BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CECS - ECPv6.18.4//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CECS
X-ORIGINAL-URL:https://www.cecs.uci.edu
X-WR-CALDESC:Events for CECS
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20170312T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20171105T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20180311T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20181104T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20190310T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20191103T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20200308T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20201101T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180606T150000
DTEND;TZID=America/Los_Angeles:20180606T160000
DTSTAMP:20231011T190742Z
CREATED:20231011T190742Z
LAST-MODIFIED:20231011T190742Z
UID:14529-1528297200-1528300800@www.cecs.uci.edu
SUMMARY:Reliable and Energy Efficient Battery-Powered Cyber-Physical Systems
DESCRIPTION:Name: Korosh Vatanparvar\nDate: Wednesday\, May 30th \nTime: 3:00 — 5:00 PM \nLocation: Calit2 3008 \nCommittee: Professor Prof. Mohammad Al Faruque (Chair) \nAbstract: \nCyber-Physical Systems (CPS) were presented as a solution to multidisciplinary integration and control in embedded systems. They provide seamless interactions between cyber and physical domains\, enabling more intelligent and complicated control applications. However\, CPS face the challenges of reliability and energy efficiency since they mainly rely on batteries for power supply. \nWe investigate these issues with Electric Vehicles (EV) which are common battery-powered CPS. EV were introduced as a mean of transportation to address environmental problems like air and noise pollution. However\, their stringent design constraints\, especially on battery packs\, create challenges of limited driving range and battery lifetime for daily drivers and manufacturers. Design automation community has been addressing these by developing more efficient and dependable devices and control methodologies. Our contributions in this thesis will embrace: \n1) novel machine learning and physics-based modeling techniques to capture CPS dynamics more accurately; 2) unique optimization problem formulations to make optimal control decisions; and 3)intelligent control methodologies that leverage the modeling and interaction within CPS to achieve reliable and efficient operation. These contributions are applied to the systems in EV such as navigation system\, climate control\, and battery management system. Our objectives are to further extend the EV driving range and prolong the battery lifetime while maintaining similar driving experience and comfort for passengers. \n 
URL:https://www.cecs.uci.edu/event/reliable-and-energy-efficient-battery-powered-cyber-physical-systems/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180607T150000
DTEND;TZID=America/Los_Angeles:20180607T160000
DTSTAMP:20231011T190742Z
CREATED:20231011T190742Z
LAST-MODIFIED:20231011T190742Z
UID:14530-1528383600-1528387200@www.cecs.uci.edu
SUMMARY:Modeling and Co-Design of Multi-domain Cyber-Physical Systems
DESCRIPTION:Name: Jiang Wan \nDate: Friday\, June 1 \nTime: 3:00 — 5:00 PM \nLocation: EH 3206 \nCommittee: Fadi Kurdahi (Chair)\, Mohammad Al Faruque\, Rainer Doemer \nAbstract: \nCyber-Physical Systems (CPS) are integration of computation and physical processes connected through networks. The high complexity of cross-domain engineering in combination with the pressure for system innovation\, higher quality\, time-to-market\, and budget constraints make it imperative for engineers to use integrated engineering methods and tools for CPS design. However\, existing computer-based engineering tools are mainly focused on a particular domain and therefore it is challenging to perform system-level analysis for CPS due to the difficulty of knowledge integration from different domains. This thesis studies the problem in the modeling of cross-domain CPS. Problems in the modeling of both functional and non-functional requirements during CPS design are explored and a functional model-based approach is proposed for high level CPS modeling. Moreover\, targeting the security requirement in CPS\, which is one of the key non-functional requirements in CPS\, physics-based models and solutions are proposed in this thesis. \n 
URL:https://www.cecs.uci.edu/event/modeling-and-co-design-of-multi-domain-cyber-physical-systems/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180702T150000
DTEND;TZID=America/Los_Angeles:20180702T160000
DTSTAMP:20231011T190742Z
CREATED:20231011T190742Z
LAST-MODIFIED:20231011T190742Z
UID:14531-1530543600-1530547200@www.cecs.uci.edu
SUMMARY:Kasra Moazzemi receives 2nd place at SIGDA PhD Forum
DESCRIPTION:The Ph.D. Forum at the Design Automation Conference is a poster session co-sponsored by both ACM SIGDA and IEEE CEDA for Ph.D. students to present and discuss their dissertation research with people in the EDA community. It has become one of the premier forums for Ph.D. students in design automation to get feedback on their research and for industry to see academic work in progress: hundreds of people attend the forums. Participation in the forum is competitive with the acceptance rate around 30%.\nKasra Moazzemi is a PhD candidate in CECS and ICS and is advised by Prof. Nikil Dutt. The title of his presentation was “Dynamic Resource Management for Many-core Systems using Supervisory Control.” Congratulations\, Kasra! \nhttps://cecs.uci.edu/files/2018/07/Kasra.pdf\nhttps://cecs.uci.edu/files/2018/07/KasraCrop.pdf\nhttps://cecs.uci.edu/files/2018/07/KasraCrop-1.pdf
URL:https://www.cecs.uci.edu/event/kasra-moazzemi-receives-2nd-place-at-sigda-phd-forum/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180712T150000
DTEND;TZID=America/Los_Angeles:20180712T160000
DTSTAMP:20231011T190742Z
CREATED:20231011T190742Z
LAST-MODIFIED:20231011T190742Z
UID:14532-1531407600-1531411200@www.cecs.uci.edu
SUMMARY:“Regional Coherence and Near Memory Acceleration in Distributed-Shared-Memory Architectures”
DESCRIPTION:Name: Andreas Herkersdorf\nDate and Time: Thursday\, July 26 at 11:00 a.m. – 12:00 p.m. \nLocation: Donald Bren Hall 3011 \nAbstract:  \nData access latencies and bandwidth bottlenecks frequently represent major limiting factors for the computational effectiveness of many-core processor architectures. This presentation introduces two\nconceptually complementary approaches to reduce the synchronization overheads for coherence\nmaintenance and to improve the locality between computing resources and data: Region-based cache\ncoherence and near memory acceleration. \nA 2D array of compute tiles with multiple\, heterogeneous RISC cores\, two levels of caches and a tile-local\nSRAM memory serves as reference processing platform. These compute tiles\, various I/O tiles and a globally shared DDR SDRAM memory tile are interconnected by a meshed Network on Chip (NoC) with support for multiple quality of service levels. Overall\, this processing architecture follows a distributed-\nshared-memory model. The limited degree of parallelism in many embedded computing applications\nalso bounds the number of compute tiles possibly sharing associated data structures. Therefore\, we favor region-based cache coherence (RBCC) among a limited number of compute tiles over global coherence approaches. Coherence regions are dynamically configured at runtime and comprise a number of arbitrary (adjacent or non-adjacent) compute tiles which are interconnected through regular NoC channels for the exchange of coherency protocol messages. We will show that region-based coherence allows maintaining substantially smaller coherence directories (e.g.\, by approx. 40% reduced in size for 16 tiles systems with up to 4 tiles per region) and shorter sharer checking latencies than global coherence. RBCC increases the locally usable intra-tile shared SRAM memories and may reduce execution times of sample video processing applications by 30% in comparison to message passing based parallelization. However\, the benefits of RBCC may strongly depend on the task and data placement among tiles in the coherency region which can affect performance by up to an order of magnitude. Near memory processing using near memory accelerators (NMA) positions processing resources for specific data manipulations as close as possible to the data memory for the benefit of shortening access latencies and increasing compute efficiency. \nBiography: \nAndreas Herkersdorf is a professor in the Department of Electrical and Computer Engineering and also\naffiliated to the Department of Informatics at Technical University of Munich (TUM). He received a Dr.\ndegree from ETH Zurich\, Switzerland\, in 1991. Between 1988 and 2003\, he has been in technical and\nmanagement positions with the IBM Research Laboratory in Rüschlikon\, Switzerland.\nSince 2003\, Dr. Herkersdorf leads the Chair of Integrated Systems at TUM. He is a senior member of the\nIEEE\, member of the DFG (German Research Foundation) Review Board and serves as editor for Springer and De Gruyter journals for design automation and information technology. His research interests include application-specific multi-processor architectures\, IP network processing\, Network on Chip and self-adaptive fault-tolerant computing.
URL:https://www.cecs.uci.edu/event/regional-coherence-and-near-memory-acceleration-in-distributed-shared-memory-architectures/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180712T150000
DTEND;TZID=America/Los_Angeles:20180712T160000
DTSTAMP:20231011T190742Z
CREATED:20231011T190742Z
LAST-MODIFIED:20231011T190742Z
UID:14533-1531407600-1531411200@www.cecs.uci.edu
SUMMARY:"Accurate and Stable CPU Power Modelling and Run-Time System Management"
DESCRIPTION:Name: Matthew Walker\nDate and Time: Friday\, July 27 at 11:00 a.m. – 12:00 p.m. \nLocation: Donald Bren Hall 4011 \nAbstract:  \nModern processors must provide an ever-increasing level of performance and are therefore including\nhigher numbers of Heterogeneous Multi-Processing (HMP) units. Intelligent run-time control of performance and power consumption is required to extend battery-life in mobile systems\, reduce energy and cooling costs in data centres\, and increase peak performance while respecting thermal and power constraints. Accurate online power estimation is essential in guiding run-time power management mechanisms and energy-aware scheduling decisions.\n\nIn this talk Matt will share his experience with CPU modelling and run-time management\, and present three open-source software tools for developing power models on mobile devices (http://www.powmon.ecs.soton.ac.uk)\, calibrating performance and energy models in the gem5 simulation framework (http://gemstone.ecs.soton.ac.uk)\, and developing run-time management algorithms (https://github.com/PRiME-project/PRiME-Framework/).\nBiography: \nMatthew J. Walker received his M.Eng. degree in Electronic Engineering (Hons) from the University of Southampton\, UK\, in 2013. In 2016 he worked on implementing non-volatile memory technologies in mobile systems at Intel Labs\, CA\, and has also completed two internships at Arm\, UK\, in 2015 and 2018. He is currently in his fourth year of his PhD at the University of Southampton researching CPU modelling techniques and run-time management approaches.
URL:https://www.cecs.uci.edu/event/accurate-and-stable-cpu-power-modelling-and-run-time-system-management/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180712T150000
DTEND;TZID=America/Los_Angeles:20180712T160000
DTSTAMP:20231011T190805Z
CREATED:20231011T190805Z
LAST-MODIFIED:20231011T190805Z
UID:14534-1531407600-1531411200@www.cecs.uci.edu
SUMMARY:"Sensors" Innovation at Intersections"
DESCRIPTION:Name: Khaled Salama\nDate and Time: Friday\, August 3 at 10:00 a.m. – 11:00 a.m. \nLocation: Engineering Hall 2430 \nAbstract:  \n\nEnergy efficiency is a key requirement for wireless sensor nodes\, biomedical implants\, and wearable devices. The energy consumption of the sensor node needs to be minimized to avoid battery replacement\, or even better\, to enable the device to survive on energy harvested from the ambient. Capacitive sensors do not consume static power; thus\, they are attractive from an energy efficiency perspective. In addition\, they can be employed in a wide range of sensing applications\, such as pressure\, humidity\, biological\, and chemical sensing. We will provide a summary of various sensors developed under the KAUST sensors initiative a consortium of 9 universities (KAUST\, MIT\, UCLA\, GATECH\, MIT\, UCLA\, Brown University\, Georgia Tech\, TU Delft\, Swansea University\, the University of Regensburg and the Australian Institute of Marine Science (AIMS). \n\nBiography: \nKhaled N. Salama received the B.S. degree from the Department Electronics and Communications\, Cairo University\, Cairo\, Egypt\, in 1997\, and the M.S. and Ph.D. degrees from the Department of Electrical Engineering\, Stanford University\, Stanford\, CA\, USA\, in 2000 and 2005\, respectively. He was an Assistant Professor at Rensselaer Polytechnic Institute\, NY\, USA\, between 2005 and 2009. He joined King Abdullah University of Science and Technology (KAUST) in January 2009\, where he is now a professor\, and was the founding Program Chair until August 2011. His work on CMOS sensors for molecular detection has been funded by the National Institutes of Health (NIH) and the Defense Advanced Research Projects Agency (DARPA)\, awarded the Stanford–Berkeley Innovators Challenge Award in biological sciences and was acquired by Lumina Inc. He is the author of 200 papers and 14 US patents on low-power mixed-signal circuits for intelligent fully integrated sensors and neuromorphic circuits using memristor devices.
URL:https://www.cecs.uci.edu/event/sensors-innovation-at-intersections/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180712T150000
DTEND;TZID=America/Los_Angeles:20180712T160000
DTSTAMP:20231011T190813Z
CREATED:20231011T190808Z
LAST-MODIFIED:20231011T190813Z
UID:14539-1531407600-1531411200@www.cecs.uci.edu
SUMMARY:"Sensors" Innovation at Intersections"
DESCRIPTION:Name: Khaled Salama\nDate and Time: Friday\, August 3 at 10:00 a.m. – 11:00 a.m. \nLocation: Engineering Hall 2430 \nAbstract:  \n\nEnergy efficiency is a key requirement for wireless sensor nodes\, biomedical implants\, and wearable devices. The energy consumption of the sensor node needs to be minimized to avoid battery replacement\, or even better\, to enable the device to survive on energy harvested from the ambient. Capacitive sensors do not consume static power; thus\, they are attractive from an energy efficiency perspective. In addition\, they can be employed in a wide range of sensing applications\, such as pressure\, humidity\, biological\, and chemical sensing. We will provide a summary of various sensors developed under the KAUST sensors initiative a consortium of 9 universities (KAUST\, MIT\, UCLA\, GATECH\, MIT\, UCLA\, Brown University\, Georgia Tech\, TU Delft\, Swansea University\, the University of Regensburg and the Australian Institute of Marine Science (AIMS). \n\nBiography: \nKhaled N. Salama received the B.S. degree from the Department Electronics and Communications\, Cairo University\, Cairo\, Egypt\, in 1997\, and the M.S. and Ph.D. degrees from the Department of Electrical Engineering\, Stanford University\, Stanford\, CA\, USA\, in 2000 and 2005\, respectively. He was an Assistant Professor at Rensselaer Polytechnic Institute\, NY\, USA\, between 2005 and 2009. He joined King Abdullah University of Science and Technology (KAUST) in January 2009\, where he is now a professor\, and was the founding Program Chair until August 2011. His work on CMOS sensors for molecular detection has been funded by the National Institutes of Health (NIH) and the Defense Advanced Research Projects Agency (DARPA)\, awarded the Stanford–Berkeley Innovators Challenge Award in biological sciences and was acquired by Lumina Inc. He is the author of 200 papers and 14 US patents on low-power mixed-signal circuits for intelligent fully integrated sensors and neuromorphic circuits using memristor devices.
URL:https://www.cecs.uci.edu/event/sensors-innovation-at-intersections-2/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180719T150000
DTEND;TZID=America/Los_Angeles:20180719T160000
DTSTAMP:20231011T190813Z
CREATED:20231011T190806Z
LAST-MODIFIED:20231011T190813Z
UID:14535-1532012400-1532016000@www.cecs.uci.edu
SUMMARY:"Efficient Processing when Intelligence Moves to the Edge"
DESCRIPTION:Name: Tinoosh Mohsenin\nDate and Time: Friday\, July 20 at 10:00 a.m. – 11:00 a.m. \nLocation: Donald Bren Hall 4011 \nAbstract:  \n\nContinuous collection and processing of vast amounts of data is becoming more common with the advancement of wearable sensors\, Internet of Things (IoT) devices and cyber physical systems. Despite their potential significant impact\, intelligent mobile technologies face a number of challenges for use in daily life. These devices usually stream raw data to cloud computers for computation which leads to massive storage\, significant transmission power consumption\, real time constraints and privacy/security issues\, thus processing at the edge of sensors is becoming increasingly preferred. Processing these sensor-level data requires a variety of signal processing and machine learning tasks that come at the cost of high computational complexity and memory storage which is overwhelming for these light weight and battery constrained platforms. \nIn this talk I will present research solutions that enable efficient processing of machine learning tasks to improve energy efficiency and throughout without sacrificing application accuracy for wide deployment of embedded/edge processing. First\, I present DeepMatter a scalable framework across algorithms\, architectures and hardware to design an embedded Deep Neural Net (DNN) accelerator. DeepMatter takes any number of raw sensor data for variety of applications and classifies the events within 92% accuracy and consumes very low power. Next I present two programmable domain-specific manycore accelerators namely PENC and BinMACthat achieve energy and speed efficiencies comparable to application-specific custom hardware through data-level and task level parallelization as well as customization of instruction-sets per-core and near-memory computing. I will show the efficiency of DeepMatter as well as PENC and BinMAC solutions for several application domains including multi-physiological processing for seizure and stress monitoring\, tongue drive assistive device\, air quality monitoring andvision-based situational awareness. The solutions derived at the intersection of algorithms\, architectures and implementation allow designers to rapidly prototype and deploy the next generation of sophisticated and intelligent systems for efficient edge processing in extreme environments. \n\nBiography: \nTinoosh Mohsenin is an Assistant Professor in the Department of Computer Science and Electrical Engineering at University of Maryland Baltimore County\, where she directs Energy Efficient High Performance Computing (EEHPC) Lab. She received her PhD from University of California\, Davis in 2010 and M.S. degree from Rice University in 2004\, both in Electrical and Computer Engineering. Prof. Mohsenin’s research focus is on designing highly accurate and energy efficient embedded processors for machine learning\, signal processing and knowledge extraction techniques for autonomous systems\, wearable smart health monitoring\, and embedded big data computing. She has over 80 peer-reviewed journal and conference publications and is the recipient of NSF CAREER award in 2017\, the best paper award in the GLSVLSI conference in 2016\, and the best paper honorable award in ISCAS 2017 for developing domain-specific accelerators for biomedical\, deep learning and cognitive computing. She currently leads 8 research projects in her lab which are all funded by National Science Foundation (NSF)\, Army Research Lab (ARL)\, Northrop Grumman\, Boeing\, Nvidia and Xilinx. She has served as associate editor in IEEE Transactions on Circuits and Systems-I (TCAS-I) and IEEE Transactions on Biomedical Circuits and Systems (TBioCAS). She was the local arrangement co-chair for the 50th IEEE\nInternational Symposium on Circuits and Systems (ISCAS) in Baltimore. She has also served as technical program committee member of the IEEE International Solid-State Circuits Conference Student Research (ISSCC-SRP)\, IEEE Biomedical Circuits and Systems (BioCAS)\, IEEE International Symposium on Circuits and Systems (ISCAS)\, ACM Great Lakes Symposium on VLSI (GLSVLSI and IEEE International Symposium on Quality Electronic Design (ISQED) conferences. She also serves as secretary of IEEE P1890 on Error Correction Coding for Non-Volatile Memories.
URL:https://www.cecs.uci.edu/event/efficient-processing-when-intelligence-moves-to-the-edge/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180904T150000
DTEND;TZID=America/Los_Angeles:20180904T160000
DTSTAMP:20231011T190813Z
CREATED:20231011T190807Z
LAST-MODIFIED:20231011T190813Z
UID:14537-1536073200-1536076800@www.cecs.uci.edu
SUMMARY:“SAT-based Design Debugging and Its Application to Undergraduate Circuit Experiment”
DESCRIPTION:Name: Takeshi Matsumoto\nDate and Time: Friday\, September 7 at 11:00 a.m. – 12:00 p.m. \nLocation: Donald Bren Hall 3011 \nAbstract: \nAs VLSI designs are becoming larger and more complicated\, designers spend a larger amount of\ntime for verification and debug to detect bugs in designs and avoid them. Moreover\, some bugs may not be detected in the verification processes before fabrication and are only recognized by running an actual chip after fabrication. In post-silicon debugging\, it is not practical that a large part of the circuit is changed for fixing bugs\, since such large change requires designers to do time-consuming physical and timing design processes again. Usually\, more than a half of the verification time is spent for correcting the buggy portions of the designs rather than identifying them\, since debugging is much less automated than checking correctness of the designs. Thus\, automating and shortening the debugging processes is now one of the most important issues in VLSI designs. In this talk\, SAT-based design debugging methods in gate-level and behavior-level are introduced. In the methods\, debugging consists of two processes: locating the suspicious portions in the designs and correcting them through replacements with appropriate sets of gates. In the locating process\, designers try to find locations of bugs (or candidate locations) which should be the root cause of the bugs. Then\, they modify logic functions at those possibly buggy locations in the correcting process. Both processes can be solved by repeatedly solving Boolean satisfiability (SAT) problems by introducing programmable logic elements\, such as MUX (multiplexer) and/or LUT (look-up table)\, to the original designs under debugging. This talk gives the details of the theoretical aspect of those methods and experimental results on several circuits. In the last part of the talk\, a trial activity to apply the debugging methods to an undergraduate experiment\, where a simple 4-bit CPU is made on breadboard through six 90-minute classes\, is introduced.\nThis activity can be seen as an application example of state-of-the-art research results to education field. \nBiography: \nTakeshi Matsumoto is an Associate Professor in the Department of Electronics and Information\nEngineering at National Institute of Technology\, Ishikawa College\, Japan. He directs Integrated System Lab in the department. He received his M.S. and Ph.D. degrees in Electronic Engineering from the University of Tokyo\, Japan\, in 2005 and 2008\, respectively. The topic of his Ph.D. thesis is equivalence checking of system level design. From 2008 to 2013\, he has been a Research Associate of VLSI Design and Education Center\, the University of Tokyo. His research interests include formal verification of system-level designs\, automated debugging and debugging support for pre- and post-silicon circuits\, education and teaching materials on electric and electronic circuits. He received IPSJ Yamashita SIG Research Award in 2012 from Information Processing Society of Japan.
URL:https://www.cecs.uci.edu/event/sat-based-design-debugging-and-its-application-to-undergraduate-circuit-experiment/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181010T150000
DTEND;TZID=America/Los_Angeles:20181010T160000
DTSTAMP:20231011T190814Z
CREATED:20231011T190807Z
LAST-MODIFIED:20231011T190814Z
UID:14538-1539183600-1539187200@www.cecs.uci.edu
SUMMARY:"Security of Additive Manufacturing: New Frontiers"
DESCRIPTION:Name: Mark Yampolskiy\nDate and Time: Friday\, October 19 at 10:00 a.m. – 11:00 a.m. \nLocation: Engineering Hall 2430 \nAbstract: Additive Manufacturing (AM)\, a.k.a. 3D printing\, is a rapidly growing multibillion-dollar industry that is increasingly used to manufacture functional parts\, including components of safety critical systems in the aerospace\, automotive\, and other industries. However\, reliance on the IT infrastructure and the high degree of computerization of the manufacturing machines make AM susceptible to a variety of cyber and cyber-physical attacks. \nAM Security is a fairly new and highly inter-disciplinary field of research that aims to address the novel threats emerging for this manufacturing technology. This talk will first provide an introduction to the field. Focusing on AM sabotage\, one of the identified threat categories\, Dr. Mark Yampolskiy will then introduce emerging frontiers: sabotage of composite material parts\, AM forensics\, and detection of sabotage attacks via side-channel measurements. The talk will conclude with a summary of identified research gaps in the current state of the art. \nBiography: \nMark Yampolskiy received Ph.D. in Computer Science from Ludwig-Maximilians University of\nMunich\, Germany in 2009. He currently holds an Assistant Professor position at the University\nof South Alabama. Since his post-doctoral appointment at Vanderbilt University (2012-2013)\,\nMark Yampolskiy is performing research on Security of Cyber-Physical Systems (CPS). Mark\nYampolskiy was among the researchers who pioneered Security of Additive Manufacturing (AM\,\na.k.a. 3D Printing) around 2014. AM Security remains his major research focus\, and he is\ncurrently one of the leading experts in this field. His work is predominantly associated with two\nthreat categories\, sabotage of 3D-printed functional parts and theft of intellectual property. He\nhas numerous seminal publications in the field\, ranging from attacks on/with AM up to novel\napproaches for the detection of such attacks. \nAM Security is a highly interdisciplinary field of research. In order to address this challenge\,\nMark Yampolskiy actively collaborates with experts from different disciplines. His major\ncollaboration partners are affiliated with Lawrence Livermore National Laboratory (LLNL)\, Ben\nGurion University of the Negev (BGU) in Israel\, Singapore University of Technology and Design\n(SUTD)\, Auburn University (AU)\, and University of Tennessee at Chattanooga (UTC).
URL:https://www.cecs.uci.edu/event/security-of-additive-manufacturing-new-frontiers/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181016T150000
DTEND;TZID=America/Los_Angeles:20181016T160000
DTSTAMP:20231011T190904Z
CREATED:20231011T190859Z
LAST-MODIFIED:20231011T190904Z
UID:14566-1539702000-1539705600@www.cecs.uci.edu
SUMMARY:An Initial Study of Simple Approaches To Eliminating Out-of-Thin-Air Results
DESCRIPTION:Name: Peizhao Ou\nChair: Prof. Brian Demsky \nDate: Tuesday October 16\, 2018 \nTime: 10am – 12pm \nLocation: CALIT2 Room 3008 \nTitle: An Initial Study of Simple Approaches To Eliminating Out-of-Thin-Air Results \nAbstract:\nEliminating so-called “out-of-thin-air” (OOTA) results is an open problem in many existing programming language memory models including Java\, C\, and C++.  OOTA behaviors are problematic in that they break both formal and informal modular reasoning about program behavior. In spite of many years of research\nefforts\, defining memory model semantics that are easily understood\, allow existing optimizations\, and forbid OOTA results remains an open problem. This thesis explores two simple solutions to this problem that forbid OOTA results. The first solution is targeted towards Java-like languages in which all memory operations may create OOTA executions\, and the second solution is targeted towards C/C++-like memory models in which racing operations are explicitly labeled as atomic operations. Our solutions provide a per-candidate execution criterion that makes it possible to examine a single execution and determine whether the memory model permits the execution. We implemented and evaluated both solutions in the LLVM compiler framework. Our results show that on an ARMv8 processor the first solution has an average overhead of 3.1% and a maximum overhead of 17.6% on the SPEC CPU2006 C/C++ benchmarks\, and that the second solution has no overhead on average and a maximum overhead of 6.3% on 43 concurrent data structures.  The results indicate that these simple approaches to eliminating out-of-thin-air behaviors deserve further consideration.
URL:https://www.cecs.uci.edu/event/an-initial-study-of-simple-approaches-to-eliminating-out-of-thin-air-results/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181030T150000
DTEND;TZID=America/Los_Angeles:20181030T160000
DTSTAMP:20231011T190813Z
CREATED:20231011T190807Z
LAST-MODIFIED:20231011T190813Z
UID:14536-1540911600-1540915200@www.cecs.uci.edu
SUMMARY:"Plasmonic Wave Computing: Concepts and Potential"
DESCRIPTION:Name: Francky Catthoor\nDate and Time: Wednesday\, October 31 at 11:00 a.m. – 12:00 p.m. \nLocation: Engineering Hall 2430 \nAbstract:  \n\nSeveral beyond CMOS computing directions are being explored given that the CMOS scaling roadmap faces increasing challenges. Any alternative is however facing strong competition from the extremely optimized CMOS roadmap. One of the potential directions which can complement CMOS in an area where it is less good is highly parallel “wave-type” computing. In this talk I will discuss some of the promising concepts and their potential but also challenges. \n\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 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.
URL:https://www.cecs.uci.edu/event/plasmonic-wave-computing-concepts-and-potential/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181031T080000
DTEND;TZID=America/Los_Angeles:20181031T170000
DTSTAMP:20231031T183144Z
CREATED:20231031T183144Z
LAST-MODIFIED:20231031T183144Z
UID:15692-1540972800-1541005200@www.cecs.uci.edu
SUMMARY:Delaram Amiri Won First Place at IEEE SOCC 2023 Student Design Contest
DESCRIPTION:Delaram Amiri won first place at the 16th International System on Chip Conference Student Design Contest with poster presentation on “Energy Efficient Edge Computing in Healthcare IoT.” Congrats Amiri!
URL:https://www.cecs.uci.edu/event/delaram-amiri-won-first-place-at-ieee-socc-2023-student-design-contest/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181031T080000
DTEND;TZID=America/Los_Angeles:20181031T170000
DTSTAMP:20231031T183342Z
CREATED:20231031T183328Z
LAST-MODIFIED:20231031T183342Z
UID:15696-1540972800-1541005200@www.cecs.uci.edu
SUMMARY:Mohammad Al Faruque Won IEEE Technical Committee on Cyber-Physical Systems Early Career Award
DESCRIPTION:Mohammad Al Faruque won the IEEE Technical Committee on Cyber-Physical Systems Early Career Award to honor his work over the past eight years in the areas of energy-efficient and security-award design automation methodologies for cyber-physical systems. Congrats Prof. Al Faruque!
URL:https://www.cecs.uci.edu/event/mohammad-al-faruque-won-ieee-technical-committee-on-cyber-physical-systems-early-career-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181101T150000
DTEND;TZID=America/Los_Angeles:20181101T160000
DTSTAMP:20231011T190843Z
CREATED:20231011T190827Z
LAST-MODIFIED:20231011T190843Z
UID:14545-1541084400-1541088000@www.cecs.uci.edu
SUMMARY:Accelerated Computing for Edge-Centric IoT
DESCRIPTION:Name: Tulika Mitra\nDate and Time: Monday\, November 5 at 2:00 p.m. – 3:00 p.m. \nLocation: Donald Bren Hall 3011 \nAbstract: Internet of Things (IoT)\, an ever-growing network of billions of devices embedded within physical objects\, is revolutionizing our daily life. The IoT devices in the edge are primarily responsible only for collecting and communicating the data to the cloud\, where the computationally intensive data analytics takes place. However\, the data privacy and the connectivity issues—in conjunction with the fast real-time response requirement of certain IoT applications—call for smart edge devices that should be able to support privacy-preserving\, time-sensitive computation for machine intelligence on-site. In this talk\, I will present the computation challenges in edge-centric IoT and introduce hardware-software co-designed approaches to overcome these challenges. I will discuss the  design of configurable\, customizable accelerators that are completely software programmable and can be universally deployed across diverse domains to speed up computation and realize the edge analytics vision at ultra-low power budget. I will also demonstrate the potential to achieve low-power\, real-time intelligence on the IoT edge devices via collaborating computing that engages all the on-chip heterogeneous compute elements (CPU\, GPU\, reconfigurable computing\, and accelerators) in a synergistic fashion though sophisticated compile- and runtime strategies. \nBiography: Tulika Mitra is a Professor of Computer Science at School of Computing\, National University of Singapore (NUS). Her research interests span various aspects of the design automation of embedded real-time systems with particular emphasis on low-power computing\, heterogeneous computing\, application-specific processors\, and software timing analysis/optimizations. She has authored over hundred and fifty scientific publications in leading international journals and conferences and holds multiple US patents. Her research has been recognized by best paper award and nominations in leading conferences. She is the recipient of the Indian Institute of Science Outstanding Woman Researcher Award and is an IEEE Distinguished Visitor.  Prof. Mitra currently serves as Senior Associate Editor of the ACM Transactions on Embedded Computing Systems\, Deputy Editor-in-Chief of IEEE Embedded Systems Letters\, and Associate Editor of IEEE Design & Test Magazine. She has served as Associate Editor of IEEE TCAD and organizing/program committee member of almost all major conferences in embedded systems\, real-time systems\, and electronic design automation including program chair of EMOSFT and CASES.
URL:https://www.cecs.uci.edu/event/accelerated-computing-for-edge-centric-iot/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181128T150000
DTEND;TZID=America/Los_Angeles:20181128T160000
DTSTAMP:20231011T190843Z
CREATED:20231011T190827Z
LAST-MODIFIED:20231011T190843Z
UID:14546-1543417200-1543420800@www.cecs.uci.edu
SUMMARY:Control System Design Automation Using Reinforcement Learning
DESCRIPTION:Title: “Control System Design Automation Using Reinforcement Learning”\nName: Hamid Mirzaei \nDate: Tuesday\, November 20\, 2018 \nTime: 1:00 p.m. \nLocation: Donald Bren Hall 3011 \nCommittee: Professor Tony Givargis (Chair)\, Professor Eli Bozorgzadeh\, Professor Ian Harris \nAbstract: \n\n\n\n\n\n\n\n\n\nConventional control theory has been used in many application domains with great success in the past decades. However\, novel solutions are required to cope with the challenges arising from complex interaction of fast growing cyber and physical systems. Specifically\, integration of classical control methods with Cyber-Physical System (CPS) design tools is a non-trivial task since those methods have been developed to be used by human expert and are not intended to be part of an automatic design tool. \n\n\n\n\n\n\n\n\n\n\n\n\nOn the other hand\, the control problems in emerging Cyber-Physical Systems\, such as intelligent transportation and autonomous driving\, cannot be addressed by conventional control methods due to the high level of uncertainty\, complex dynamic model requirements and operational and safety constraints.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nIn this dissertation\, a holistic CPS design approach is proposed in which the control algorithm is incorporated as a building block in the design tool. The proposed approach facilitates the inclusion of physical variability into the design process and reduces the parameter space to be explored. This has been done by adding constraints imposed by the control algorithm.\n\n\nFurthermore\, Reinforcement Learning (RL) as a replacement for convection control solutions are studied in the emerging domain of intelligent transportation systems. Specifically\, dynamic tolling assignments and autonomous intersection management are tackled by the state-of-the-art RL methods\, namely\, Trust Region Policy Optimization and Finite-Difference Gradient Descent. Additionally\, Q-learning is used to improve the performance of an embedded controller using a novel formulation in which cyber-system actions\, such as changing control sampling time\, is combined with the physical action set of the RL agent. Using the proposed approach\, it is shown that the power consumption and computational overhead of the embedded control can be improved.\n\nFinally\, to address the current lack of available physical benchmarks\, an open physical environment benchmarking framework is introduced. In the proposed framework\, various components of a physical environment are captured in a unified repository to enable researchers to define and share standard benchmarks that can be used to evaluate different reinforcement algorithms. They can also share the realized environments via the cloud to enable other groups perform experiments on the actual physical environments instead of currently available simulation-based environments.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n 
URL:https://www.cecs.uci.edu/event/control-system-design-automation-using-reinforcement-learning/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190129T150000
DTEND;TZID=America/Los_Angeles:20190129T160000
DTSTAMP:20231011T190843Z
CREATED:20231011T190827Z
LAST-MODIFIED:20231011T190843Z
UID:14547-1548774000-1548777600@www.cecs.uci.edu
SUMMARY: Partial logic synthesis and its application to automatic generation of parallel/distributed algorithms
DESCRIPTION:Name: Masahiro Fujita\nDate and Time: Thursday\, January 14 at 3:00 p.m. \nLocation:Engineering Hall 3206 \nAbstract: In this talk first we review the partial logic synthesis problem and its associated\nalgorithm based on QBF (Quantified Boolean Formula) formulation. Partial logic synthesis\nis to generate appropriate sub-circuits for the missing portions in the target design so that\nthe entire circuit becomes equivalent to the specification which is separately given. Then\nwe show the problem to automatically generate distributed/parallel computing for the\ngiven specification can be defined as partial logic synthesis problem. Taking matrix-vector\nproduct computation as an example\, we show how theoretical optimum distributed/parallel\ncomputation can be automatically generated targeting many cores/chips which are\nconnected through a ring connection. \nBiography: Masahiro Fujita receivedh is Ph.D. in Information Engineering from the\nUniversity of Tokyo in 1985 on his work on model checking of hardware designs by using\nlogic programming languages. In 1985\, he joined Fujitsu as a researcher and started to\nwork on hardware automatic synthesis as well as formal verification methods and tools\,\nincluding enhancements of BDD/SAT-based techniques. Since March 2000\, he has been a\nprofessor at VLSI Design and Education Center of the University of Tokyo. He has been\ninvolved in a Japanese governmental research project for dependable system designs and\nhas developed a formal verifier for C programs that could be used for both hardware and\nembedded software designs. He has authored and co-authored 10 books\, and has more\nthan 200 publications.
URL:https://www.cecs.uci.edu/event/partial-logic-synthesis-and-its-application-to-automatic-generation-of-parallel-distributed-algorithms/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190227T150000
DTEND;TZID=America/Los_Angeles:20190227T160000
DTSTAMP:20231011T190843Z
CREATED:20231011T190828Z
LAST-MODIFIED:20231011T190843Z
UID:14548-1551279600-1551283200@www.cecs.uci.edu
SUMMARY:Cyber-Physical Systems Approach to Irrigation Systems
DESCRIPTION:Title: “Cyber-Physical Systems Approach to Irrigation Systems”\nName: Davit Hovhannisyan \nDate: March 5\, 2019 \nTime: 4:00PM \nLocation: EH 3206  (CECS conference room) \nCommittee:  Prof. Fadi Kurdahi (Chair)\, Prof. Ahmed Eltawil\, Prof. Mohammad Al Faruque \nAbstract: \nSemiconductor industry has successfully brought silicon technology to price point that it is accessible for application domains such as irrigation systems\, which wastefully utilizes 70% of all fresh water. Moreover\, worldwide fresh water resources will soon reach a deficit due to ever growing demand\, while the state of the art precision irrigation systems utilize sophisticated water delivery drip lines\, yet are only controlled at source by the gut of the end user. This work demonstrates that scientific foundation of cyber-physical systems can be used to design automated\, distributed and intelligent precision irrigation systems that improve irrigation efficiency. Thus\, this work explores and analyzes in depth the cross section of irrigation practices and cyber-physical systems knowledge to show a path toward a successful adaptation of silicon technology that solves one of the greatest challenges of the 21st century\, the fresh water scarcity. To that end\, this work presents contributions that complete a novel vision for next generation precision irrigation systems\, which can be grouped into three main thrusts: (1) circuit inspired models for irrigation system components and scheduling strategies by analogy method\, (2) CPS approach based (a) design methodology capable of comparing irrigation controllers\, (b) simulation tools and software for analyzing the distributed behavior of the specialized irrigation controllers\, (c) topology adaptation technique that utilizes multi-graphs to mine the hydro-wireless topology of the IoT controllers\, and (d) a distributed controller implementation with novel energy harvesting and low power support for irrigation controllers and sensors\, (3) overhead vision solutions for health and growth monitoring. The observations\, analysis and insight from experimental studies were in collaboration with Rancho California Water District\, growers and practitioners.
URL:https://www.cecs.uci.edu/event/cyber-physical-systems-approach-to-irrigation-systems/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190307T150000
DTEND;TZID=America/Los_Angeles:20190307T160000
DTSTAMP:20231011T190843Z
CREATED:20231011T190828Z
LAST-MODIFIED:20231011T190843Z
UID:14549-1551970800-1551974400@www.cecs.uci.edu
SUMMARY:"Poly-Logarithmic Side Channel Rank Estimation via Exponential Sampling"
DESCRIPTION:Name: Liron David\nDate and Time: Tuesday\, March 12 at 10:00 a.m. \nLocation: Engineering Hall 5204 \nAbstract: \nRank estimation is an important tool for a side-channel evaluations laboratories. It allows estimating the remaining security after an attack has been performed\, quantified as the time complexity and the memory consumption required to brute force the key given the leakages as probability distributions over d subkeys (usually key bytes). These estimations are particularly useful where the key is not reachable with exhaustive search. \nWe propose ESrank\, the first rank estimation algorithm that enjoys provable poly-logarithmic time- and space-complexity\, which also achieves excellent practical performance. Our main idea is to use exponential sampling to drastically reduce the algorithm’s complexity. Importantly\, ESrank is simple to build from scratch\, and requires no algorithmic tools beyond a sorting function. After rigorously bounding the accuracy\, time and space complexities\, we evaluated the performance of ESrank on a real SCA data corpus\, and compared it to the currently-best histogram-based algorithm. We show that ESrank gives excellent rank estimation (with roughly a 1-bit margin between lower and upper bounds)\, with a performance that is on-par with the Histogram algorithm: a run-time of under 1 second on a standard laptop using 6.5 MB RAM. \nBiography: \nLiron David is a Ph.D. candidate in Electrical Engineering at Tel-Aviv University under the supervision of Prof. Avishai Wool. She received her B.Sc. degree in Computer Science and Electrical and Electronics Engineering from Tel-Aviv University and her M.Sc. degree in Electrical Engineering from Tel-Aviv University. Liron has won the Weinstein award for excellence in studies in 2017 \,the Weinstein best paper prize in 2018 and the Tel-Aviv University excellence in teaching in 2018.
URL:https://www.cecs.uci.edu/event/poly-logarithmic-side-channel-rank-estimation-via-exponential-sampling/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190501T150000
DTEND;TZID=America/Los_Angeles:20190501T160000
DTSTAMP:20231011T190852Z
CREATED:20231011T190846Z
LAST-MODIFIED:20231011T190852Z
UID:14555-1556722800-1556726400@www.cecs.uci.edu
SUMMARY:"Safety Verification and Training for Learning-enabled Cyber-Physical Systems"
DESCRIPTION:Name: Jyotirmoy Vinay Deshmukh\nDate and Time: Tuesday\, May 14\, 2019 at 2:00 p.m. \nLocation: Donald Bren Hall 4011 \nAbstract: \nWith the increasing popularity of deep learning\, there have been several efforts to use neural network based controllers in cyber-physical system applications. However\, neural networks are equally well-known for their lack of interpretability\, explainability and verifiability. This is especially an issue for safety-critical cyber-physical systems such as unmanned aerial vehicles or autonomous ground vehicles. How can we verify that a neural network based controller will always keep the system safe? We look at a new verification approach based on automatically synthesizing a barrier certificate for the system to prove that: starting from a given set of initial conditions\, the system behavior can never reach an unsafe state. Barrier Certificates are essentially a generalization of inductive invariants for continuous dynamical systems\, and we will show how we can use nonlinear SMT solvers to establish the barrier certificate conditions. A more intriguing challenge is whether we can actually train neural networks to obey safety constraints. We will look at a new way of reward shaping in reinforcement learning that could help achieve this goal. \nBiography: \nJyotirmoy V. Deshmukh (Jyo) is an assistant professor in the Department of Computer Science in the Viterbi School of Engineering at the University of Southern California in Los Angeles\, USA. Before joining USC\, Jyo worked as a Principal Research Engineer in Toyota Motors North America R&D. He got his Ph.D. degree from the University of Texas at Austin and was a post-doctoral fellow at the University of Pennsylvania. Jyo’s research interest is in the broad area of formal methods. Currently\, Jyo is interested in using logic-based methods for machine learning\, and in techniques for the analysis\, design\, verification and synthesis of cyber-physical systems\, especially those that use AI-based perception\, control and planning algorithms.
URL:https://www.cecs.uci.edu/event/safety-verification-and-training-for-learning-enabled-cyber-physical-systems/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190522T150000
DTEND;TZID=America/Los_Angeles:20190522T160000
DTSTAMP:20231011T190852Z
CREATED:20231011T190846Z
LAST-MODIFIED:20231011T190852Z
UID:14556-1558537200-1558540800@www.cecs.uci.edu
SUMMARY:Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis
DESCRIPTION:Title: “Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis”\nName: Sujit Rokka Chhetri \nDate: May 20\, 2019 \nTime: 3:00 PM \nLocation: EH 5200 \nCommittee: Prof. Mohammad Al Faruque (Chair)\, Prof. Pramod Khargonekar\, Prof. Fadi Kurdahi \nAbstract: \nCyber-Physical System consists of the integration of computational components in the cyber-domain with the physical-domain processes. In cyber-domain\, embedded computers and networks monitor and control the physical processes\, and in the physical-domain the sensors and actuators aid in interacting with the physical world. This interaction between the cyber and physical domain brings unique modeling challenges one of which includes the integration of discrete models in cyber-domain with the continuous physical domain processes. However\, the same cyber-physical interaction also opens new opportunities for modeling. For example\, the information flow in the cyber-domain manifests physically in the form of energy flows in the physical domain. Some of these energy flows unintentionally provide information about the cyber-domain through the side-channels. \nIn this thesis\, the extensive analysis of the side-channels (such as acoustic\, magnetic\, thermal\, power and vibration) of the cyber-physical system is performed. Based on this analysis data-driven models are estimated. These models are then used to perform security vulnerability analysis (for confidentiality and integrity)\, whereby\, new attack models are explored.  Furthermore\, the data-driven models are also utilized to create a defensive mechanism to minimize the information leakage from the system and to detect attacks to the integrity of the system. The cyber-physical manufacturing systems are taken as use cases to demonstrate the applicability of the modeling approaches. \nFinally\, the side-channel analysis is also performed to aid in modeling digital twins of the cyber-physical systems. Specifically\, a novel methodology to utilize low-end sensors to analyze the side-channels and build the digital twins is proposed. These digital twins are used to capture the interaction between the cyber-domain and the physical domain of the manufacturing systems\, and aid in process quality inference and fault localization. Using side-channels these digital twins are kept up-to-date\, which is one of the fundamental requirements for building digital twins.
URL:https://www.cecs.uci.edu/event/data-driven-modeling-of-cyber-physical-systems-using-side-channel-analysis/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190703T150000
DTEND;TZID=America/Los_Angeles:20190703T160000
DTSTAMP:20231011T190852Z
CREATED:20231011T190846Z
LAST-MODIFIED:20231011T190852Z
UID:14557-1562166000-1562169600@www.cecs.uci.edu
SUMMARY:"Scalable Set-based Analysis for Verification of Cyber-Physical Systems”
DESCRIPTION:Name: Stanley Bak\nDate and Time: Tuesday\, July 9\, 2019 \nLocation: Engineering Hall 2430 \nAbstract: \nCyber-physical systems combine complex physics with complex software. Although these systems offer significant potential in fields such as smart grid design\, autonomous robotics and medical systems\, verification of CPS designs remains challenging. Model-based design permits simulations to be used to explore potential system behaviors\, but individual simulations do not provide full coverage of what the system can do. In particular\, simulations cannot guarantee the absence of unsafe behaviors\, which is unsettling as many CPS are safety-critical systems. \nThe goal of set-based analysis methods is to explore a system’s behaviors using sets of states\, rather than individual states. The usual downside of this approach is that set-based analysis methods are limited in scalability\, working only for very small models. This talk describes our recent process on improving the scalability of set-based reachability computation for LTI hybrid automaton models\, some of which can apply to very large systems (up to one billion continuous state variables!). Lastly\, we’ll discuss the significant overlap of techniques used for our scalable reachability analysis methods with set-based input/output analysis of neural networks. \nBiography: \nStanley Bak is a research computer scientist investigating the formal verification of cyber-physical systems. He strives to create scalable and automatic formal analysis methods for complex models with both ordinary differential equations and discrete behaviors. The ultimate goal is to make formal approaches applicable\, which demands developing new theory\, programming efficient tools and building experimental systems. \nStanley Bak received a Bachelor’s degree in Computer Science from Rensselaer Polytechnic Institute (RPI) in 2007 (summa cum laude)\, a Master’s degree in Computer Science from the University of Illinois at Urbana-Champaign (UIUC) in 2009\, and a PhD from UIUC in 2013. He received the Founders Award of Excellence for his undergraduate research at RPI in 2004\, the Debra and Ira Cohen Graduate Fellowship from UIUC twice\, in 2008 and 2009\, and was awarded the Science\, Mathematics and Research for Transformation (SMART) Scholarship from 2009 to 2013. Stanley worked as a research computer scientist for the Air Force Research Laboratory (AFRL) from 2013 to 2018\, both in the Information Directorate and the Aerospace Systems Directorate. Currently\, he helps run Safe Sky Analytics\, a small research consulting company working with the FAA and the Air Force.
URL:https://www.cecs.uci.edu/event/scalable-set-based-analysis-for-verification-of-cyber-physical-systems/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190806T150000
DTEND;TZID=America/Los_Angeles:20190806T160000
DTSTAMP:20231011T190852Z
CREATED:20231011T190846Z
LAST-MODIFIED:20231011T190852Z
UID:14558-1565103600-1565107200@www.cecs.uci.edu
SUMMARY:Low-Power Integrated Circuits For Biomedical Applications
DESCRIPTION:Title: “Low-Power Integrated Circuits For Biomedical Applications”\nName: Karimi Bidhendi\, Alireza \nChair: Professor Payam Heydari \nDate: August 6\, 2019 \nTime: 1 pm \nLocation: Calit2\,  Room 3008 \nAbstract: \nWith thousands new cases of spinal cord injury reported everyday\, many people suffer from paralysis and loss of sensation in both legs. Beside the healthcare costs\, such a state severely deteriorates a patients quality of life and may even lead to additional medical conditions. Therefore\, there is a growing need for cyber-physical systems to restore the walking ability through bypassing the damaged spinal cord. This goal can be achieved by monitoring and processing patient’s brain signals to enable brain-directed control of prosthetic legs. Among several existing methods to record brain signals\, electrocorticography (ECoG) has gained popularity due to being robust to motion artifacts\, having high spatial resolution and signal to noise ratio\, being moderately invasive and the possibility of chronic implantation of recording grids with no or minor scar tissue formation. The latest property is of particular importance for the whole system to be a viable fully implantable solution. Furthermore\, the implanted system has to operate independently with no or minimal need of external hardware (e.g. a bulky personal computer) to be individually and socially accepted. \nTo implement a fully implantable system\, low-power and miniaturized electronics are needed to reduce heat generation\, increase battery life-time and be minimally intrusive. These requirements indicate that many of the system’s components should be custom-designed to integrated as much functionality as possible in a given real estate. This thesis presents silicon tested prototypes of several building blocks for the envisioned system\, namely\, ultra low-power brain signal acquisition front-ends\, a low-power and inductorless MedRadio transceiver\, and a fast start-up crystal oscillator. Brain signal acquisition front-ends provide low noise amplification of weak ECoG biosignals. MedRadio transceiver enables communication between the implant and end effectors or base station (e.g. prosthetic legs or desktop computer). Crystal oscillators generate the reference signal for other system components such as analog to digital converters. Novel techniques to improve important performance parameters (power consumption\, low noise operation and interference resilience) have been introduced. Electrical\, in-vitro and in-vivo experimental measurements have verified the functionality and performance of each design.
URL:https://www.cecs.uci.edu/event/low-power-integrated-circuits-for-biomedical-applications/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190812T150000
DTEND;TZID=America/Los_Angeles:20190812T160000
DTSTAMP:20231011T190852Z
CREATED:20231011T190846Z
LAST-MODIFIED:20231011T190852Z
UID:14559-1565622000-1565625600@www.cecs.uci.edu
SUMMARY:Cooperative Power and Resource Management for Heterogeneous Mobile Architectures
DESCRIPTION:Name: Chenying Hsieh\n\nDate: Wednesday Aug 7\, 2019 \n\n\n\n\n\n\nTime: 2:00 pm\n\nLocation: Donald Bren Hall 4011\n\nCommittee: Nikil Dutt (Chair)\, Tony Givargis\, and Ardalan Amiri Sani\n\nTitle: Cooperative Power and Resource Management for Heterogeneous Mobile Architectures\n \nAbstract:\n\n\n\n\n\n\nHeterogeneous architectures have been ubiquitous in mobile system-on-chips (SoCs). The demand from different application domains such as games\, computer vision and machine learning which requires massive parallelism of computation has driven the integration of more accelerators into mobile SoCs to provide satisfactory performance energy-efficiently.These on-chip computing resources typically have their individual runtime systems including: (1) a software governor: continuously monitors hardware utilization and makes decisions of trade-off between performance and power consumption. (2) software stack: allows application developers to program the hardware for general purpose computation and perform memory management and profiling. As computation of mobile applications may demand all sorts of combinations of computing resources\, we identify two problems: (1) individual runtime can often lead to poor performance-power trade-off or inefficient utilization of computing resources. (2) existing approaches fail to schedule subprograms among different computing resources and further lose the opportunity to avoid resource contention to gain better performance.\n\nTo address these issues\, we propose a holistic approach to coordinate different runtime regrading application performance and energy efficiency in this dissertation. We first present MEMCOP\, a memory-aware collaborative CPU-GPU governor that considers both the memory access footprint as well as the CPU/GPU frequency to improve energy efficiency of high-end mobile game workloads by performing dynamic voltage and frequency scaling (DVFS). Second\, We present a case study executing a mix of popular data-parallel workloads such as convolutional neural networks (CNNs)\, computer vision filters and graphics rendering kernels on mobile devices\, and show that both performance and energy consumption of mobile platforms can be improved by synergistically deploying these underutilized compute resources. Third\, we present SURF: a self-aware unified runtime framework for parallel programs on heterogeneous mobile architectures. SURF supports several heterogeneous parallel programming languages (including OpenMP and OpenCL)\, and enables dynamic task-mapping to heterogeneous resources based on runtime measurement and prediction.The measurement and monitoring loop enables self-aware adaptation of run-time mapping to exploit the best available resource dynamically.\n\nWe implemented all the software components on real-world mobile SoCs and evaluate our proposed approaches with mobile games and mix of parallel benchmarks and CNN applications accordingly.
URL:https://www.cecs.uci.edu/event/cooperative-power-and-resource-management-for-heterogeneous-mobile-architectures/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20190826T150000
DTEND;TZID=America/Los_Angeles:20190826T160000
DTSTAMP:20231011T190904Z
CREATED:20231011T190859Z
LAST-MODIFIED:20231011T190904Z
UID:14565-1566831600-1566835200@www.cecs.uci.edu
SUMMARY:Event Detection and Estimation Using Distributed Population Owned Sensors
DESCRIPTION:Name: Ahmed Mokhtar Nagy Ibrahim\nChair: Prof. Ahmed Eltawil \nDate: August 7th\, 2019 \nTime: 1:00 pm \nLocation:  EH 2210 – EECS Chair’s Conference Room \nCommittee: Ahmed Eltawil(Chair)\, Ender Ayanoglu\, and Lee Swindlehurst \nTitle:”Event Detection and Estimation Using Distributed Population Owned Sensors ” \nAbstract:\nSmart phones are an indispensable tool in modern day-to-day life. Their widespread use has spawned numerous applications targeting diverse domains such as bio-medical\, environment sensing and infrastructure monitoring. In such applications\, the accuracy of the sensors at the core of the system is still questionable\, since these devices are not originally designed for high accuracy sensing purposes. In this thesis\, we investigate the accuracy limits of one of the commonly used sensors\, namely\, a smart phone accelerometer. As a use case\, we focus on utilizing smart phone accelerometers in structural health monitoring (SHM). Using the already deployed network of distributed citizen-owned sensors is considered a cheap alternative to standalone sensors. These devices can capture floors vibration during disasters\, and consequently compute the instantaneous displacement of each floor. Hence\, damage indicators defined by government standards such as peak relative displacement can be estimated. In this work\, we study the displacement estimation accuracy and propose a zero-velocity update (ZUPT) method for noise cancellation. Theoretical derivation and experimental validation are presented\, and we discuss the impact of sensor error on the achieved building classification accuracy. Moreover\, in spite of the presence of sensor error\, SHM systems can be resilient by adopting machine learning. Several algorithms such as support vector machine (SVM)\, K-nearest neighbor (KNN) and convolutional neural network (CNN) are adopted and compared. Techniques for addressing noise levels are proposed and the results are compared to regular noise cancellation techniques such as filtering. \nFinally\, since most previous work focused on modelling the sensor chip error itself\, we study other sources of error such as sampling time uncertainty which is introduced by the device operating system (OS). That type of error can be considered a major contributor to the overall error\, specially for sufficiently large signals. Hence\, we propose a novel smart device accelerometer error model that includes the traditional additive noise as well as sampling time uncertainty errors. The model is validated experimentally using shake table experiments\, and maximum likely-hood estimation (MLE) is used to estimate the model parameters. Moreover\, we derive the Cramer-Rao lower bound (CRLB) of acceleration estimation based on the proposed model.
URL:https://www.cecs.uci.edu/event/event-detection-and-estimation-using-distributed-population-owned-sensors/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20191011T150000
DTEND;TZID=America/Los_Angeles:20191011T160000
DTSTAMP:20231011T190904Z
CREATED:20231011T190900Z
LAST-MODIFIED:20231011T190904Z
UID:14567-1570806000-1570809600@www.cecs.uci.edu
SUMMARY:Towards Engineering Computer Vision Systems: From Web to FPGAs
DESCRIPTION:Final Defense – Sajjad Taheri \n\n\nDate: August 26\, 2019\nTime: 2:00 pm \n\nLocation: Donald Bren Hall 4011 \n\n\nCommittee: Alex Nicolau(chair)\, Alex Veidenbaum(co-chair)\, Nikil Dutt \n\n\nTitle: Towards Engineering Computer Vision Systems: From Web to FPGAs\n\n\n\nAbstract:\n\nComputer vision has many applications that impact our daily lives\, such as automation\, entertainment\, healthcare\, etc. However\, computer vision is very challenging. This is in part due to intrinsically difficult nature of the problem and partly due to the complexity and size of visual data that need to be processed. To be able to deploy computer vision in many practical use cases\, sophisticated algorithms and efficient implementations are required. In this dissertation\, we consider two platforms that are suitable for computer vision processing\, yet they were not easily accessible to algorithm designers and developers: The Web and FPGA-based Accelerators. Through the development of open-source software\, we highlight challenges associated with vision development on each platform and demonstrate opportunities to mitigate them.\n\nThe Web is the world’s most ubiquitous computing platform which hosts a plethora of visual content. Due to historical reasons such as insufficient JavaScript performance and lack of API support for acquiring and manipulating images\, computer vision is not mainstream on the Web. We show that in light of recent web developments such as vastly improved JavaScript performance and addition of APIs such as WebRTC\, efficient computer vision processing can be realized on web clients. Through novel engineering techniques\, we translate a popular open-source computer vision library (OpenCV) from C++ to JavaScript and optimize its performance for the web environment. We demonstrate that hundreds of computer vision functions run in browsers with performance close to their original C++ version.\n\nField Programmable Gate Arrays (FPGA)s are a promising solution to mitigate the computational cost of vision algorithms through hardware pipelining and parallelism while providing excellent power efficiency. However\, an efficient FPGA implementation of vision algorithm requires hardware design expertise and a considerable amount of engineering person-hours. We show how high-level graph-based specifications\, such as OpenVX can significantly improve FPGA design productivity. Since such abstractions exclude implementation details\, different implementation configurations that satisfy various design constraints\, such as performance and power consumption\, can be explored systematically. They also enable a variety of local and global optimizations to apply across the algorithms.
URL:https://www.cecs.uci.edu/event/towards-engineering-computer-vision-systems-from-web-to-fpgas/
CATEGORIES:PhD Defenses
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20191016T150000
DTEND;TZID=America/Los_Angeles:20191016T160000
DTSTAMP:20231011T190904Z
CREATED:20231011T190900Z
LAST-MODIFIED:20231011T190904Z
UID:14568-1571238000-1571241600@www.cecs.uci.edu
SUMMARY:"Energy-Aware Data Center Management: Monitoring Trends and Insights via Machine Learning"
DESCRIPTION:Name: Hayk Shoukourian\nDate and Time: Friday\, November 15\, 2019 \nLocation: Donald Bren Hall 3011 \nAbstract: \nThe increasing demand for online resources has led to an immense energy burden on contemporary\nHigh Performance Computing (HPC) and cloud data centers. Even though each new generation of HPC systems delivers a higher power efficiency\, the growth in system density and overall performance has continuously contributed to an increase in energy consumption. The mentioned energy consumption not only converts to high operational bills and affects the environment\, but also influences the stability of the underlying power grid. In fact\, all these have already led some governmental organizations to reconsider data center deployment procedures with an increased demand for the renewable energy utilization and waste heat recovery. \nThe talk will give an overview of Leibniz Supercomputing Centre (LRZ)\, introduce its flagship HPC systems\, discuss the high-temperature direct liquid cooling solution and the waste heat reuse. These will be followed by the recent R&D results that rely on ML technologies for forecasting various energy/power consumption relevant Key Performance Indicators at a data center building infrastructure level. The talk will highlight the applications of the developed model outlining its use in proactive management of modern data centers for tackling the above-mentioned challenges. \nBiography: \nDr. Hayk Shoukourian received his M.Sc. and PhD in Computer Science from Technical University of Munich in 2012 and 2015 correspondingly. He joined Leibniz Supercomputing Centre (LRZ) in 2012 and his R&D activities mainly involve efficient energy/power consumption management of the HPC data centers. In his current role\, Dr. Shoukourian is responsible for adaptive modelling of interoperability between the target HPC systems and the building infrastructure of the supercomputing site. He is also a team leader for PRACE (Partnership for Advanced Computing in Europe) work package on “HPC Commissioning and Prototyping”. Since August 2018 Dr. Shoukourian is a lecturer in Computer Science at Ludwig-Maximilians-Universität München (LMU).
URL:https://www.cecs.uci.edu/event/energy-aware-data-center-management-monitoring-trends-and-insights-via-machine-learning/
CATEGORIES:Seminars at CECS
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20191028T150000
DTEND;TZID=America/Los_Angeles:20191028T160000
DTSTAMP:20231011T193349Z
CREATED:20231011T190900Z
LAST-MODIFIED:20231011T193349Z
UID:14569-1572274800-1572278400@www.cecs.uci.edu
SUMMARY:Daniel Gajski and Lukai Cai Win ESWEEK Test of Time Award
DESCRIPTION:Daniel Gajski (Prof. Emeritus) and Lukai Cai (former PhD student\, now at Qualcomm\, San Diego) have been awarded the Embedded Systems Week (ESWEEK) Test of Time Award 2019 for their paper\, “Transaction Level Modeling: An Overview”\, which was originally published at the International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) in 2003.\nWith more than 40 years of intensive engagement in industry and academia and considered on of the founding fathers of new design methods with higher reach towards an upwards degree of abstraction\, Daniel Gajski has been a leader in establishing the fields of silicon compilation\, high-level synthesis and system-level design. \nThis award is in recognition of a paper which has defined a new era in embedded computer system design and is now\, 16 years later\, honored because it has passed the test of time. In the year 2000\, Daniel Gajski’s research group created the concept of Transaction Level Modeling by applying the SpecC methodology used in their “Transaction Level Modeling: An Overview”. This paper marks the milestone of a novel taxonomy where communication and computation are separated in the modeling\, validation\, refinement\, exploration and synthesis of embedded computer systems. Today\, these principles in use throughout national and international academia and industry\, proving the substantial impact their work has created. \nProf. Juergen Teich\, who led the award ceremony together with Prof. Petru Eles (General Chair) in New York on October 16\, emphasized\, “For the first year\, ESWEEK is honoring the authors of one paper with highest impact published at a previous CODES+ISSS\, CASES and EMSOFT conference at ESWEEK with a Test-of-Time Award.” \nWe are proud to see Daniel Gajski and Lukai Cai’s paper receiving this exceptional award.
URL:https://www.cecs.uci.edu/event/daniel-gajski-and-lukai-cai-win-esweek-test-of-time-award/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20191031T080000
DTEND;TZID=America/Los_Angeles:20191031T170000
DTSTAMP:20231031T183444Z
CREATED:20231031T183444Z
LAST-MODIFIED:20231031T183444Z
UID:15701-1572508800-1572541200@www.cecs.uci.edu
SUMMARY:Rainer Doemer Awarded Dean’s Honoree for Teaching Excellence
DESCRIPTION:Rainer Doemer awarded Dean’s Honoree for Teaching Excellence by the Office of the Provost and Executive VC to recognize his demonstrated excellence in undergraduate teaching at UCI. Congrats Prof. Doemer!
URL:https://www.cecs.uci.edu/event/rainer-doemer-awarded-deans-honoree-for-teaching-excellence/
CATEGORIES:Awards
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20191031T080000
DTEND;TZID=America/Los_Angeles:20191031T170000
DTSTAMP:20231031T183645Z
CREATED:20231031T183645Z
LAST-MODIFIED:20231031T183645Z
UID:15705-1572508800-1572541200@www.cecs.uci.edu
SUMMARY:Zhou Li and Chaoyi Lu Reached Best paper Award Finalist at ACM IMC’19
DESCRIPTION:Assistant Professor Zhou Li and Chaoyi Lu reached Best paper Award Finalist at the ACM Internet Measurement Conference 2019 with research paper titled\, “An End-to-End\, Large-Scale Measurement of DNS-over-Encryption: How Far Have We Come?” Congrats!
URL:https://www.cecs.uci.edu/event/zhou-li-and-chaoyi-lu-reached-best-paper-award-finalist-at-acm-imc19/
CATEGORIES:Awards
END:VEVENT
END:VCALENDAR