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X-WR-CALDESC:Events for CECS
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T192201Z
CREATED:20231031T192201Z
LAST-MODIFIED:20231031T192201Z
UID:15776-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Mohammad Al Faruque Received Distinguished Lecturer Nomination by IEEE CEDA
DESCRIPTION:Professor Mohammad Al Faruque Received Distinguished Lecturer Nomination by the IEEE Central Dredging Association for promoting the field of electronic design automation to the scientific community and the public at large. Congrats Prof. Al Faruque!
URL:https://www.cecs.uci.edu/event/mohammad-al-faruque-received-distinguished-lecturer-nomination-by-ieee-ceda/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T192244Z
CREATED:20231031T192244Z
LAST-MODIFIED:20231031T192244Z
UID:15780-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Ardalan Amiri Sani Won ICS Dean’s Mid-Career Award for Research
DESCRIPTION:Assistant Professor Ardalan Amiri Sani won the ICS Dean’s Mid-Career Award for Research to recognize his innovative research\, exemplar service\, student mentorship and exceptional teaching skills. Congrats Prof. Sani!
URL:https://www.cecs.uci.edu/event/ardalan-amiri-sani-won-ics-deans-mid-career-award-for-research/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T192402Z
CREATED:20231031T192402Z
LAST-MODIFIED:20231031T192402Z
UID:15784-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Ahmed Eltawil Awarded Innovator of the Year Award
DESCRIPTION:Professor Ahmed Eltawil was awarded Innovator of the Year Award by the Henry Samueli School of Engineering for his journey of innovation to commercialization of full duplex technology is a successful example of entrepreneurship based on “Made at UCI’ technology. Congrats Prof. Eltawil!
URL:https://www.cecs.uci.edu/event/ahmed-eltawil-awarded-innovator-of-the-year-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T192455Z
CREATED:20231031T192455Z
LAST-MODIFIED:20231031T192455Z
UID:15788-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Yasser Shoukry Won IEEE Early Career Award
DESCRIPTION:Assistant Professor Yasser Shoukry won IEEE Early Career Award for demonstrated outstanding contributions to the field of cyber-physical systems in the early stage of his career. Congrats Prof. Shoukry!
URL:https://www.cecs.uci.edu/event/yasser-shoukry-won-ieee-early-career-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T192557Z
CREATED:20231031T192557Z
LAST-MODIFIED:20231031T192557Z
UID:15792-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Payam Heydari Named UCI Chancellor’s Professor
DESCRIPTION:Professor Payam Heydari named UCI Chancellor’s Professor to recognize his research contribution in microelectronics\, specifically in the design and analysis of radio frequency\, millimeter-wave and terahertz integrated circuits. Congrats Prof. Heydari!
URL:https://www.cecs.uci.edu/event/payam-heydari-named-uci-chancellors-professor/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T192907Z
CREATED:20231031T192907Z
LAST-MODIFIED:20231031T192907Z
UID:15796-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Yasser Shoukry Awarded Early-Career Award
DESCRIPTION:Assistant Professor Yasser Shoukry was awarded the Early-Career Award by the IEEE Technical Committee on Cyber-Physical Systems for the contributions to the theory and design of safe learning-enabled cyber-physical systems. Congrats Prof. Shoukry!
URL:https://www.cecs.uci.edu/event/yasser-shoukry-awarded-early-career-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20211031T080000
DTEND;TZID=America/Los_Angeles:20211031T170000
DTSTAMP:20231031T193007Z
CREATED:20231031T193007Z
LAST-MODIFIED:20231031T193007Z
UID:15800-1635667200-1635699600@www.cecs.uci.edu
SUMMARY:Luke Chen Received John and Joanna Duffy Graduate Fellowship Award
DESCRIPTION:Luke Chen received John and Joanna Duffy Graduate Fellowship Award\, supports M.S. student who can enhance the diversity\, equity\, and inclusion of EECS graduate program. Congrats Chen!
URL:https://www.cecs.uci.edu/event/luke-chen-received-john-and-joanna-duffy-graduate-fellowship-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220516T090000
DTEND;TZID=America/Los_Angeles:20220516T100000
DTSTAMP:20231011T032339Z
CREATED:20231011T032339Z
LAST-MODIFIED:20231011T032339Z
UID:14132-1652691600-1652695200@www.cecs.uci.edu
SUMMARY:Internet of Things-Based Collaborative Position-Sensing Systems for Cardiopulmonary Resuscitation and Indoor Localization
DESCRIPTION:Name: Chen\, Hsin-Chung “Andrew” \nChair: Pai Chou \nDate:  Wednesday\, March 16\, 2022 \nTime: 9:00 am \nLocation:  https://uci.zoom.us/j/93264053012 \nCommittee: Nader Bagherzadeh\, Rainer Doemer \nTitle: Internet of Things-Based Collaborative Position-Sensing Systems for Cardiopulmonary Resuscitation and Indoor Localization \nAbstract: \nThe ubiquitous IoT devices have promoted the growth of applications that require target positioning. While precise positioning remains a challenge for IoT devices\, existing methods mainly focus on optimizing the positioning algorithms or expanding the sensing modalities. One opportunity area of improvement is to leverage their wireless communication capability to exchange sensing data of different modalities with nearby devices. This work proposes collaborative sensing frameworks to enhance the accuracy of position inference. \nOur approach to collaborative sensing is divided into selection of reliable devices\, the data-exchange mechanism\, and the data-fusion algorithm. We demonstrate our approach on two different position-sensing systems: one for chest compression-depth estimation and one for indoor pedestrian localization. The key components used in the frameworks include quality assessment of sensor data using mutual information\, data-fusion algorithms based on the chest-compression model and the pedestrian-encounter model\, and the data-exchange mechanism using Bluetooth Low Energy (BLE). A real-time position-estimation method based on our chest-compression model is proposed to remove the noise and handle the cumulative error. A collaborative conditional random field algorithm is developed to reduce the convergence distance in the localization estimation. Experimental results show our collaborative-sensing approach outperforms the existing solutions in terms of real-time estimated position. \nThis dissertation proposes an alternative approach to optimizing the position-sensing systems through collaborative sensing. Our work represents the first step towards the universal positioning on IoT devices and provides research opportunities for further improvement and exploration. \n\nShort Bio: Hsinchung Chen is a Ph.D. candidate in computer engineering. His research interests include signal processing\, machine learning\, and embedded system design.
URL:https://www.cecs.uci.edu/event/internet-of-things-based-collaborative-position-sensing-systems-for-cardiopulmonary-resuscitation-and-indoor-localization/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220517T140000
DTEND;TZID=America/Los_Angeles:20220517T150000
DTSTAMP:20231011T032340Z
CREATED:20231011T032340Z
LAST-MODIFIED:20231011T032340Z
UID:14133-1652796000-1652799600@www.cecs.uci.edu
SUMMARY:"Beyond Approximate Computing: Quality-Scalability for Low-Power Embedded Systems and Machine Learning"
DESCRIPTION:Speaker: Younghyun Kim\nDate and Time: Tuesday\, May 17\, 2022 at 2:00 p.m. \nLocation: Zoom https://uci.zoom.us/j/98632011722 \nAbstract: \nApproximate computing is a new paradigm to accomplish energy-efficient computing in this twilight of Moore’s law by relaxing the exactness requirement of computation results for intrinsically error-resilient applications\, such as deep learning and signal processing\, and producing results that are “just good enough.” It exploits that the output quality of such error-resilient applications is not fundamentally degraded even if the underlying computations are greatly approximated. This favorable energy-quality tradeoff opens up new opportunities to improve the energy efficiency of computing\, and a large body of approximate computing methods for energy-efficient “data processing” have been proposed. In this talk\, I will introduce approximate computing methods to accomplish “full-system energy-quality scalability.” It extends the scope of approximation from the processor to other system components including sensors\, interconnects\, etc.\, for energy-efficient “data generation” and “data transfer” to fully exploit the energy-quality tradeoffs across the entire system. I will also discuss how approximate computing can benefit the implementation of machine learning on ultra low-power embedded systems. \nBiography: \nProf. Younghyun Kim is an Assistant Professor in the Department of Electrical and Computer Engineering and an ECE Grainger Faculty Scholar at the University of Wisconsin-Madison\, where leads the Wisconsin Embedded Systems and Computing (WISEST) Laboratory (https://wisest.ece.wisc.edu/). Prof. Kim received his B.S. degree in computer science and engineering and his Ph.D. degree in electrical engineering and computer science from Seoul National University in 2007 and 2013\, respectively. He was a Postdoctoral Research Assistant at Purdue University and a visiting scholar at the University of Southern California. His current research interests include energy-efficient computing and security and privacy of the Internet-of-Things. Prof. Kim was a recipient of several awards\, including the NSF Faculty Early Career Development Program (CAREER) Award\, Facebook Research Award\, IEEE Micro Top Pick\, the EDAA Outstanding Dissertation Award\, and the Design Contest Awards at the ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED). He served on the Technical Program Committees of various conferences on design automation and embedded systems\, including the Design Automation Conference (DAC)\, ISLPED\, Asia and South Pacific Design Automation Conference (ASP-DAC)\, International Conference on VLSI Design (VLSID)\, and Symposium on Applied Computing (SAC). He served as a Guest Editor for a Special Issue of VLSI Integration Journal (Elsevier). \nHosted By: Prof. Nikil Dutt \n 
URL:https://www.cecs.uci.edu/event/beyond-approximate-computing-quality-scalability-for-low-power-embedded-systems-and-machine-learning/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220523T140000
DTEND;TZID=America/Los_Angeles:20220523T150000
DTSTAMP:20231011T032340Z
CREATED:20231011T032340Z
LAST-MODIFIED:20231011T032340Z
UID:14135-1653314400-1653318000@www.cecs.uci.edu
SUMMARY:"Runtime Monitoring of Distributed Cyber-physical Systems"
DESCRIPTION:Speaker: Borzoo Bonakdarpour\nDate and Time: Monday\, May 23\, 2022 at 2:00 pm \nLocation: DBH 3011 \nAbstract:  \nWe consider the problem of detecting violations of specification In the signal temporal logic over distributed continuous-time and continuous-valued signals in cyber-physical systems (CPS). We assume a partially synchronous setting\, where a clock synchronization algorithm guarantees a bound on clock drifts among all signals. We introduce a novel retiming method that allows reasoning about the correctness of predicates among continuous-time signals that do not share a global view of time. The resulting problem is encoded as an SMT problem and we introduce techniques to solve the SMT encoding efficiently. Leveraging simple knowledge of physical dynamics allows further runtime reductions. We will discuss case studies on monitoring a network of autonomous ground vehicles\, a network of aerial vehicles\, and a water distribution system. \nBiography: Borzoo Bonakdarpour is currently an Associate Professor of Computer Science at Michigan State University. His research interests include formal methods and its application in distributed systems\, computer security\, and cyber-physical systems. He has published more than 100 articles and papers in top journals and conferences. His work in these areas have received multiple best paper awards from highly prestigious conferences\, including\, RV’21\, SRDS’17\, SSS’14\, and SIES’10. He chaired the Technical Program Committee of the SRDS’20\, SSS’16\, and RV’14 conferences. \nHosted By: Prof. Eli Bozorgzadeh \n 
URL:https://www.cecs.uci.edu/event/runtime-monitoring-of-distributed-cyber-physical-systems/
LOCATION:DBH 3011\, Donald Bren Hall University of California\, Irve\, Irvine\, CA\, 92617\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220707T100000
DTEND;TZID=America/Los_Angeles:20220707T230000
DTSTAMP:20231011T032340Z
CREATED:20231011T032340Z
LAST-MODIFIED:20231011T032340Z
UID:14136-1657188000-1657234800@www.cecs.uci.edu
SUMMARY:Transaction-Level Modeling of Deep Neural Networks for Efficient Parallelism and Memory Accuracy
DESCRIPTION:Name: Emad Arasteh\nChair: Prof. Rainer Doemer \nDate: July 7\, 2022 \nTime: 10:00 am \nLocation: EH 3206 \nCommittee: Prof. Fadi Kurdahi\, Prof. Ian Harris \nTitle: Transaction-Level Modeling of Deep Neural Networks for Efficient Parallelism and Memory Accuracy \nAbstract:  \nThe emergence of data-intensive applications\, such as Deep Neural Networks (DNNs)\, exacerbates the well-known memory bottleneck in computer systems and demands early attention in the design flow. Electronic System-Level (ESL) design using SystemC Transaction Level Modeling (TLM) enables effective performance estimation\, design space exploration\, and gradual refinement. In this dissertation\, we present our exploratory modeling framework for hardware-software codesign based on SystemC TLM with particular focus on exposing parallelism and memory contention. We demonstrate the effectiveness of our approach for representative complex DNNs such as GoogLeNet and Single Shot MultiBox Detector. \nFirst\, we study the impact of communication mechanisms on the available parallelism in TLM models. Specifically\, we demonstrate the impact of varying synchronization mechanisms and buffering schemes on the exposed parallelism using different modeling styles of a DNN. We measure the performance of aggressive out-of-order parallel discrete event simulation and analyze the available parallelism in the models. Our study suggests that increased parallel simulation performance indicates better models with higher amounts of parallelism exposed. \nSecond\, we explore the critical aspects of modeling and analysis of timing accuracy and memory contention. A major hurdle in tackling the memory bottleneck is the detection of memory contention late in the design cycle once detailed timed or cycle-accurate models are developed. A memory bottleneck detected at such a late stage can severely limit the available design choices or even require costly redesign. To explore new architectures prior to RTL implementation\, we propose a novel TLM-2.0 loosely-timed contention-aware (LT-CA) modeling style that offers high-speed simulation close to traditional loosely-timed (LT) models\, yet shows the same accuracy for memory contention as low level approximately-timed (AT) models. \nFinally\, we refine further the TLM-2.0 AT model by adding a cycle-accurate model of a memory subsystem. This model provides a higher timing accuracy for contention analysis\, hence it gives a more accurate estimation of the performance. We revise our LT-CA memory delay modeling to provide further accuracy comparable to the cycle-accurate TLM model of the shared memory subsystem. The high amount of contention on the shared memory suggests new processor architectures with local memories. \n\nShort Bio: \nEmad Arasteh is a Ph.D. candidate in Computer Engineering at University of California\, Irvine and a graduate researcher at the Center for Embedded and Cyber-physical Systems (CECS). He received the M.Sc. degree in Electronic Design from Lund University in Sweden. His current research interests include system-level modeling and design of embedded systems\, scalable memory system design\, and massively-parallel processor architecture. Previously\, he worked as a hardware and software engineer at semiconductor companies in Sweden and USA including Ericsson\, Canon (Axis Communications) and Samsung.
URL:https://www.cecs.uci.edu/event/transaction-level-modeling-of-deep-neural-networks-for-efficient-parallelism-and-memory-accuracy/
LOCATION:EH 3206\, Engineering Hall University of California\, Irve\, Irvine\, CA\, 92697\, United States
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220707T140000
DTEND;TZID=America/Los_Angeles:20220707T150000
DTSTAMP:20231011T032340Z
CREATED:20231011T032340Z
LAST-MODIFIED:20231011T032340Z
UID:14134-1657202400-1657206000@www.cecs.uci.edu
SUMMARY:"Anti-virus hardware: Applications in Embedded\, Automotive and Power Systems Security"
DESCRIPTION:Speaker: Kanad Basu\nDate and Time: Tuesday\, June 7\, 2:00 pm \nLocation: Zoom https://uci.zoom.us/j/97807443602 \nAbstract: \nAnti-virus software (AVS) tools are used to detect Malware in a system. However\, software-based AVS are vulnerable to attacks. A malicious entity can exploit these vulnerabilities to subvert the AVS. Recently\, hardware components such as Hardware Performance Counters (HPC) have been used for Malware detection\, in the form of Anti-virus Hardware (AVH). In this talk\, we will discuss HPC-based AVHs for improving embedded security and privacy. Furthermore\, we will discuss the application of HPCs in security cyber physical systems (CPS)\, namely automotive and microgrid systems. Subsequently\, we will discuss their pitfalls. Finally\, we will present PREEMPT\, a zero overhead\, high-accuracy and low-latency technique to detect Malware by re-purposing the embedded trace buffer (ETB)\, a debug hardware component available in most modern processors.  PREEMPT combines these hardware-level observations with machine learning-based classifiers to preempt Malware before it can cause damage. We will conclude the talk with future research directions and challenges. \nBiography: \nKanad Basu received his Ph.D. from the department of Computer and Information Science and Engineering\, University of Florida. His thesis was focused on improving signal observability for post-silicon validation. Post-PhD\, Kanad worked in various semiconductor companies like IBM and Synopsys. During his PhD days\, Kanad interned at Intel. Currently\, Kanad is an Assistant Professor at the Electrical and Computer Engineering Department of the University of Texas at Dallas\, where he leads the Trustworthy and Intelligent Embedded Systems (TIES) lab. Prior to this\, Kanad was an Assistant Research Professor at the Electrical and Computer Engineering Department of NYU. He has authored 1 book\, 2 US patents\, 2 book chapters and several peer reviewed journal and conference articles. His research is supported by SRC\, NSF\, DARPA and Ford Motors. Kanad was awarded the ”Best Paper Award” at the International Conference on VLSI Design 2011 and an honorable mention award at the same conference in 2021. Several News agencies have covered his research including NBC Austin and CBS Dallas-Fort Worth. Kanad’s current research interests are hardware and systems security as well as Deep learning hardware. \nHosted By: Prof. Nikil Dutt \n 
URL:https://www.cecs.uci.edu/event/anti-virus-hardware-applications-in-embedded-automotive-and-power-systems-security/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220715T100000
DTEND;TZID=America/Los_Angeles:20220715T110000
DTSTAMP:20231011T032348Z
CREATED:20231011T032346Z
LAST-MODIFIED:20231011T032348Z
UID:14137-1657879200-1657882800@www.cecs.uci.edu
SUMMARY:"Electric Power to the People: Secure & Resilient Cyber-Physical Systems in the Age of Renewable Energy"
DESCRIPTION:Speaker: Charalambos Konstantinou\nDate and Time: Friday\, July 15\, 10:00 am \nLocation: EH 2430 \nAbstract: \nRapid advancements in power electronics along with the increasing penetration of distributed energy resources (DERs) are transforming the electric power grids. Furthermore\, increasing types and number of loads and electric transportation are stressing the network. Overall\, the power system is facing unprecedented changes in operation and control as more and diverse sources and loads are being connected to this complex cyber-physical energy system. In light of this modernization\, and due to the growing number of Internet-of-things (IoT) connected controllers\, and the use of communication and control interfaces\, making cyber-physical energy systems resilient to high-impact\, low-probability cyber-physical adverse events\, such as cyber-attacks\, is a major priority for power grid operations. Such incidents\, if left unabated\, can intensify and elicit system dynamics instabilities\, eventually causing outages and system failures. In this talk\, we will give an overview of the research of the Secure Next Generation Resilient Systems (SENTRY) lab (sentry.kaust.edu.sa) at KAUST\, presenting different methodologies\, in the age of renewable energy\, contributing towards building secure and resilient cyber-physical grids. \nBiography: \nCharalambos Konstantinou is an Assistant Professor of Computer Science (CS) and Affiliate Professor of Electrical and Computer Engineering (ECE) at the Computer\, Electrical and Mathematical Science and Engineering Division (CEMSE) of King Abdullah University of Science and Technology (KAUST)\, Thuwal\, Saudi Arabia. He is the Principal Investigator of the SENTRY Lab (Secure Next Generation Resilient Systems – sentry.kaust.edu.sa) and a member of the Resilient Computing and Cybersecurity Center (RC3 – rc3.kaust.edu.sa) at KAUST. Before joining KAUST in 2021\, he was an Assistant Professor with the Center for Advanced Power Systems (CAPS) at Florida State University (FSU). His research interests are in secure\, trustworthy\, and resilient cyber-physical and embedded IoT systems. He is also interested in critical infrastructures security and resilience with special focus on smart grid technologies\, renewable energy integration\, and real-time simulation. He received a Ph.D. in Electrical Engineering from New York University (NYU)\, NY\, in 2018\, and an M.Eng. Degree in Electrical and Computer Engineering from National Technical University of Athens (NTUA)\, Greece\, in 2012. \nHosted By: Prof. Mohammad Al Faruque \n 
URL:https://www.cecs.uci.edu/event/electric-power-to-the-people-secure-resilient-cyber-physical-systems-in-the-age-of-renewable-energy/
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:20220802T140000
DTEND;TZID=America/Los_Angeles:20220802T150000
DTSTAMP:20231011T032348Z
CREATED:20231011T032346Z
LAST-MODIFIED:20231011T032348Z
UID:14138-1659448800-1659452400@www.cecs.uci.edu
SUMMARY:“Securing Hardware for Designing Trustworthy Systems”
DESCRIPTION:Speaker: Prabhat Mishra\nDate and Time: Tuesday\, August 2\, 2:00 pm \nLocation: DBH 4011 OR Zoom Link \nAbstract: \nSystem-on-Chip (SoC) is the brain behind computing and communication in a wide variety of embedded systems. Reusable hardware Intellectual Property (IP) based SoC design has emerged as a pervasive design practice in the industry to dramatically reduce SoC design and verification cost while meeting aggressive time-to-market constraints. Growing reliance on these pre-verified hardware IPs\, often gathered from untrusted third-party vendors\, severely affects the security and trustworthiness of computing platforms. It is crucial to evaluate the integrity and trustworthiness of third-party IPs for designing trustworthy systems. In this talk\, I will introduce a wide variety of hardware security vulnerabilities\, design-for-security solutions\, and possible attacks and countermeasures. I will briefly describe how the complementary abilities of simulation-based validation\, formal verification as well as side channel analysis can be effectively utilized for comprehensive SoC security and trust validation. \nBiography: \nPrabhat Mishra is a Professor in the Department of Computer and Information Science and Engineering and a UF Research Foundation Professor at the University of Florida. He received his Ph.D. in Computer Science from the University of California at Irvine in 2004. His research interests include embedded and cyber-physical systems\, hardware security and trust\, energy-aware computing\, system-on-chip validation\, machine learning\, and quantum computing. He has published 8 books\, 35 book chapters\, and more than 200 research articles in premier international journals and conferences. His research has been recognized by several awards including the NSF CAREER Award\, IBM Faculty Award\, three best paper awards\, and EDAA Outstanding Dissertation Award. He currently serves as an Associate Editor of IEEE Transactions on VLSI Systems and ACM Transactions on Embedded Computing Systems. He is an IEEE Fellow and an ACM Distinguished Scientist. \nHosted By: Prof. Nikil Dutt \n 
URL:https://www.cecs.uci.edu/event/securing-hardware-for-designing-trustworthy-systems/
LOCATION:DBH 4011\, Donald Bren Hall\, University of California\, Irvine\, Irvine\, CA\, 92617\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220810T110000
DTEND;TZID=America/Los_Angeles:20220810T120000
DTSTAMP:20231011T032348Z
CREATED:20231011T032346Z
LAST-MODIFIED:20231011T032348Z
UID:14139-1660129200-1660132800@www.cecs.uci.edu
SUMMARY:"DRAC: Designing RISC-V-based Accelerators for next generation Computers"
DESCRIPTION:Speaker: Miquel Moreto\nDate and Time: Wednesday\, August 10\, 11:00 am \nLocation: DBH 3011 OR Zoom Link \nAbstract: \nDesigning RISC-V-based Accelerators for next-generation Computers (DRAC) is a 3-year project (2019-2022) funded by the ERDF Operational Program of Catalonia 2014-2020. DRAC will design\, verify\, implement and fabricate a high-performance general purpose processor that will incorporate different accelerators based on the RISC-V technology\, with specific applications in the field of post-quantum security\, genomics\, and autonomous navigation. In this talk\, we will provide an overview of the main achievements in the DRAC project\, including the fabrication of Lagarto\, the first RISC-V processor developed in Spain. \nBiography: \nMiquel Moreto is a Ramon y Cajal Fellow at the Computer Architecture Departament (DAC) at the Universitat Politècnica de Catalunya (UPC)\, and he leads the High Performance Domain Specific Architectures team at the Barcelona Supercomputing Center (BSC). Miquel received his Ph.D. from UPC in 2010. After finishing the PhD\, he spent 15 months at the International Computer Science Institute (ICSI)\, affiliated with UC Berkeley\, as a Fulbright Postdoctoral Research Fellowship Holder during 2011 and 2012. In 2013\, he returned to Barcelona to work on multiple European projects (RoMoL\, Mont-Blanc\, EPI\, DeepHealth\, eProcessor) and industrial projects (Arm\, IBM\, Lenovo). In 2019\, he led the design and fabrication of Lagarto\, the first processor developed in Spain based on the open source RISC-V instruction set architecture. Currently\, he coordinates the DRAC project\, which is promoting the Lagarto initiative with new generations of the Lagarto processor and accelerators. \nHosted By: Prof. Veidenbaum \n 
URL:https://www.cecs.uci.edu/event/drac-designing-risc-v-based-accelerators-for-next-generation-computers/
LOCATION:DBH 3011\, Donald Bren Hall University of California\, Irve\, Irvine\, CA\, 92617\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220817T103000
DTEND;TZID=America/Los_Angeles:20220817T113000
DTSTAMP:20231011T032408Z
CREATED:20231011T032408Z
LAST-MODIFIED:20231011T032408Z
UID:14153-1660732200-1660735800@www.cecs.uci.edu
SUMMARY:An End-to-End Platform for Multi-Modal Machine Learning Affective Computing Services
DESCRIPTION:Name: Emad Kasaeyan Naeini \nChair: Nikil Dutt \nDate: August 17\, 2022 \nTime: 10:30 AM \nLocation: DBH 3011 \nCommittee: Amir Rahmani\, Fadi Kurdahi \nTitle:  An End-to-End Platform for Multi-Modal Machine Learning Affective Computing Services \nAbstract: \nSmart affective computing applications deliberately influence pain\, emotion and other affective phenomena\, and are fundamental to human experience\, health and well-being. Affective states such as pain\, stress\, and emotion are intrinsically subjective in nature\, posing challenges for objective assessment and quantification of such affective phenomena. Prior efforts in affective computing provide a foundation for the automated analysis of affective states\, but still face challenges in real-life\, everyday settings. We use pain as an exemplar for affective computing services. Pain assessment is critical for optimal treatment\, and is particularly important during periods of acute pain since inadequately treated acute pain increases the risk of chronic pain. Historically\, patients have served as the main assessment tool as they are able to self-report their pain presence and severity on standard\, but somewhat subjective pain scales. However\, it remains a challenge to assess pain from patients who cannot self-report. Automatic pain recognition systems could be crucial to facilitating accurate\, objective\, and real-time pain measurement\, that can in turn improve pain management and ultimately lead to improved patient outcomes. Using pain as an exemplar of smart affective computing services\, this thesis proposes the use of multimodal sensing of physiological and behavioral input data\, transmits the data to edge and/or cloud nodes\, and processes data with compute-intensive machine learning (ML) algorithms. The efficiency of ML-driven applications for affective computing (e.g.\, pain assessment) is greatly affected by run-time variations resulting from continuous stream of noisy input data\, unreliable network connections\, and the variations in computational requirements of ML algorithms. Towards that end\, this thesis evaluates and automates objective and real-time multimodal pain assessment algorithms\, and performs design space exploration of accuracy-performance-energy trade-offs and sense-compute co-optimization for multimodal machine learning (MMML) methods. The approach developed in this thesis could be used for the design and development of an end-to-end platform for multimodal machine learning affective computing services\, together with a thorough analysis of their roles in the prediction\, performance and energy in future studies. \nShort bio: \nEmad Kasaeyan Naeini is a Ph.D. candidate in Computer Engineering at the University of California\, Irvine. He received his M.Sc. degree in Electrical and Computer Engineering from the Department of Electrical Engineering and Computer Science at the University of California Irvine in 2020 and his B.Sc. in Electrical Engineering from Sharif University of Technology\, Tehran\, Iran\, in 2017. His research interests primarily include deep learning and machine learning\, signal processing\, healthcare Internet of Things (IoT)\, and healthcare data analysis.
URL:https://www.cecs.uci.edu/event/an-end-to-end-platform-for-multi-modal-machine-learning-affective-computing-services/
LOCATION:DBH 3011\, Donald Bren Hall University of California\, Irve\, Irvine\, CA\, 92617\, United States
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20220929T110000
DTEND;TZID=America/Los_Angeles:20220929T120000
DTSTAMP:20231011T032348Z
CREATED:20231011T032346Z
LAST-MODIFIED:20231011T032348Z
UID:14140-1664449200-1664452800@www.cecs.uci.edu
SUMMARY:"Design Automation and Computing based on Additive Printed Electronics”
DESCRIPTION:Speaker: Mehdi Tahoori\nDate and Time: Thursday\, September 29\, 11:00 am \nLocation: EH 2430 \nAbstract: \nPrinted electronics is an emerging and fast-growing field which can be used in many demanding and emerging application domains such as wearables\, smart sensors\, and Internet of Things (IoT). Unlike traditional computing and electronics domain which is mostly driven by performance characteristics\, printed and flexible electronics based on additive manufacturing processes are mainly associated with low fabrication costs and low energy. Printed electronics offer certain technological advantages over their silicon-based counterparts\, such as mechanical flexibility\, low process temperatures\, maskless and additive manufacturing possibilities. Electrolyte gated transistors (EGTs) using solution-processed inorganic materials which are fully printed using inkject printers at low temperatures are very promising to provide such solutions. However\, due to low device count\, large device dimension and high variabilities\, originated in low-cost additive manufacturing\, existing design automation and computing paradigms of digital VLSI are not applicable to printed electronics. This talk covers the technology\, process\, modeling\, fabrication\, design automation\, computing paradigms and security aspects of circuits and systems based on additive printed technologies. \nBiography: \nMehdi B. Tahoori is Professor and the Chair of Dependable Nano-Computing at Karlsruhe Institute of Technology (KIT)\, Germany. He received the B.S. degree in computer engineering from Sharif University of Technology\, Tehran\, Iran\, in 2000\, and the M.S. and Ph.D. degrees in electrical engineering from Stanford University\, Stanford\, CA\, in 2002 and 2003\, respectively. He is currently the deputy editor-in-chief of IEEE Design and Test Magazine. He was the editor-in-chief of Elsevier Microelectronic Reliability journal. He was the program chair of IEEE VLSI Test Symposium in (VTS) in 2021 and 2018\, and General Chair of IEEE European Test Symposium (ETS) in 2019. Prof. Tahoori was a recipient of the US National Science Foundation Early Faculty Development (CAREER) Award in 2008 and European Research Council (ERC) Advanced Grant in 2022. He has received a number of best paper nominations and awards at various conferences and journals. He is currently the chair of IEEE European Test Technologies Technical Council (eTTTC). He is a fellow of the IEEE. \nHosted by: Prof. Bozorgzadeh \n 
URL:https://www.cecs.uci.edu/event/design-automation-and-computing-based-on-additive-printed-electronics/
LOCATION:EH 2430\, Engineering Hall\, University of California\, Irvine\, Irvine\, CA\, 92697\, United States
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20221017
DTEND;VALUE=DATE:20221022
DTSTAMP:20231011T032348Z
CREATED:20231011T032346Z
LAST-MODIFIED:20231011T032348Z
UID:14141-1665964800-1666396799@www.cecs.uci.edu
SUMMARY:2022 Wolfgang Hillen Summer School
DESCRIPTION:Event: 2022 Wolfgang Hillen Summer School\, supported by BaCaTeC\nDate: October 17th-21st\, 2022 \nLocation: UCI \nView Details
URL:https://www.cecs.uci.edu/event/2022-wolfgang-hillen-summer-school/
CATEGORIES:Other Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193129Z
CREATED:20231031T193129Z
LAST-MODIFIED:20231031T193129Z
UID:15804-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Rozhin Yasaei Received iREDEFINE Fellowship 2022
DESCRIPTION:Assistant Professor Rozhin Yasaei received iREDEFINE Fellowship 2022 at the iREDEFINE ECE Workshop for her academic achievement as a woman and underrepresented minorities. Congrats Yasaei!
URL:https://www.cecs.uci.edu/event/rozhin-yasaei-received-iredefine-fellowship-2022/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193303Z
CREATED:20231031T193303Z
LAST-MODIFIED:20231031T193303Z
UID:15808-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Yasser Shoukry Won Category Winner Award
DESCRIPTION:Assistant Professor Yasser Shoukry won Category Winner Award at the International Verification of Neural Networks Competition 2022 for the top performing tool in the tllverifybench Benchmark of the VNN competition. Congrats Shoukry!
URL:https://www.cecs.uci.edu/event/yasser-shoukry-won-category-winner-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193354Z
CREATED:20231031T193354Z
LAST-MODIFIED:20231031T193354Z
UID:15812-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Ping-Xiang Chen Received J. Yang & Family Foundation Fellowship
DESCRIPTION:Ping-Xiang Chen received J. Yang & Family Foundation Fellowship for Chen’s work on building novel self-award and adaptive computing frameworks that support the efficiency\, reliability and scalability of autonomous systems. Congrats!
URL:https://www.cecs.uci.edu/event/ping-xiang-chen-received-j-yang-family-foundation-fellowship/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193444Z
CREATED:20231031T193444Z
LAST-MODIFIED:20231031T193444Z
UID:15816-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Mohammad Al Faruque Named IEEE Distinguished Lecturer
DESCRIPTION:Professor Mohammad Al Faruque was named IEEE Distinguished Lecturer for promoting the field of electronic design automation to the scientific community and the public at large. Congrats Prof. Al Faruque!
URL:https://www.cecs.uci.edu/event/mohammad-al-faruque-named-ieee-distinguished-lecturer/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193549Z
CREATED:20231031T193549Z
LAST-MODIFIED:20231031T193549Z
UID:15820-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Daniel Gajski Named Croatian Extraordinary Scientist
DESCRIPTION:Professor Daniel Gajski was named Croatian Extraordinary Scientist. Book titled “Croatian Extraordinary Scientists” features a chapter dedicated to Emeritus Prof. Gajski for his contributions to the embedded systems and computer science.
URL:https://www.cecs.uci.edu/event/daniel-gajski-named-croatian-extraordinary-scientist/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193847Z
CREATED:20231031T193847Z
LAST-MODIFIED:20231031T193847Z
UID:15824-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Rozhin Yasaei Named 2022 Rising Star in EECS
DESCRIPTION:Assistant Professor Rozhin Yasaei was named 2022 Rising Star in EECS. Launched in 2012 by MIT\, Rising Stars in EECS is an intensive workshop for graduate students and postdocs with historically marginalized or underrepresented genders who are interested in pursuing academic careers in electrical engineering & computer science\, and AI. Congrats Yasaei!
URL:https://www.cecs.uci.edu/event/rozhin-yasaei-named-2022-rising-star-in-eecs/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T193949Z
CREATED:20231031T193949Z
LAST-MODIFIED:20231031T193949Z
UID:15828-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Payam Heydari Won Distinguished Educator Award
DESCRIPTION:Professor Payam Heydari received the Distinguished Educator Award by the IEEE Society for his outstanding achievements as an educator\, mentor and role model for microwave engineers and engineering students. Congrats Prof. Heydari!
URL:https://www.cecs.uci.edu/event/payam-heydari-won-distinguished-educator-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T194126Z
CREATED:20231031T194126Z
LAST-MODIFIED:20231031T194126Z
UID:15832-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Qi Alfred Chen Received CAREER Award
DESCRIPTION:Assistant Professor Qi Alfred Chen received CAREER Award from the National Science Foundation for his research on securing the AI stack in autonomous CPS under physical layer attacks. Congrats Prof. Chen!
URL:https://www.cecs.uci.edu/event/qi-alfred-chen-received-career-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T194222Z
CREATED:20231031T194222Z
LAST-MODIFIED:20231031T194222Z
UID:15836-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Payam Heydari Named NAI Fellow
DESCRIPTION:Professor Payam Heydari was named a National Academy of Inventor Fellow for being a prolific creator of cutting-edge microelectronics technologies. Congrats Prof. Heydari!
URL:https://www.cecs.uci.edu/event/payam-heydari-named-nai-fellow/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T194337Z
CREATED:20231031T194337Z
LAST-MODIFIED:20231031T194337Z
UID:15840-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Anomadarshi Barua Won Distinguished Paper Award at ACSAC 2022
DESCRIPTION:Assistant Professor Anomadarshi Barua won Distinguished Paper Award at Annual Computer Security applications Conference (ACSAC) 2022 for project title: “Bayesian Estimation Based .bss Imposter Attack on Industrial Control Systems.” Congrats Prof. Barua!
URL:https://www.cecs.uci.edu/event/anomadarshi-barua-won-distinguished-paper-award-at-acsac-2022/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T194508Z
CREATED:20231031T194456Z
LAST-MODIFIED:20231031T194508Z
UID:15844-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Panyang Chen Won MECPS Best Project Award
DESCRIPTION:Panyang Chen won MECPS Best Project Award at the MECPS Symposium for project title: “Edith Wearable Device.” Congrats Chen and team!
URL:https://www.cecs.uci.edu/event/panyang-chen-won-mecps-best-project-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221031T080000
DTEND;TZID=America/Los_Angeles:20221031T170000
DTSTAMP:20231031T194626Z
CREATED:20231031T194626Z
LAST-MODIFIED:20231031T194626Z
UID:15849-1667203200-1667235600@www.cecs.uci.edu
SUMMARY:Sina Shahhosseini Won Best Paper Award at ISQED 2022
DESCRIPTION:Sina Shahhosseini won Best Paper Award at 2022 International Symposium on Quality Electronic Design (ISQED) for project title: “Hybrid Learning for Orchestrating Deep Learning Inference in Multi-user Edge-cloud Networks.” Congrats Shahhosseini!
URL:https://www.cecs.uci.edu/event/sina-shahhosseini-won-best-paper-award-at-isqed-2022/
CATEGORIES:Awards
END:VEVENT
END:VCALENDAR