AR/VR security and microarchitectural security. His work has been\nrecognized by top-tier conferences and journals including multiple USENIX Security\, IEEE S&P\, IEEE DSN and IEEE TIFS. More information can be found at his website: https://yichez.site/ \nHosted By: Prof. Zhou Li \nMore Information
URL:https://www.cecs.uci.edu/event/security-in-heterogeneous-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/2025/04/yicheng.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250519T110000
DTEND;TZID=America/Los_Angeles:20250519T120000
DTSTAMP:20250513T184038Z
CREATED:20250513T183835Z
LAST-MODIFIED:20250513T184038Z
UID:16459-1747652400-1747656000@www.cecs.uci.edu
SUMMARY:Efficient and Robust Defense against Query-based Black-box Attacks
DESCRIPTION:Title: Efficient and Robust Defense against Query-based Black-box Attacks \nSpeaker: Shaofei Li \nDate and Time: Monday\, May 2119\, 11:00am \nLocation: EH 2430 \nAbstract: \nQuery-based black-box attacks have emerged as a significant threat to machine learning systems\, where adversaries can manipulate the input queries to generate adversarial examples that can cause misclassification of the system. To counter these attacks\, researchers have proposed Stateful Defense Models (SDMs) such as BlackLight and PIHA\, which can reject queries that are “similar” to historical queries. However\, recent studies show that existing approaches are vulnerable to a stronger adaptive attack\, Oracle-guided Adaptive Rejection Sampling (OARS). OARS can be easily integrated with existing attack algorithms to evade the SDMs by generating queries with fine-tuned direction and step size of perturbations utilizing the leaked decision boundary from the SDMs. In this talk\, I will present our novel approach\, Query Provenance Analysis (QPA)\, for defending against query-based black-box attacks robustly (against both non-adaptive and adaptive attacks) and efficiently (in real-time). The key insight is that\, instead of focusing on individual queries\, utilizing features from the query sequence (termed query provenance) can distinguish malicious queries from benign queries more effectively. So it constructs a query provenance graph to capture the relationship between a new query and prior historical queries\, and then design efficient algorithms to detect malicious queries based on the query provenance graphs. As a results\, QPA outperforms the baselines regarding defense robustness and efficiency on both non-adaptive and adaptive attacks. It can also be deployed for various attack scenarios\, such as membership inference attack and jailbreaking. \nBiography: \nShaofei Li is currently a fourth-year Ph.D. student in the Department of Computer Science at Peking University\, advised by Prof. Ding Li\, Prof. Yao Guo and Prof. Xiangqun Chen. He received his B.S. degree from the School of Electronics Engineering and Computer Science (EECS) at Peking University in 2021. His research interests lie in cybersecurity\, system security and AI security. His research focuses on developing detection and defense mechanisms for various security threats in the real world systems. He has published several papers in top-tier security conferences and transactions such as S&P\, NDSS\, CCS and TOSEM. More information can be found at his website: https://shaofei-li.org/ \nHosted By: Prof. Zhou Li \nMore Information
URL:https://www.cecs.uci.edu/event/efficient-and-robust-defense-against-query-based-black-box-attacks/
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/2025/05/shaofei_li.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250519T110000
DTEND;TZID=America/Los_Angeles:20250519T120000
DTSTAMP:20250513T184743Z
CREATED:20250513T184624Z
LAST-MODIFIED:20250513T184743Z
UID:16468-1747652400-1747656000@www.cecs.uci.edu
SUMMARY:TEE-Shielded LLM Partition – Efficiently Protect Model Security on User Devices
DESCRIPTION:Title: TEE-Shielded LLM Partition – Efficiently Protect Model Security on User Devices \nSpeaker: Ziqi Zhang \nDate and Time: Monday\, May 19\, 11:00am \nLocation: EH 2430 \nAbstract: \nIn this talk\, I will introduce recent work on TEE-based LLM protection (TSLP) on the user devices: TEESlice (S&P24) and ArrowCloak (Security25 revision). Existing TEE products provides high security guarantee\, but usually lack GPU support and introduce additional inference latency. TSLP aims to incorporate untrusted GPU into TEE to reduce computation overhead. TSLP partition a LLM into two parts\, offloading the privacy-insensitive part to the GPU while shielding the critical privacy-sensitive part within the TEE. In TEESlice\, we systematically review and benchmark existing TSDP solutions and reveal that offloading model weights in plain-text leaks model privacy. Based on the observation\, TEESlice uses a partition-before-training strategy for accurate separation between privacy-related weights from public weights. In ArrowCloak\, we review existing lightweight weight obfuscation solutions in TSLP and find that these solutions cannot effectively protect vector direction in the weight matrix. We use a proof-of-concept attack to exploit this vulnerability and propose ArrowCloak that uses vector-matrix multiplication to protect vector direction. \nBiography: \nZiqi Zhang is currently a Postdoc Researcher at University of Illinois Urbane-Champaign\, working with Lingming Zhang. In 2023\, he obtained Ph.D degree in the School of Computer Science from Peking University in China. Before that\, he obtained the bachelor degree in the School of EECS of Peking University in 2018. His research interests lie in AI security\, software engineering\, and software security. His interested topics include trusted AI\, AI with trusted hardware\, and AI with SE. He has published several papers at top-tier conferences in various domains\, including computer security (S&P\, USENIX Security\, CCS)\, software engineering (ESEC/FSE\, ICSE\, ISSTA\, ISSRE)\, AI (ICML\, WWW)\, and ubiquitous computing (Ubicomp). More information can be found at https://ziqi-zhang.github.io/ \nHosted By: Prof. Zhou Li \nMore Information
URL:https://www.cecs.uci.edu/event/tee-shielded-llm-partition-efficiently-protect-model-security-on-user-devices/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2025/05/ziqi_zhang.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250609T110000
DTEND;TZID=America/Los_Angeles:20250609T120000
DTSTAMP:20261027T171544Z
CREATED:20250522T200123Z
LAST-MODIFIED:20261027T171544Z
UID:16475-1749466800-1749470400@www.cecs.uci.edu
SUMMARY:Confidential Computing and Trusted Execution Environment: Challenges\, Opportunities\, and the Future
DESCRIPTION:Title: Confidential Computing and Trusted Execution Environment: Challenges\, Opportunities\, and the Future \nSpeaker:  Mengyuan Li \nDate and Time: Monday\, June 9\, 11:00am \nLocation: EH 2430 \nAbstract: \nConfidential Computing\, or Trusted Execution Environment (TEE)\, represents a cutting-edge design in server-grade CPUs. This technology acts as a protective shield for cloud tasks\, safeguarding the confidentiality and integrity of cloud workloads against a range of threats\, including attacks from privileged software\, physical attackers\, and untrustworthy hypervisors. As the demand for secure private data handling continues to rise\, the adoption of Confidential Computing has become widespread across various industries. Evidence of this includes the adoption of TEE in server-grade CPUs from major vendors like Intel\, AMD\, and ARM. Furthermore\, leading cloud service providers\, such as AWS\, Google Cloud\, Microsoft Azure\, and IBM Cloud\, now offer commercial Confidential Computing services. In this talk\, I will outline my contributions to the study of complex\, heterogeneous Confidential Computing systems. I will share my insights into two real-world vulnerabilities we uncovered within commercial Confidential Computing systems\, along with our joint efforts with CPU manufacturers to address these issues in the latest server-grade CPUs. At the hardware design level\, I will discuss a novel ciphertext side-channel attack targeting hardware-accelerated memory encryption\, which is a crucial hardware feature to protect the memory of cloud workloads. Moving to the software system design level\, I will illustrate how inadequately designed TEE operating systems can pose a threat to the security of Confidential VMs. Finally\, I will outline my ongoing efforts and future directions in enhancing the security and effectiveness of Confidential Computing and my research vision towards building secure and performant hardware systems. \nBiography: \nDr. Mengyuan Li is an Assistant Professor of Computer Science at the University of Southern California (with a courtesy appointment in the ECE department) . Before joining USC\, he was a postdoctoral researcher at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds a Ph.D. from Ohio State University and a bachelor’s degree from Shanghai Jiao Tong University. His research vision is to contribute to the creation of a secure and trustworthy computing environment where private data and programs are well protected. In pursuit of this vision\, his research interests include system security and privacy\, cloud security\, Trusted Execution Environments\, confidential computing\, CPU security\, micro-architectural security\, GPU security\, and AI security. He has published over 20 papers at leading security and privacy conferences\, including IEEE S&P\, Usenix Security\, and CCS\, and holds multiple technology patents. \nHosted By: Prof. Zhou Li \nMore Information
URL:https://www.cecs.uci.edu/event/confidential-computing-and-trusted-execution-environment-challenges-opportunities-and-the-future/
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/2025/05/Mengyuan_pic-e1793121341316.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251015T140000
DTEND;TZID=America/Los_Angeles:20251015T150000
DTSTAMP:20261027T171519Z
CREATED:20251007T230120Z
LAST-MODIFIED:20261027T171519Z
UID:16512-1760536800-1760540400@www.cecs.uci.edu
SUMMARY:Unleashing Multi-GPU Computing to the Next-Level
DESCRIPTION:Title: Unleashing Multi-GPU Computing to the Next-Level \nSpeaker:  Dr. Xulong Tang \nDate and Time: Wednesday\, October 15\, 2:00pm \nLocation: EH 2430 \nAbstract: \nModern computing platforms increasingly rely on multi-GPU systems to deliver the performance\, bandwidth\, and memory capacity required by data-intensive applications spanning cloud and edge services to large language models (LLMs) and quantum workloads. However\, scaling GPUs beyond single-device encounters fundamental system-level challenges\, including address translation overheads\, complex memory management\, and inefficient multi-tenancy in shared environments. In this talk\, I will present our recent efforts on hardware-software co-design to overcome these bottlenecks and unleash the full potential of multi-GPU computing. I will discuss novel techniques such as lightweight invalidations for page translation\, short-circuiting page table walks\, and multi-instance GPU (MIG) reconfiguration strategies that collectively deliver substantial performance and efficiency gains. Looking forward\, I will highlight emerging research directions in scalable heterogeneous GPU architectures and memory management in GPU virtualization. An especially exciting avenue is applying these insights to LLMs\, where efficient GPU memory use and multi-GPU coordination are critical for KV-cache reuse\, reduced serving latency\, and scalable throughput. Together\, these innovations pave the way for the next generation of GPU systems that can power both large-scale scientific computing and next-generation intelligent applications. \nBiography: \nDr. Xulong Tang is an Associate Professor in the Department of Computer Science at the University of Pittsburgh. His research spans computer architecture and systems\, with a focus on multi-GPU architectures\, scalable memory management\, and heterogeneous computing across high-performance\, edge\, and quantum systems. His group has pioneered advances in GPU memory management\, temporal graph neural network training\, and quantum compilation. Dr. Tang has published extensively in premier venues such as MICRO\, HPCA\, ISCA\, ASPLOS\, PLDI\, ICLR\, and NeurIPS\, and his work has received recognition including an Intel Research Award\, an ICLR Spotlight Award\, and a MICRO Best Paper Nomination. He is also active in the community\, serving as General Co-Chair of ASPLOS 2026 and Vice Chair of the IEEE Micro Top Picks 2025 Selection Committee. \nHosted By: Prof. Sitao Huang \nMore Information
URL:https://www.cecs.uci.edu/event/unleashing-multi-gpu-computing-to-the-next-level/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
ATTACH;FMTTYPE=image/png:https://cecs.uci.edu/files/2025/10/Xulong_10_15_25-e1793121315619.png
END:VEVENT
BEGIN:VEVENT
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
END:VEVENT
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
END:VEVENT
BEGIN:VEVENT
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
END:VEVENT
BEGIN:VEVENT
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
END:VEVENT
END:VCALENDAR