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SUMMARY:Applied Microeconomics and Trade Seminar Series presents: Shanjun Li
DESCRIPTION:Applied Microeconomics and Trade Seminar\nDate: Thursday\, October 30th\, 2025\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Shanjun Li\nPersonal Webpage \nTitle: Steven and Roberta Denning Professor of Global Sustainability \nAffiliation: Stanford University \nHost: Peter Christensen \n \nSeminar title: Range Anxiety\n \nABSTRACT:   Range anxiety\, the fear of depleting battery before reaching a charging station\, is often cited as a major barrier to electric vehicle (EV) adoption\, yet there has been limited formal economic analysis to quantify its importance and understand the policy implications. We develop a continuous-time dynamic model of EV usage and charging decisions to quantify range anxiety as the utility loss from feasible yet unrealized trips due to perceived range constraints. Using high-frequency data of 188\,000 EV trips and 30\,000 charging events among 8\,000 EVs in Shanghai\, we recover model parameters governing consumer driving and charging decisions. The estimates imply that\, across EV models with varying driving ranges\, average range anxiety was about $1\,900 in 2021 but declined to $1\,200 in 2024\, driven by improvements in charging infrastructure and\, especially\, in creases in driving range. Policy simulations underscore the importance of coordinating investments in battery capacity and charging infrastructure to address range anxiety: relative to socially optimal levels\, Shanghai’s EV market has under-invested in driving range while over-investing in charging infrastructure.
URL:https://events.ucsc.edu/event/applied-microeconomics-and-trade-seminar-series-presents-shanjun-li/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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SUMMARY:In-person Info Session – Japan Research Fellowships (JSPS)
DESCRIPTION:Are you interested in funding for research\, collaboration\, and travel opportunities in Japan? Representatives from the Japan Society for the Promotion of Science (JSPS) will be on campus for an in-person info session: \n\n\nWhen:  Wednesday\, October 29\, 2025  |  1:30 p.m. – 2:30 p.m. \nWhere: Engineering Building 2\, Room 180 (E2-180) \nLight refreshments provided. \n  \nPlease RSVP here \nWho should attend? \nFaculty\, researchers/postdocs\, students in ALL disciplines. This information session is particularly relevant for: \n\nFaculty fellowships at junior\, mid\, and senior levels (short and long term)\nPostdocs (summer\, short\, and long-term fellowships)\nPre-PhD students (summer and short-term fellowships)\n\nLearn more about JSPS here. Questions? Email gsabo@ucsc.edu.
URL:https://events.ucsc.edu/event/in-person-info-session-japan-research-fellowships-jsps/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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DTSTART;TZID=America/Los_Angeles:20251028T134000
DTEND;TZID=America/Los_Angeles:20251028T150000
DTSTAMP:20260629T185924
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SUMMARY:Macroeconomics & International Finance Seminar Series Presents: Zhiguo He
DESCRIPTION:Macroeconomics and International Finance Seminar\nDate: Tuesday\, October 28\, 2025\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Zhiguo He\nTitle: James Irvin Miller Professor of Finance\nAffiliation: Stanford University \nHost: Michael Leung \n \nSeminar title: Household Migration and Collateral Constraint: Cash-based Housing Resettlement in China\n \nABSTRACT:   Collateral constraints reduce household migration to expensive locations by restricting financing for home purchases. This endogenous location choice can amplify the impact of relaxing borrowing constraints. Using China’s cash-based shantytown renovation program (2015-2018) as a natural experiment\, we provide evidence that cash resettlement– by converting illiquid shanty houses into cash– facilitated household location upgrading and raised house prices in more expensive locations. A dynamic spatial model with collateral constraints confirms that endogenous location upgrading amplified the effect of cash transfer\, raising lifetime housing expenditures by nearly 50%\, and house price growth in low-tier cities by 9% in 2016-2020.
URL:https://events.ucsc.edu/event/macroeconomics-international-finance-seminar-series-presents-zhiguo-he/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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DTSTART;TZID=America/Los_Angeles:20251028T110000
DTEND;TZID=America/Los_Angeles:20251028T121500
DTSTAMP:20260629T185924
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SUMMARY:CSE Colloquium: A Journey from Programming Systems Research to AI Agents
DESCRIPTION:Speaker: Koushik Sen\, UC Berkeley and Google DeepMind \nAbstract: Coding has emerged as an important application area for large language models (LLMs)\, with a proliferation of code-specific models and their applications across various domains and tasks such as program repair\, performance optimization\, debugging\, test generation\, documentation\, and security hardening. In this talk\, I will describe how we built powerful coding agents such as R2E-Gym and DeepSWE using test-driven methodology for solving various kinds of coding tasks\, such as repair\, optimization\, security vulnerability detection\, and refactoring.  I will also discuss a novel technique\, called GEPA\, for domain-specific optimization of AI agent systems\, which has shown a significant advantage over reinforcement learning. \nBio: Koushik Sen is a professor in the Department of Electrical Engineering and Computer Sciences at the University of California\, Berkeley. His research interest lies in Software Engineering\, Programming Languages\, and AI. He is interested in developing software tools and methodologies that improve programmer productivity and software quality. He is known for his work on “DART: Directed Automated Random Testing\,” concolic testing\, and LiveCodeBench. He has received a NSF CAREER Award in 2008\, a Haifa Verification Conference (HVC) Award in 2009\, a IFIP TC2 Manfred Paul Award for Excellence in Software: Theory and Practice in 2010\, a Sloan Foundation Fellowship in 2011\, a Professor R. Narasimhan Lecture Award in 2014\, an Okawa Foundation Research Grant in 2015\, and an ACM SIGSOFT Impact Paper Award in 2019. He has won several ACM SIGSOFT Distinguished Paper Awards. He received the C.L. and Jane W-S. Liu Award in 2004\, the C. W. Gear Outstanding Graduate Award in 2005\, and the David J. Kuck Outstanding Ph.D. Thesis Award in 2007\, and a Distinguished Alumni Educator Award in 2014 from the UIUC Department of Computer Science. He holds a B.Tech from the Indian Institute of Technology\, Kanpur\, and an M.S. and Ph.D. in CS from the University of Illinois at Urbana-Champaign. \n\nHosted by: Professor Mohsen Lesani \nLocation: Engineering 2\, E2-180 (Refreshments such as coffee and pastries will be provided.) \nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-a-journey-from-programming-systems-research-to-ai-agents/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251027T104000
DTEND;TZID=America/Los_Angeles:20251027T114500
DTSTAMP:20260629T185924
CREATED:20251020T180828Z
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SUMMARY:ECE 290 Seminar: Performance Bounds and Bottlenecks for Neuromorphic ML Accelerators
DESCRIPTION:Presenter: Jason Yik\, PhD Candidate\, Harvard SEAS \nDescription: Recent research on neuromorphic accelerators has investigated their efficiency and performance benefits for machine learning (ML) inference at the edge. This talk will focus on the performance implications of the fully-on-chip\, manycore-distributed memory architecture used by current neuromorphic accelerators. In conventional architectures\, the roofline model is a well-known performance model for denoting performance bounds and bottlenecks. For neuromorphics\, we show that bounds create a different shape\, a floorline\, and we demonstrate how to optimize ML deployment using the floorline as a performance guide. \nBio: Jason Yik is a PhD candidate at Harvard SEAS\, with a research focus in neuromorphic computing architectures. His prior work includes designing benchmark frameworks and tools for neuromorphic research\, and modeling and optimizing neuromorphic system performance. Currently\, he is an intern with the ASIC architecture team at Cerebras Systems. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1 \nRoom: E2-192
URL:https://events.ucsc.edu/event/ece-290-seminar-performance-bounds-and-bottlenecks-for-neuromorphic-ml-accelerators/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251023T140000
DTEND;TZID=America/Los_Angeles:20251023T170000
DTSTAMP:20260629T185924
CREATED:20250709T070000Z
LAST-MODIFIED:20251002T220138Z
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SUMMARY:Wiki-a-thon Supporting BIPOC Scientists
DESCRIPTION:Join us for an afternoon of creating and editing pages for BIPOC scientists\, engineers\, and technologists! Wikipedia overwhelmingly recognizes the achievements of white people. This wiki-a-thon works to reverse this trend\, highlighting the often overlooked accomplishments of BIPOC leaders in science and technology\, and ensuring that the next generation can see role models who look like them. \nNO EXPERIENCE NECESSARY – RSVPs appreciated \nWe will provide a list of scientists who don’t yet have pages\, or you can come up with your own! The event will begin with a short training on how to edit Wikipedia\, followed by time to write your own article on a scientist\, engineer\, or technologist of your choice. \nWhen: Thursday\, October 23 from 2-5pm. Come for the whole time or just an hour or two! \nWhere: E2-506 and Zoom (RSVP for link) \nWho: All students\, faculty\, and staff are welcome to attend! \nSnacks and drinks will be provided! \nRead more about our inspiration.
URL:https://events.ucsc.edu/event/copy-of-wiki-a-thon-supporting-bipoc-scientists/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251023T140000
DTEND;TZID=America/Los_Angeles:20251023T150000
DTSTAMP:20260629T185924
CREATED:20251017T183348Z
LAST-MODIFIED:20251017T183421Z
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SUMMARY:Robots that Know What They Do Not Know: Assured AI-enabled Autonomy in Unknown Environments
DESCRIPTION:Speaker: Yiannis Kantaros\, Assistant Professor\, Electrical and Systems Engineering at WashU in St. Louis. \nTitle: Robots that Know What They Do Not Know: Assured AI-enabled Autonomy in Unknown Environments. \nTime: Thursday\, Oct 23rd\, 2025\, 2:00-3:00 pm. \nLocation: E2-553 or Zoom. \nAbstract: Designing robots that navigate unfamiliar environments to execute natural language (NL) commands is a cornerstone of advanced embodied intelligence. While recent AI-enabled architectures have made impressive empirical progress\, they often lack introspection\, leading to systems that act with unwarranted confidence\, unaware of their own limitations or whether they have successfully completed their tasks. As a result\, these systems offer limited performance and safety guarantees\, restricting their deployment in safety-critical settings.\nIn this talk\, I will present an introspective\, neuro-symbolic autonomy architecture that enables robots to complete NL tasks in unknown environments with assurance guarantees by explicitly quantifying their own uncertainty using uncertainty quantification (UQ) tools. The neural component employs large language models (LLMs) to translate NL commands into temporal logic specifications\, while leveraging conformal prediction\, a UQ tool\, to calibrate and quantify prediction uncertainty arising from LLM imperfections and potential NL ambiguity. When uncertainty exceeds user-defined thresholds\, uncertainty-aware feedback is solicited from auxiliary LLMs—or\, if necessary\, from human operators. We provide theoretical guarantees\, supported by empirical case studies\, that the proposed uncertainty-aware translation framework\, called ConformalNL2LTL\, achieves user-specified translation success rates under certain distributional settings. The symbolic component generates plans for mobile robots with AI-enabled perception systems to satisfy temporal logic tasks while explicitly reasoning over perceptual and environmental uncertainty. This allows robots to decide when to proceed confidently and when to actively gather additional sensor data\, ensuring task completion with the desired probability. Notably\, the developed planners are agnostic to specific sensor models or noise characteristics. The talk will conclude with case studies and demonstrations\, followed by a discussion of limitations and open problems. \nSpeaker Bio: Yiannis Kantaros is an Assistant Professor in the Department of Electrical and Systems Engineering\, Washington University in St. Louis (WashU)\, St. Louis\, MO\, USA. He earned a Diploma in Electrical and Computer Engineering in 2012 from the University of Patras\, Greece\, and M.Sc. and Ph.D. degrees in Mechanical Engineering from Duke University\, Durham\, NC\, in 2017 and 2018\, respectively. Prior to joining WashU\, he was a postdoctoral associate in the Department of Computer and Information Science\, University of Pennsylvania\, Philadelphia\, PA. His current research interests include machine learning\, distributed control and optimization\, and formal methods with applications in robotics. He received the Best Student Paper Award at the 2nd IEEE Global Conference on Signal and Information Processing (GlobalSIP) in 2014 and was a finalist for the Best Multi-Robot Systems Paper at the IEEE International Conference on Robotics and Automation (ICRA) in 2024 and a finalist for the Best Paper Award at the ACM/IEEE International Conference on Cyber-physical Systems (CPSWeek-ICCPS) in 2025. He also received the 2017-18 Outstanding Dissertation Research Award from the Department of Mechanical Engineering and Materials Science at Duke University and a 2024 NSF CAREER Award.
URL:https://events.ucsc.edu/event/assured-ai-enabled-autonomy-in-unknown-environments/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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DTSTART;TZID=America/Los_Angeles:20251023T134000
DTEND;TZID=America/Los_Angeles:20251023T150000
DTSTAMP:20260629T185924
CREATED:20251022T204629Z
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SUMMARY:Behavioral\, Econometrics and Theory Seminar Series Presents: Kevin Chen
DESCRIPTION:Economics Behavioral\, Econometrics\, & Theory Seminar\nDate: Thursday\, October 23\, 2025\nTime: 1:40-3:00 p.m.\nLocation: Engineering 2\, Rm 499\n\n \n\nSpeaker: Kevin Chen \nTitle:  Assistant Professor of Economics \nAffiliation: Stanford University\nHost: Michael Leung\n \nSeminar title: Compound Selection Decisions: An Almost SURE Approach \n \nABSTRACT:  This paper proposes methods for producing compound selection decisions in a Gaussian sequence model. Given unknown\, fixed parameters µ_{1:n} and known σ_{1:n} with observations Yᵢ ∼ 𝒩(μᵢ\, σᵢ²)\, the aim is to select a subset of units S to maximize utility Σ_{i∈S}(μᵢ − Kᵢ) for known costs Kᵢ. Inspired by Stein’s unbiased risk estimate (SURE)\, we introduce an almost unbiased estimator\, ASSURE\, for the expected utility of a proposed decision rule. ASSURE allows a user to choose a welfare-maximizing rule from a pre-specified class by optimizing the estimated welfare\, thereby producing selection decisions that borrow strength across noisy estimates. We show that ASSURE yields decision rules that are asymptotically no worse than the optimal but infeasible rule in the pre-specified class. We apply ASSURE to p-value decision procedures in A/B testing\, selecting Census tracts for economic opportunity\, and identifying discriminating firms.
URL:https://events.ucsc.edu/event/behavioral-econometrics-and-theory-seminar-series-presents-kevin-chen/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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DTSTART;TZID=America/Los_Angeles:20251022T110000
DTEND;TZID=America/Los_Angeles:20251022T121500
DTSTAMP:20260629T185924
CREATED:20250919T070000Z
LAST-MODIFIED:20251022T183911Z
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SUMMARY:CSE Colloquium - The C++11 Concurrency Memory Model: Remaining Challenges
DESCRIPTION:Presenter: Hans Boehm\, Google \nAbstract: C++11 extended the language to include threads\, defining a concurrency memory model to specify the semantics of shared variables\, including “atomic” variables that can be accessed without mutual exclusion. Although this followed Posix threads by more than a decade\, and the revision of the Java memory model by a few years\, it still helped to resolve some very fundamental points of confusion about the semantics and validity of compiler optimizations in multi-threaded programs. The C definition largely copied it\, and several other programming languages and systems\, as well as later versions of Java\, built on it. \nThese shared variable semantics provide a clean solution for concurrent programming for which a small amount of extra synchronization-related overhead is acceptable. However\, C++ programmers pride themselves in squeezing out the last bit of performance\, even if it involves living on the edge. Although the C++ memory model attempts to address those cases\, issues remain. In particular\, so-called “relaxed” atomics do not have clean semantics\, for reasons that appear more and more fundamental. And the discovery that well-motivated hardware characteristics are incompatible with the original model required complicating it. On the other hand\, hardware improvements have greatly reduced the need for the now deprecated “memory_order_consume” facility. \nWe’ll start with an overview of the C++ memory model\, and then outline some of the remaining challenges. We’ll give an example to illustrate why “memory_order_relaxed”\, which attempts to just expose machine load and store instructions\, is inherently much harder to define at the programming language level than it is at the hardware level. \nBio: Hans Boehm works primarily on concurrency issues in the Android platform. He was the initial chair of the ISO C++ Concurrency Study Group\, where he led the addition of threads and associated concurrency semantics to the language. He occasionally gets sidetracked into other topics\, including work on arithmetic in the Google Calculator app.\n\nHans is best known as the original primary author of bdwgc\, a garbage collector for C. He has published extensively on memory management and concurrent programming. He holds a Ph.D. from Cornell University. He is a former chair of ACM SIGPLAN\, an ACM Fellow\, and the recipient of the 2020 ACM SIGPLAN Programming Languages Achievement Award.\nHosted by: Professor Mohsen Lesani \nLocation: Engineering 2\, E2-180\n*Refreshments such as coffee and pastries will be provided. \nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-the-c11-concurrency-memory-model-remaining-challenges/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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DTSTART;TZID=America/Los_Angeles:20251020T123000
DTEND;TZID=America/Los_Angeles:20251020T123000
DTSTAMP:20260629T185924
CREATED:20251009T225928Z
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SUMMARY:CM Seminar - "Forty-Four Esolangs: The Art of Esoteric Code"
DESCRIPTION:Presented by: Daniel Temkin\n\nDescription: Software art is widely accepted\, but can programming languages themselves be art? The new book Forty-Four Esolangs makes this argument\, collecting work by a single artist who poses code as prayer to the Greek gods\, patterns of empty folders\, or typed in tandem by two programmers\, the rhythm and synchrony of their typing determining commands. Temkin will share projects from the book in the context of thirty plus years of esolangs\, showing the poetic possibilities of this medium. \nBio: Daniel Temkin makes photographic and computational art exploring logic and human irrationality. He began interviewing other esolangers and code artists in 2011\, creating the blog esoteric.codes. ZKM exhibited the blog and commissioned videos of Temkin explaining esolang history for their Open Codes show in 2018–19. Esoteric.codes earned an ArtsWriters.org grant and a residency at New Museum’s NEW INC\, the first museum-led cultural incubator. Temkin has written about esolangs for Hyperallergic and Leonardo\, and his aesthetic theory of the form was published by Digital Humanities Quarterly. You can see his work at danieltemkin.com. \nHosted by: Professor Katherine Isbister \nWhen: Monday\, October 20 from 12:30PM to 1:30PM \nLocation:  \nIN-PERSON @ UCSC Main Campus\, E2-280. \nViewing room @ SVC 3212.  \nLUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend. \n  \nZoom info:  \nhttps://ucsc.zoom.us/j/94577724433?pwd=VgUIkuCxez84skpyuxydEDxbdSfc5k.1 \nMeeting ID: 945 7772 4433 \nPasscode: 545175
URL:https://events.ucsc.edu/event/cm-seminar-forty-four-esolangs-the-art-of-esoteric-code/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
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DTSTART;TZID=America/Los_Angeles:20251020T104000
DTEND;TZID=America/Los_Angeles:20251020T114500
DTSTAMP:20260629T185924
CREATED:20251016T235308Z
LAST-MODIFIED:20251016T235431Z
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SUMMARY:ECE 290 Seminar: Biohybrid Electronics Using Extracellular Electron Transfer
DESCRIPTION:Presenter: Ben Keitz\, Associate Professor\, University of Texas at Austin \nDescription: Qualities exhibited by living systems\, including self-regulation\, self-healing\, morphology control\, and environmental responsiveness\, are highly attractive for sensing and computing applications. However\, it has been challenging to develop robust and programmable interfaces between living systems and electronic components. Addressing this challenge\, our lab employs techniques from microbiology\, synthetic biology\, and metabolic engineering to control extracellular electron transfer (EET)\, a form of microbial respiration in which extracellular metals and metal oxides are used as terminal electron acceptors. Using the model electroactive bacterium Shewanella oneidensis\, we coopt EET to link cellular metabolism and protein expression to microelectronic device behavior. Specifically\, we show that S. oneidensis can interface with organic electrochemical transistors (OECTs) through specific electron transfer machinery. The inclusion of living cells endows single transistors with complex logic\, short-term plasticity\, and other unique properties. We also establish that S. oneidensis can interact with both p-type and n-type conducting polymers to further control transistor performance. Ultimately\, our work demonstrates how unique forms of bacterial respiration can be leveraged to merge the advantages of living and traditional computation. \nBio: Benjamin (Keith) Keitz received his PhD in Chemistry from the California Institute of Technology and completed his postdoctoral training at the University of California\, Berkeley. He is a native of Austin\, TX and is currently an Associate Professor and the Frank A. Liddell Jr. Fellow in Chemical Engineering in the McKetta Department of Chemical Engineering at the University of Texas at Austin. Research in the Keitz lab focuses on the engineering of electroactive bacteria and the applications of extracellular electron transfer in biocatalysis\, materials synthesis\, synthetic biology\, and biosensing. His work has received several awards including an NIH Maximizing Investigators’ Research Award\, an NSF CAREER Award\, and an Air Force Office of Scientific Research Young Investigator Award. \nHosted by: Professor Marco Rolandi\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1 \nRoom: E2-192
URL:https://events.ucsc.edu/event/ece-290-seminar-biohybrid-electronics-using-extracellular-electron-transfer/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251010T113000
DTEND;TZID=America/Los_Angeles:20251010T113000
DTSTAMP:20260629T185924
CREATED:20250920T070000Z
LAST-MODIFIED:20250925T231706Z
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SUMMARY:Guide to Data Structures and Algorithms at Google
DESCRIPTION:Interested in learning more about data structures and algorithms? Join Google for this highly informative workshop!
URL:https://events.ucsc.edu/event/guide-to-data-structures-and-algorithms-at-google/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251009T173000
DTEND;TZID=America/Los_Angeles:20251009T173000
DTSTAMP:20260629T185924
CREATED:20250924T213406Z
LAST-MODIFIED:20250924T213406Z
UID:10000212-1760031000-1760031000@events.ucsc.edu
SUMMARY:Developing Personal Projects & Building Your Brand with Google
DESCRIPTION:Learn directly from successful Googlers about how to highlight the qualities\, skills\, and talents that describe you as a professional by building a brand profile and mission statement.
URL:https://events.ucsc.edu/event/developing-personal-projects-building-your-brand-with-google/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251008T183000
DTEND;TZID=America/Los_Angeles:20251008T183000
DTSTAMP:20260629T185924
CREATED:20250920T070000Z
LAST-MODIFIED:20250925T231600Z
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SUMMARY:Understanding the Technical Interview Process at Google
DESCRIPTION:Curious of how the technical interview process at Google works? Are you gearing up for technical interviews this fall? Whether you’re Interested in their internships or full-time roles\, you may want to brush up on those interview skills. Join us for mock questions and tips!
URL:https://events.ucsc.edu/event/understanding-the-technical-interview-process-at-google/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251008T140000
DTEND;TZID=America/Los_Angeles:20251008T140000
DTSTAMP:20260629T185924
CREATED:20250920T070000Z
LAST-MODIFIED:20250925T231705Z
UID:10000210-1759932000-1759932000@events.ucsc.edu
SUMMARY:Resume Workshop with Google
DESCRIPTION:Are you submitting applications for internships and full-time opportunities this semester? Join us for this resume workshop to find out how the format\, structure\, and detailed content of your resume could maximize your chances of receiving an interview opportunity with Google. Don't forget to bring a copy of your most updated resume with you!
URL:https://events.ucsc.edu/event/resume-workshop-with-google/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/09/97e6ce886799eac09edd3587fac085ed6992f021.jpg
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251008T110000
DTEND;TZID=America/Los_Angeles:20251008T110000
DTSTAMP:20260629T185924
CREATED:20250919T070000Z
LAST-MODIFIED:20250925T231702Z
UID:10000204-1759921200-1759921200@events.ucsc.edu
SUMMARY:CSE Colloquium: Can Great Programmers Be Taught?
DESCRIPTION:Presenter: John Ousterhout\, Stanford University \nAbstract: People have been programming computers for more than 80 years\, but there is little agreement on how to design software or even what a good design looks like. As a community\, we talk a lot about tools and processes\, but hardly at all about design. In this talk I will describe my recent work to identify and communicate a set of software design principles\, including a new software design course at Stanford that is taught more like an English writing seminar than a traditional programming class\, and a book on software design\, which is based on the concepts from the class. I will also present a few of the design principles\, such as "classes should be deep" and "general-purpose classes are deeper." \nBio: John Ousterhout is the Bosack Lerner Professor of Computer Science\, Emeritus at Stanford University. His prior positions include 14 years in industry\, where he founded two companies (Scriptics and Electric Cloud)\, preceded by 14 years as Professor of Computer Science at U.C. Berkeley.  He is author of the book "A Philosophy of Software Design"\, co-creator of the Raft consensus protocol\, and creator of the Tcl scripting language and the Tk toolkit.  Ousterhout received a BS degree in Physics from Yale University and a PhD in Computer Science from Carnegie Mellon University. He is a member of the National Academy of Engineering and has received numerous awards\, including the ACM Software System Award\, the ACM Grace Murray Hopper Award\, the National Science Foundation Presidential Young Investigator Award\, and the U.C. Berkeley Distinguished Teaching Award. \nHosted by: Professor Mohsen Lesani \n*Refreshments such as coffee and pastries will be provided.
URL:https://events.ucsc.edu/event/cse-colloquium-can-great-programmers-be-taught/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/09/fcc89bc579b7bdc3daf60fc4830e92da3e06aaf0.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251006T104000
DTEND;TZID=America/Los_Angeles:20251006T104000
DTSTAMP:20260629T185924
CREATED:20251003T195533Z
LAST-MODIFIED:20251003T195533Z
UID:10003166-1759747200-1759747200@events.ucsc.edu
SUMMARY:ECE 290 Seminar: Operational Cybersecurity of Modern Power Systems
DESCRIPTION:Presenter: Dr. Daniel Arnold\, Lead Power Systems Engineer\, Lawrence Livermore National Laboratory \n  \nDescription: The adoption of new types of generation and loads\, such as data centers\, small modular reactors\, and electric vehicles servicing equipment presents many challenges for system operators who are tasked with maintaining the safety and efficiency of the power grid.  New consumption patterns\, IoT connectivity of these devices\, and emerging control paradigms\, make it possible for these devices to be utilized to disrupt the operation of the power system.  In this talk\, I will discuss our past research efforts at the intersection of control theory\, power systems\, and AI to model\, simulate\, and mitigate cyber threats in the electric grid. I will close with a discussion of contemporary issues in power systems which will need to be addressed by the research and industrial community in the near future. \n  \nBio: Dr. Daniel Arnold is a Lead Power Systems Engineer at the Lawrence Livermore National Laboratory and an Adjunct Professor of Civil and Environmental Engineering at UC Berkeley. He graduated from UC Berkeley with a Ph.D. in Mechanical Engineering in 2015 and was an ITRI-Rosenfeld Postdoctoral Fellow at Lawrence Berkeley National Laboratory from 2016-2017. From 2017 to 2025 he was a Research Scientist at the Lawrence Berkeley National Laboratory. His interests are at the intersection of the fields of control theory\, optimization\, machine learning\, and power systems. His recent work focuses on the use of these techniques for cybersecurity of the electric power system and other critical infrastructure. \n  \nHosted by: Professor Soumya Bose\, ECE Department \n\nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-operational-cybersecurity-of-modern-power-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251002T110000
DTEND;TZID=America/Los_Angeles:20251002T110000
DTSTAMP:20260629T185924
CREATED:20250922T070000Z
LAST-MODIFIED:20250925T231708Z
UID:10000216-1759402800-1759402800@events.ucsc.edu
SUMMARY:CSE Colloquium: Enabling scalable GPU computing via efficient virtual memory systems
DESCRIPTION:Presenter: Hyeran Jeon\, UC Merced \nTitle: Enabling scalable GPU computing via efficient virtual memory systems \nAbstract: GPUs have become one of the most important accelerators of various emerging workloads. While the massive parallelism makes the GPUs one of the most favorable compute engines\, the limited on-device memory capacity hinders their wider adoption. Virtual memory systems have been helpful in transparently expanding memory space to host CPU memory and peer GPU memories\, as GPUs can access data through simple pointer sharing regardless of the physical location of that data. However\, as GPU architecture evolves and the volume of data increases significantly\, the virtual memory systems themselves become one of the critical performance bottlenecks. This talk will explore the perils and opportunities of virtual memory systems under emerging GPU architectures.\nThe first part of the talk will show that the limited IOMMU bandwidth is one of the primary performance limiters in multi-chip-module GPUs (MCM-GPUs) due to the increasing concurrency of multiple GPU chiplets. To fundamentally reduce the translation demands\, the talk will introduce a new way of page mapping that effectively replaces page-table-based virtual memory translations with simple calculation-based translations. The second part of the talk will focus on GPUs that have internal GMMUs. The talk will first show that naive GMMU translation bandwidth increase will incur significant area overhead. Then\, we show that one of the existing but highly underutilized accelerators integrated in the GPU die\, the ray tracing cores\, can be repurposed for virtual memory translation. \nBio: Hyeran Jeon is an associate professor at the University of California\, Merced. Hyeran's main research interests lie in high-performance\, energy-efficient\, and robust computer architecture and systems. Her research lab (MoCA Lab) has been sponsored by the government and industry\, including National Science Foundation\, California Energy Commission\, Xilinx\, NVIDIA\, and Ampere Computing. She earned her Ph.D. at the University of Southern California. She has industry experience as an intern at IBM T.J. Watson Research Center and AMD Research\, and as a systems software engineer at Samsung Electronics. She is a recipient of the NSF CAREER award and the USC Viterbi dean’s doctoral fellowship.  \nHosted by: Professor Mohsen Lesani \nLocation: Engineering 2\, E2-180\n*Refreshments such as coffee and pastries will be provided.
URL:https://events.ucsc.edu/event/cse-colloquium-enabling-scalable-gpu-computing-via-efficient-virtual-memory-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/09/b56062924b51a96e16bab380e11a731acbcdae43.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250929T104000
DTEND;TZID=America/Los_Angeles:20250929T104000
DTSTAMP:20260629T185924
CREATED:20250919T070000Z
LAST-MODIFIED:20250925T231554Z
UID:10000202-1759142400-1759142400@events.ucsc.edu
SUMMARY:ECE 290 Seminar: From Code to Clinic: How Regulatory Science and Virtual Trials Ensure Trustworthy AI in Medical Imaging
DESCRIPTION:Presenter: Dr. Brandon Nelson\, Staff Fellow\, Division of Imaging\, Diagnostics\, and Software Reliability (DIDSR)\, U.S. Food and Drug Administration’s Center for Devices and Radiological Health (CDRH) \nDescription: Artificial intelligence is rapidly transforming diagnostic and interventional radiology\, presenting immense opportunities for improving patient care alongside significant regulatory challenges. As AI/ML-enabled devices proliferate\, how do we ensure they are safe\, effective\, and perform robustly across the diverse patient populations and imaging hardware seen in clinical practice? \nThis talk will introduce the FDA’s role in device evaluation and address the urgent need for new scientific methods to keep pace with the rapid evolution of AI-based technologies. The presentation will focus on the critical role of regulatory science—the discipline of creating novel tools and methodologies to assess the safety\, efficacy\, and performance of these complex\, data-driven systems. \nI will detail my research at the FDA\, which centers on developing and applying innovative in silico evaluation tools\, specifically virtual clinical trials that leverage synthetic patient data and simulated pathologies. These tools are critical for addressing real-world data gaps and allow for the rigorous\, systematic "stress-testing" of AI algorithms. I will share specific examples from my research\, including the creation of virtual cohorts to assess AI robustness for tasks like intracranial hemorrhage detection and CT image reconstruction\, with a particular focus on ensuring generalizability to underrepresented pediatric populations. \nFinally\, I will discuss how these regulatory science frameworks can create powerful collaborative opportunities\, bridging the gap between cutting-edge academic innovation in areas like photon-counting and C-arm CT and the evidence needed to bring trustworthy AI safely to the clinic. \nBio: Dr. Brandon Nelson is a Staff Fellow within the Division of Imaging\, Diagnostics\, and Software Reliability (DIDSR) at the U.S. Food and Drug Administration’s Center for Devices and Radiological Health (CDRH). In this unique role\, he combines regulatory duties with scientific research\, serving as a subject matter expert and reviewer for medical device submissions that incorporate AI/ML and advanced image reconstruction\, while also leading research to develop novel tools for their evaluation.  \nHis primary research focuses on leveraging regulatory science—including in silico methods like virtual clinical trials and synthetic data generation—to assess the robustness\, generalizability\, and safety of medical imaging AI\, with a special emphasis on addressing performance gaps in pediatric populations.\n  \nHe earned his Ph.D. in Biomedical Engineering from the Mayo Clinic Graduate School of Biomedical Sciences\, where his dissertation focused on multi-contrast\, grating-based interferometry for micro-CT. Dr. Nelson is a recipient of the FDA's Critical Path Award for his work on pediatric AI evaluations and has published extensively in leading medical physics journals and conferences. \n\nHosted by: Professor Soumya Bose\, ECE Department
URL:https://events.ucsc.edu/event/ece-290-seminar-from-code-to-clinic-how-regulatory-science-and-virtual-trials-ensure-trustworthy-ai-in-medical-imaging/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/09/56be053cbaf20930289bab1af234ee4b7cee6f5d.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250915T100000
DTEND;TZID=America/Los_Angeles:20250915T100000
DTSTAMP:20260629T185924
CREATED:20250905T070000Z
LAST-MODIFIED:20250925T231435Z
UID:10000145-1757930400-1757930400@events.ucsc.edu
SUMMARY:Van Duker\, N. (AM) - A Random Choice Hybrid Method for Resolving Shock Placement Errors in 1D Relativistic Hydrodynamics with Transverse Velocities
DESCRIPTION:This report presents a one-dimensional Random Choice-based hybrid method for simulating special relativistic hydrodynamics (SRHD) flow problems. The proposed scheme combines a high-order accurate method and a random choice method\, selectively applying the first to smooth flows and the second to shocks and discontinuities. This hybrid approach addresses the issue of incorrect wave placements in the presence of significant transverse velocity\, commonly encountered in one-dimensional SRHD shock tube tests. In support of this development\, we present a modified shock/contact detection switch\, specifically tuned for relativistic flows. We find that our method improves both the accuracy and computational performance when compared against existing methods on a well-known family of pathological shock tube problems. Our analysis of these pathological problems provides a path forward for further improving existing higher-dimensional methods. \nEvent Host: Nathan Van Duker\, Ph.D Student\, Applied Mathematics \nAdvisor: Dongwook Lee
URL:https://events.ucsc.edu/event/van-duker-n-am-a-random-choice-hybrid-method-for-resolving-shock-placement-errors-in-1d-relativistic-hydrodynamics-with-transverse-velocities/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250910T140000
DTEND;TZID=America/Los_Angeles:20250910T140000
DTSTAMP:20260629T185924
CREATED:20250825T070000Z
LAST-MODIFIED:20250925T231632Z
UID:10000123-1757512800-1757512800@events.ucsc.edu
SUMMARY:Mavrogiannakis\, A. (CSE) - Scalable Oblivious Databases and Systems
DESCRIPTION:Modern applications are increasingly designed with a strong emphasis on scalability and performance\, as systems are expected to process ever-growing volumes of data and deliver results with minimal latency. Techniques such as distributed architectures\, in-memory computation\, and optimized data structures are routinely adopted to meet these performance-driven demands. However\, in the pursuit of speed and efficiency\, security is often treated as a secondary concern or an afterthought. This oversight can lead to critical vulnerabilities\, as even the most performant systems remain fundamentally insecure if sensitive information can be leaked or exploited. As data becomes more valuable and privacy regulations grow stricter\, ensuring robust security measures is not merely desirable but strictly necessary—an essential requirement that must stand alongside scalability and performance as a first-class design goal. \nTo meet security requirements\, many applications adopt end-to-end encryption to protect data stored in the cloud. While this prevents external adversaries from accessing sensitive information\, prior work [CITE] has demonstrated that encryption alone is insufficient: an untrusted server can still exploit execution patterns and access behaviors to gradually reconstruct the underlying database in plaintext. As an alternative\, other applications rely on Trusted Execution Environments (TEEs)\, which offer strong guarantees through memory encryption\, isolation\, and integrity checks. TEEs are particularly appealing due to their ease of use and high performance\, often approaching that of non-encrypted systems. However\, TEEs are not without limitations [CITE]. They remain vulnerable to leakage-abuse attacks and side-channel vulnerabilities [CITE]\, which can undermine their security guarantees in practice. \nIn my research\, I combine TEEs with oblivious computation to achieve stronger security guarantees without sacrificing practicality. Specifically\, my work focuses on designing\, analyzing\, and implementing oblivious algorithms for databases and systems. A central theme of my research is bridging the gap between security and performance\, developing scalable algorithms that approach the efficiency of plaintext execution. For example\, in our first project\, Obliviator (to appear at USENIX Security ’25)\, we introduced oblivious implementations of fundamental database operators—such as filtering\, aggregation\, and joins—in a shared-memory setting\, achieving efficiency at scale on datasets up to hundreds of gigabytes. Building on this foundation\, our subsequent work extends these operators to distributed environments\, addressing challenges such as secure execution under weaker trust assumptions and reducing communication overhead\, both in terms of rounds and data exchanged. We also introduced frameworks that enable parallelism in oblivious computation\, further enhancing performance. My current work focuses on extending these techniques to multi-way joins\, where combining multiple tables introduces new challenges in both efficiency and security. In parallel\, I am exploring query optimization strategies tailored to the oblivious setting\, with the goal of pushing oblivious database systems closer to the performance of traditional plaintext systems. \nEvent Host: Apostolos Mavrogiannakis\, Ph.D Student\, Computer Science & Engineering
URL:https://events.ucsc.edu/event/mavrogiannakis-a-cse-scalable-oblivious-databases-and-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250827T110000
DTEND;TZID=America/Los_Angeles:20250827T110000
DTSTAMP:20260629T185924
CREATED:20250825T070000Z
LAST-MODIFIED:20250925T231632Z
UID:10000124-1756292400-1756292400@events.ucsc.edu
SUMMARY:Rakshit\, G. (CSE) -Improving Question Answering through Figurativeness Understanding\, Semantic Representation and Multi-Agent Conflict Resolution
DESCRIPTION:Open-domain question answering (ODQA) systems come with diverse challenges — ranging from resolving conflicting information to interpreting figurative expressions and representing meaning in a human-understandable form. This dissertation presents three complementary contributions toward building more robust and interpretable QA systems. \nFirst\, we investigate QA model performance on figurative language. Introducing FigurativeQA\, a benchmark of yes/no questions with figurative and literal contexts\, we demonstrate that popular BERT-based QA systems underperform significantly on figurative text. However\, prompting-based approaches like ChatGPT with chain-of-thought reasoning can mitigate this gap\, particularly when figurative contexts are automatically simplified. \nSecond\, we present ASQ\, a novel tool for automatically generating question-answer meaning representations (QMR) from Abstract Meaning Representation (AMR) graphs. ASQ enables scalable and linguistically grounded QA dataset construction\, bridging traditional formal semantics with natural language interfaces. We show that ASQ-generated questions exhibit high content fidelity and overlap with existing crowd-annotated resources like QAMR. \nFinally\, we explore how large language models (LLMs) handle conflicting evidence in ODQA\, proposing a multi-agent framework where answers generated by different models are evaluated through a verification step. Experiments using the QACC dataset and state-of-the-art LLMs (GPT-4o\, Claude 4\, DeepSeek-R1) reveal that model diversity enhances answer quality\, though requiring explanations during verification does not always lead to improvements. \nTogether\, these contributions advance the interpretability\, robustness\, and accuracy of QA systems. \nEvent Host: Geetanjali Rakshit\, Ph.D Candidate\, Computer Science & Engineering
URL:https://events.ucsc.edu/event/rakshit-g-cse-improving-question-answering-through-figurativeness-understanding-semantic-representation-and-multi-agent-conflict-resolution/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250821T130000
DTEND;TZID=America/Los_Angeles:20250821T130000
DTSTAMP:20260629T185924
CREATED:20250815T070000Z
LAST-MODIFIED:20250925T231627Z
UID:10000106-1755781200-1755781200@events.ucsc.edu
SUMMARY:Briden\, M. (CSE) -  Representation Learning and Generative Forecasting for Noisy and Limited Clinical Data: Applications in Wound Healing and EEG
DESCRIPTION:The rapid integration of artificial intelligence and machine learning into clinical practice has driven advances in disease classification\, segmentation\, and clinical decision support. However\, the complexities of medical data pose a challenge to widespread adoption. The rarity of medical conditions\, ethical considerations\, and varying acquisition protocols leads to limited and noisy data. The time-intensive process of labeling data\, the high degree of accuracy required in clinical settings\, and the ill-defined nature of certain medical conditions further complicate the application and deployment of machine learning models. Likewise\, high‐stakes medical decisions demand trustworthy and interpretable predictions. However\, prioritizing trust and explainability is rarely a primary objective in most model designs. \nThis thesis addresses three key challenges in machine learning for healthcare. First\, we develop methods for learning under noisy and limited medical data\, focusing on representation learning strategies that improve generalization when datasets are small or contain mislabeled samples. Second\, we explore the prediction of generative outcomes amid label noise and data scarcity\, utilizing parameter-efficient and temporal generative models to forecast disease trajectories. Third\, we advance trustworthy and explainable medical artificial intelligence by designing deep architectures that provide interpretable outputs suitable for clinical decision-making. \nThese challenges are addressed in the context of two complementary medical modalities: wound healing images and electroencephalogram signals. Wound healing tasks focus on predicting healing trajectories while enhancing interpretability through segmentation-based explanations and training large models in light of extreme data noise and scarcity. Electroencephalogram-based tasks emphasize representation learning and explainability for non-invasive mental state classification. These experiments demonstrate the clinical relevance of the proposed approaches and their ability to operate under challenging medical conditions across both imaging and physiological signal domains. \nEvent Host: Michael Briden\, PhD Candidate\, Computer Science & Engineering \nAdvisor: Narges Norouzi
URL:https://events.ucsc.edu/event/briden-m-cse-representation-learning-and-generative-forecasting-for-noisy-and-limited-clinical-data-applications-in-wound-healing-and-eeg/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250819T140000
DTEND;TZID=America/Los_Angeles:20250819T140000
DTSTAMP:20260629T185924
CREATED:20250818T070000Z
LAST-MODIFIED:20250925T231432Z
UID:10000111-1755612000-1755612000@events.ucsc.edu
SUMMARY:Bhatia\, N. (CSE) - Building Adaptive Intelligence into Wireless Sensing
DESCRIPTION:WiFi-based indoor positioning is a widely researched area focused on determining the location of devices. Accurate indoor positioning has numerous applications\, including asset tracking and indoor navigation. Despite advances\, their adoption in practice remains limited due to several challenges such as environmental changes that cause signal fading\, multipath effects\, and interference\, all of which reduce positioning accuracy. Moreover\, telemetry data vary across WiFi device vendors\, presenting distinct features and formats\, while use-case requirements can also differ significantly. At present\, there is no unified model capable of handling these variations effectively. \nWe present WiFiGPT\, a decoder-only transformer-based system designed to address these variations while achieving high localization accuracy. Our experiments with WiFiGPT show that it can effectively capture subtle spatial patterns in noisy wireless telemetry\, making them reliable regressors. Compared to state-of-the-art methods\, our approach matches and often surpasses conventional techniques across multiple types of telemetry. Achieving sub-meter accuracy for RSSI and FTM and centimeter-level precision for CSI highlights the potential of LLM-based localization to outperform specialized methods\, without the need for handcrafted signal processing or calibration. Other work includes EchoSense\, which utilizes CSI to monitor vital signs such as heart rate and respiration with high accuracy. \nEvent Host: Nayan Bhatia\, PhD Student\, Computer Science & Engineering \nAdvisor: Katia Obraczka
URL:https://events.ucsc.edu/event/bhatia-n-cse-building-adaptive-intelligence-into-wireless-sensing/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250819T140000
DTEND;TZID=America/Los_Angeles:20250819T140000
DTSTAMP:20260629T185924
CREATED:20250818T070000Z
LAST-MODIFIED:20250925T231627Z
UID:10000112-1755612000-1755612000@events.ucsc.edu
SUMMARY:Swaby\, A. (ECE) -  Improving X-ray Medical Imaging using Amorphous Selenium as a Photoconductive Layer
DESCRIPTION:The presence of coronary artery calcification is a strong predictor for future cardiovascular events where cardiac risk categories are quantified depending on calcification size. Dual-energy chest X-rays provide high contrast visualization to improve opportunistic screening for quantifying coronary artery calcifications\, determining bone mineral density (i.e.\, osteoporosis) and characterizing lung lesions. As a dual-energy imaging modality\, multilayer flat panel detectors acquire low- and high-energy X-ray images as a polyenergetic\, single-exposure. Combining two detectors into a dual-layer configuration\, weighted subtraction techniques in the resulting images allow for differentiation of soft tissue from the projection of the bone structures and other high attenuating materials. To improve detection of calcifications < 1 mm in size\, the performance of a dual-layer X-ray detector is investigated as a means of providing the necessary μm-resolution and spectral separation for enhanced contrast between low- and high-energy X-ray images. A cascaded linear systems model is used to simulate the modulation transfer function\, detective quantum efficiency\, and noise power spectrum of an amorphous selenium direct conversion top detector and a cesium iodide-based indirect conversion bottom detector. As the framework for system design and optimization\, a generalized task-based analysis is used to analyze how the signal projections\, noise contributions\, task function\, and weighting factors contribute to the detectability index of the dual-layer imaging system.  \nEvent Host: Akyl Swaby\, PhD Candidate\, Electrical & Computer Engineering \nAdvisor:  Dr. Shiva Abbaszadeh
URL:https://events.ucsc.edu/event/swaby-a-ece-improving-x-ray-medical-imaging-using-amorphous-selenium-as-a-photoconductive-layer/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250819T100000
DTEND;TZID=America/Los_Angeles:20250819T100000
DTSTAMP:20260629T185924
CREATED:20250815T070000Z
LAST-MODIFIED:20250925T231431Z
UID:10000105-1755597600-1755597600@events.ucsc.edu
SUMMARY:Osorio\, S. (AM) - Image-Based Wound Infection Classification
DESCRIPTION:This thesis investigates the use of deep learning for classifying wound infections from photographic images\, using colony-forming unit (CFU) counts as a quantitative labeling standard. Leveraging the visual information in wound photographs and the clinical relevance of bacterial burden\, the study implements a multi-task U-Net architecture for both image reconstruction and binary classification in a shared-encoder framework. Three experimental conditions were explored: one using original images with positive class weighting\, one incorporating data augmentation to enhance visual diversity\, and one employing 5-fold cross-validation with augmentation to improve validation reliability. The non-augmented model achieved 91.7% accuracy at a threshold of 0.8\, correctly identifying 4 of 5 infected cases\, while Experiment 2 achieved 87.5% accuracy at a moderate threshold of 0.5 but became more conservative at higher thresholds. The third experiment reached 79.6% accuracy at a threshold of 0.3\, detecting all 11 infected cases despite signs of overfitting. These results highlight the model's strong performance in minimizing false negatives\, particularly in the non-augmented setting\, but also reflect limitations from the small dataset\, class imbalance\, and reliance on a small validation set. These factors suggest results should be interpreted cautiously and motivate further study with larger datasets\, improved regularization\, and more varied clinical scenarios. \nEvent Host: Sebastian Osorio\, M.S. Candidate\, Scientific Computing & Applied Mathematics \nAdvsior: Marcella Gomez
URL:https://events.ucsc.edu/event/osorio-s-am-image-based-wound-infection-classification/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250813T100000
DTEND;TZID=America/Los_Angeles:20250813T100000
DTSTAMP:20260629T185924
CREATED:20250806T070000Z
LAST-MODIFIED:20250925T231625Z
UID:10000092-1755079200-1755079200@events.ucsc.edu
SUMMARY:Asefi\, N. (ECE) - Generative Lagrangian Data Assimilation for Ocean Dynamics under Extreme Sparsity
DESCRIPTION:Reconstructing ocean dynamics from observational data is fundamentally limited by the sparse\, irregular\, and Lagrangian nature of spatial sampling\, particularly in subsurface and remote regions. This sparsity poses significant challenges for forecasting key phenomena such as eddy shedding and rogue waves. Traditional data assimilation methods and deep learning models often struggle to recover mesoscale turbulence under such constraints. We leverage a deep learning framework that combines neural operators with denoising diffusion probabilistic models (DDPMs) to reconstruct high-resolution ocean states from extremely sparse Lagrangian observations. By conditioning the generative model on neural operator outputs\, the framework accurately captures small-scale\, high-wavenumber dynamics even at $99%$ sparsity (for synthetic data) and $99.9%$ sparsity (for real satellite observations). We validate our method on benchmark systems\, synthetic float observations\, and real satellite data\, demonstrating robust performance under severe spatial sampling limitations as compared to other deep learning baselines. \nEvent Host: Niloofar Asefi\, PhD Student\, Electrical & Computer Engineering \nAdvisor: Ashesh Chattopadhyay
URL:https://events.ucsc.edu/event/asefi-n-ece-generative-lagrangian-data-assimilation-for-ocean-dynamics-under-extreme-sparsity/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250812T100000
DTEND;TZID=America/Los_Angeles:20250812T100000
DTSTAMP:20260629T185924
CREATED:20250811T070000Z
LAST-MODIFIED:20250925T231626Z
UID:10000098-1754992800-1754992800@events.ucsc.edu
SUMMARY:Mawhorter\, R. (CSE) - Certified Synthesis for Interactive Media: High Assurance Metroidvania Generation
DESCRIPTION:Program verification has been applied in many contexts (including videogames)\, but the scale and complexity of the examples that have been analyzed fall short of the ability to analyze many existing games without massive computational costs. My research focuses on automatic analysis and design of one particular game: Super Metroid\, with the goal of creating general methods for efficient analysis that address these issues. In pursuit of this goal\, I develop novel abstraction strategies that can be reapplied in other contexts. I also show that these same techniques can also be used to synthesize games\, and I develop a paradigm for understanding procedural generation problems as verification problems. This paradigm enables generators to certify their output\, and these certificates act as a powerful debugging tool. My research expands on existing techniques for applying symbolic search to large state spaces\, exploring many different ways of optimizing the state space representation\, and reporting on their relative effectiveness in real-world contexts. I also demonstrate how multiple layers of abstraction can be used to enhance existing search algorithms. Using these methods\, I show how verifying properties of software with respect to the humans that interact with it can be practically achieved. \nEvent Host: Ross Mawhorter\, PhD Candidate\, Computer Science & Engineering \nAdvsior: Adam Smith
URL:https://events.ucsc.edu/event/mawhorter-r-cse-certified-synthesis-for-interactive-media-high-assurance-metroidvania-generation/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250805T100000
DTEND;TZID=America/Los_Angeles:20250805T100000
DTSTAMP:20260629T185924
CREATED:20250801T070000Z
LAST-MODIFIED:20250925T231319Z
UID:10000086-1754388000-1754388000@events.ucsc.edu
SUMMARY:Larsen\, B. (CMPM) - Communal Narrative Play in Perennial Games
DESCRIPTION:Online communities tell stories with the games they play. As continual updates\, recurring monetization\, and platforms for community discussions have flourished\, we have seen a rise in video games using ongoing development to tell stories\, and have a community interact with those stories and build upon them. In this dissertation\, I study this phenomenon\, which I call textit{perennial games}—storytelling experiences\, which are perpetual\, continuous\, and tell an ongoing\, communal story\, where everyone influences its future in big and small ways. I study this especially as it has grown in the years 2010-2025\, as the modern rise of the live-service game has exploded in popularity\, and are using this format to tell stories in ways both unique yet also in ways that harks back to serial fiction\, professional wrestling\, modern television series\, traditional mythology\, and more. Through a three-pronged focus I study: 1) the games as narrative experiences\, and how they facilitate narrative play through their design\, 2) the communities who play them\, how and why they play with the narrative and stay in these worlds for decades\, and 3) the development\, investigating the many joys and challenges of telling an ongoing story\, following the inevitable oscillations as developers interact with the community. Through this multifaceted approach\, I illustrate how perennial games cultivate community by inherently trading their mystery for familiarity\, creating strong social bonds through the communal experience of uncovering\, cataloging and deciphering mystery. Pushed forward by the inherent myth that these games will continue to change\, the communities around them strain against and increasing lack of mystery\, both seeking the safety of their social bonds while yearning for that which brought them there in the first place. Perennial games can be alluded to a developed garden\, requiring maintenance and care\, each year taking a subtly new shape\, molded by its inhabitants and its caretakers\, always a bit more wild than anyone can manage on their own\, and as it grows the people inside it grow ever more dependent on its continued existence\, until the promise that kept them there breaks. \nEvent Host: Bjarke Larsen\, PhD Candidate\, Computational Media \nAdvisor: Elin Carstensdottir
URL:https://events.ucsc.edu/event/larsen-b-cmpm-communal-narrative-play-in-perennial-games/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250725T110000
DTEND;TZID=America/Los_Angeles:20250725T110000
DTSTAMP:20260629T185924
CREATED:20250709T070000Z
LAST-MODIFIED:20250925T231317Z
UID:10000065-1753441200-1753441200@events.ucsc.edu
SUMMARY:Basu\, S. (CSE) - Decomposition Techniques for Web-Scale Networks: Bridging Theory and Practice
DESCRIPTION:Decompositions of large-scale networks are central to many applications in graph mining\, network science\, and algorithm design. Over several decades\, a rich body of work has developed techniques to partition networks with various different objectives. However\, a noticeable gap persists between methods with strong theoretical guarantees\, and those that perform well in practice. Practical algorithms often lack provable guarantees\, while theoretically sound methods are rarely straightforward to implement\, and scale poorly. This thesis presents a suite of techniques that aim to close this gap\, presenting decomposition methods that are both theoretically grounded and practically efficient. \n\nThe first part of the thesis focuses on dense subgraph decomposition\, a fundamental problem with numerous real-world applications and a close relation to the problem of community detection studied in the complex networks literature. Specifically\, we focus on decompositions that produce a large number of small components; a variant that existing techniques struggle with. We propose a novel shift in perspective: rather than approximate the optimum closely using traditional optimization approaches\, we develop fast algorithms with provable lower bounds on output quality. We introduce some new objectives and metrics to achieve these\, and introduce a new theoretical framework that captures structural properties of real-world networks. We compare our perspective with the common approach taken in the community detection literature\, and demonstrate algorithms that significantly outperform prior methods across a broad range of datasets. \nThe second part of the thesis explores how network decompositions can enable sublinear-time algorithms: ones that produce approximate solutions without needing to inspect the entire input. We study two somewhat distinct problems. The first is a property testing problem in bounded-degree planar graphs\, where we show that hyperfinite decompositions allow for efficient testing of even the most complex properties. The second examines shortest-path computation in real-world networks. By observing that shortest paths often traverse a dense core\, we design the first sublinear algorithm that exploits this structure to approximate shortest paths. Our method competes with exact algorithms in speed\, while scaling to larger networks that such algorithms cannot handle. \nWe leave some open problems and discuss ongoing and future work\, and provide pointers on how our insights can be leveraged to study a larger class of problems in graph algorithms. \nEvent Host: Sabyasachi Basu\, PhD Candidate\, Computer Science & Engineering \nAdvisor: C. Seshadhri
URL:https://events.ucsc.edu/event/basu-s-cse-decomposition-techniques-for-web-scale-networks-bridging-theory-and-practice/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
END:VCALENDAR