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SUMMARY:Sheaves\, T. (CSE) - Timing Side-Channels in Commercial ReRAM: Toward ReRAM Pentimenti
DESCRIPTION:Recently\, a class of non-invasive hardware side-channel attacks has been discovered in field-programmable gate arrays (FPGAs). These attacks extract remnants of prior users’ activity that persist as transistor defect states within reconfigurable routing resources. These remnants are known as FPGA Pentimenti. Resistive random-access memory (ReRAM) is a compelling candidate for pentimenti-like attacks beyond FPGAs. However\, unlike FPGAs\, where sophisticated on-chip sensors capable of detecting pentimenti have been well-studied\, non-invasive pentimenti recovery in commercial ReRAM must rely on measurements of observable write latency. These measurements are dominated by data-dependent structural biases that obscure any underlying defect-dynamics signal. In this dissertation\, we demonstrate that the structural and stochastic components of commercial ReRAM write latency can be decoupled and recovered through non-invasive timing analysis alone. Our results provide the reverse engineering and measurement infrastructure for future study of ReRAM pentimenti by isolating the component of programming latency sensitive to defect dynamics. \nEvent Host: Tyler Sheaves\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Dustin Richmond  \nZoom: https://ucsc.zoom.us/j/92729427179?pwd=BpYLqft18YdOU0mDdQWs8erID2VcHi.1 \nPasscode: 939530
URL:https://events.ucsc.edu/event/sheaves-t-cse-timing-side-channels-in-commercial-reram-toward-reram-pentimenti/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260601T123000
DTEND;TZID=America/Los_Angeles:20260601T133000
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SUMMARY:CM Seminar - Alex Olwal\, "Human-Centered Augmentation: Interacting with Matter\, Humans\, and Machines"
DESCRIPTION:Presented by: Alex Olwal \nDescription: “In this talk\, I will share my perspectives on the evolution and future of human-centered augmentation\, through the lens of two decades of research and development. Drawing from experiences across academia and industry\, I will discuss insights from having led projects in augmented reality\, accessibility\, electronic textiles\, novel sensing and displays\, and their implications for emerging AI-augmented interfaces.” \nBio: Alex Olwal is a research scientist and engineering leader focused on interaction technology and human augmentation. During his tenure at Google\, he founded the Interaction Lab and Biointerfaces team \, and tech transferred accessibility-focused language glasses to the Augmented Reality product organization\, where he established the Augmented Language Team. As an engineering manager in the product organization\, he evolved his team’s scope to deliver Human-AI language capabilities\, including speech perception\, natural language understanding\, real-time translation and captions\, and generative AI. The team’s conversational AI experiences for AR glasses were a key feature in the Google I/O 2022 keynote. Alex’s research has spanned augmented reality\, ubiquitous computing\, wearables\, and accessibility\, often leveraging novel opportunities in display technology\, sensing\, soft electronics\, and machine intelligence. He is passionate about impactful problems that can be addressed through Human-AI interfaces\, real-time interaction techniques and transformative applications. \nPreviously\, Alex conducted research at MIT Media Lab as a postdoctoral fellow after receiving his Ph.D. from KTH Royal Institute of Technology\, with research conducted at Columbia University\, UC Santa Barbara\, and Microsoft Research (research internship). He has held faculty positions at Stanford University\, Rhode Island School of Design\, and KTH. \nWebsite: www.olwal.com \nHosted by: Professor Katherine Isbister \nWhen: Monday\, June 1\, 2026 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. \nZoom info: \nhttps://ucsc.zoom.us/j/97081260699?pwd=eyt5f4CAEHHLQWBhdaLA693T3gecaj.1\nMeeting ID: 970 8126 0699\nPasscode: 047011
URL:https://events.ucsc.edu/event/cm-seminar-alex-olwal-human-centered-augmentation-interacting-with-matter-humans-and-machines/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20260601T104000
DTEND;TZID=America/Los_Angeles:20260601T114500
DTSTAMP:20260528T185942Z
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SUMMARY:ECE 290 Seminar: Memristors for a brain-scale neuromorphic chip
DESCRIPTION:Presenter: Sung-Mo “Steve” Kang\, Distinguished Professor Emeritus and Research Professor\, UC Santa Cruz \n  \nDescription: Recently\, applications of artificial intelligence (AI) have far outpaced Moore’s law in chip development\, thus creating an increasingly large gap between user demand and the supply that the semiconductor industry can deliver. In this talk\, we will discuss the unique roles of memristor technologies that can be leveraged to develop scaled-up AI neural networks\, particularly spiking neural networks (SNNs) for brain-like neuromorphic computing and unsupervised learning with high energy efficiency. Open-source memristor circuit designs\, along with open-source software\, may facilitate the development of micro- and nano-electronic systems that emulate brain functions. In this venue\, we will discuss how to harness memristor- based circuits and systems to build memristor neurons\, synapses\, and their interconnects for ultra-high packing density\, low power consumption\, and the fabrication services needed to enable innovation. \n  \nBio: Sung-Mo “Steve” Kang is a Distinguished Professor Emeritus and Research Professor at the Baskin School of Engineering\, UC Santa Cruz; Chancellor Emeritus of UC Merced; and President Emeritus of KAIST. He has published more than 500 journal and conference papers\, authored 10 books\, and holds 17 patents. Before returning to academia in 1985\, he led the development of the world’s premier fully CMOS 32-bit VLSI microprocessor chipsets for telecommunications and computing applications as a technical supervisor at AT&T Bell Laboratories in Murray Hill\, New Jersey. This work was recognized as an IEEE Milestone in February 2025. He has received honors\, including best paper awards\, induction into the Silicon Valley Engineering Hall of Fame\, the Alexander von Humboldt Senior US Scientists Award\, the IEEE Millennium Medal\, the IEEE Mac Van Valkenburg Circuits and Systems (CAS) Society Award\, the IEEE CAS Society Technical Excellence Award\, the US Semiconductor Research Corporation (SRC) Technical Excellence Award\, the IEEE Leon K. Kirchmayer Graduate Teaching Technical Field Award\, and the IEEE CAS Society John Choma Education Award\, as well as the Chang-Lin Tien Education Leadership Award. Dr. Kang is a Life Fellow of the IEEE and a Fellow of the Association for Computing Machinery (ACM)\, the American Association for the Advancement of Science (AAAS)\, and the Asia-Pacific AI Association. He is a life member of the European Academy of Sciences and Arts and the Korean Academy of Science and Technology\, and a foreign member of the National Academy of Engineering\, Korea. He received his B.S. from Fairleigh Dickinson University\, Teaneck\, New Jersey\, in 1970; an honorary B.S. from Yonsei University; an M.S. from the State University of New York at Buffalo in 1972; and a Ph.D. from the University of California at Berkeley in 1975\, all in electrical engineering. \n  \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-memristors-for-a-brain-scale-neuromorphic-chip/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20260529T140000
DTEND;TZID=America/Los_Angeles:20260529T160000
DTSTAMP:20260512T163221Z
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SUMMARY:Zhu\, R. (ECE) - From Neuromorphic Principles to Efficient Neural Language Architectures
DESCRIPTION:This dissertation investigates how neuromorphic and brain-inspired principles can guide the design of efficient neural language architectures. It addresses two central limitations of modern Transformer-based language models: memory growth with context length and high computational cost from dense matrix multiplication. Through studies of spiking neural networks\, linear-recurrent language models\, hybrid attention architectures\, MatMul-free models\, and looped language models\, the dissertation develops practical approaches for bounded-memory and bounded-compute language modeling. The central conclusion is that recurrent state\, temporal decay\, sparse computation\, and parameter reuse can provide useful design principles for scalable language models\, even when they are abstracted beyond literal biological spiking. \nEvent Host: Ridger Zhu\, Ph.D. Candidate\, Electrical & Computer Engineering  \nAdvisor: Jason Eshraghian \nZoom: https://ucsc.zoom.us/j/96672322005?pwd=3MSitgbm5WboIENbf1hKpxwXnt9VXh.1
URL:https://events.ucsc.edu/event/zhu-r-ece-from-neuromorphic-principles-to-efficient-neural-language-architectures/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260528T120000
DTEND;TZID=America/Los_Angeles:20260528T140000
DTSTAMP:20260526T163353Z
CREATED:20260526T163353Z
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SUMMARY:Ortiz Barbosa\, D. (CSE) - HARDENING AUTONOMOUS CYBER-PHYSICAL SYSTEMS AGAINST ADVERSARIAL CONDITIONS
DESCRIPTION:Autonomous systems\, such as Autonomous Vehicles (AVs) and drones\, are increasingly\ndeployed across a wider array of contexts for both civilian and military use. As these\nsystems become more common\, they may be targeted by malicious actors seeking to\nexploit and abuse them\, compromising safety-critical operations. Among the ways to\nprotect these systems simulation based testing frameworks have been developed. How-\never\, existing testing frameworks primarily focus on identifying logical flaws or system\nvulnerabilities\, often emphasizing static scenarios and paying less attention to an adap-\ntive intelligent adversary.\nTo help reduce this gap\, this dissertation develops and applies adaptive\, adversary-\naware methodologies to discover\, formalize\, and mitigate security vulnerabilities in au-\ntonomous systems spanning vehicle platooning\, drone swarms\, and vision-based drone\nrecovery. We first apply NLP techniques to discover and formalize driving rules across\nNorth American and Australian jurisdictions\, identifying possible restriction that an\nadversary can exploit. Likewise\, these rules can be used to test the adaptability of AVs\nto new contexts and to establish a formal basis for context-aware AV testing. Next\,\nwe apply optimization-based adversarial search to both ACC-controlled vehicle pla-\ntoons and obstacle-avoiding drone swarms. We uncover maneuvers that an adversary\ncan use against the system that range from crash-inducing patterns against platooning\ncontrollers to herding strategies that divert swarms from their objectives. Finally\, to\naddress the gap regarding the possible solutions to an adversarial attack we explore how\na drone can recover from it by using LVLMs to understand its context and select a safe\nlanding surface. \nEvent Host: Diego Ortiz Barbosa\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Alvaro A Cardenas
URL:https://events.ucsc.edu/event/ortiz-barbosa-d-cse-hardening-autonomous-cyber-physical-systems-against-adversarial-conditions/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260528T110000
DTEND;TZID=America/Los_Angeles:20260528T120000
DTSTAMP:20260522T165248Z
CREATED:20260522T165248Z
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SUMMARY:Oh\, S. (CSE) - Efficient Instruction Supply for Datacenter Processors
DESCRIPTION:Modern datacenter CPUs lose 25–66% of execution cycles to instruction-delivery stalls. This bottleneck persists\, despite the recent trend towards accelerators and GPUs\, as there is continuing demand by applications that only execute on CPUs. Two workload classes dominate today’s datacenter execution cycles: hyperscale server software (databases\, build systems\, and content stores)\, whose large instruction footprints create severe frontend pathologies; and agentic AI systems\, in which large-language-model agents plan\, dispatch tools\, and maintain growing conversational contexts\, causing CPUs to account for up to 88% of end-to-end agent latency. Reflecting this shift\, major CPU vendors have publicly repositioned the CPU as the orchestration layer of the AI stack and have begun shipping processors optimized for agent-centric workloads. \nThis dissertation argues that instruction delivery is the dominant CPU bottleneck across both workload classes and that the recent trend towards agentic AI further exacerbates this challenge. In hyperscale server binaries\, the primary pathologies are wrong-path prefetch pollution and post-recovery instruction-delivery gaps across large\, irregular call graphs. In agentic AI systems\, the bottleneck shifts to an orchestration substrate composed of protocol stacks\, dynamic-runtime dispatch\, and agent-specific extensions that is even more frontend-bound than traditional warehouse-scale workloads. \nTo address these bottlenecks\, this dissertation presents three technical contributions\, together with a companion infrastructure contribution. First\, Utility-Driven Prefetching (UDP) extends fetch-directed instruction prefetching (FDIP) with a learned per-prefetch utility model that admits candidates based on their historical contribution to demand-fetch hits\, including those reached along wrong-path execution. Second\, Junction-based Unified Miss-point Prefetching (JUMP) addresses the post-recovery instruction-delivery gap that UDP and prior FDIP optimizations cannot reach by launching a lightweight secondary FDIP thread at a learned miss point following each branch-prediction failure. Across a suite of datacenter workloads\, UDP improves IPC by 3.6% on average (up to 16.1%) over a state-of-the-art FDIP baseline\, while JUMP improves IPC by 2.0% on average (up to 14.9%). Combined\, the two mechanisms substantially close the gap between FDIP and a perfect L1 instruction cache at a storage cost of only a few tens of kilobytes.\nThird\, this dissertation introduces the Agentic Tax\, the first CPU characterization study of agentic AI workloads across three runtime families. The study is packaged as a deterministic-replay benchmark infrastructure that enables repeatable\, cycle-level evaluation under controlled conditions. The characterization shows that the orchestration substrate of agentic AI workloads is significantly more frontend-bound than the hyperscale datacenter workloads examined in prior work\, and that it introduces new dominant function families with no analog in traditional warehouse-scale systems. These findings motivate two architectural directions proposed as future work: extending UDP and JUMP to optimize the orchestration substrate itself\, and designing heterogeneous CPU cores that allocate frontend resources according to the execution phase. \nEvent Host: Surim Oh\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Heiner Litz \nZoom: https://ucsc.zoom.us/j/94753352649?pwd=7vQxlnSJkUb0KfG3t6STo639LhRv7j.1 \nPasscode: 205162
URL:https://events.ucsc.edu/event/oh-s-cse-efficient-instruction-supply-for-datacenter-processors/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260527T110000
DTEND;TZID=America/Los_Angeles:20260527T123000
DTSTAMP:20260330T203942Z
CREATED:20260330T203942Z
LAST-MODIFIED:20260330T203942Z
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SUMMARY:CSE Colloquium - Learning to Image: Computational Microscopy for Dynamic Systems
DESCRIPTION:Presenter: Laura Waller\, UC Berkeley \nAbstract: \nComputational imaging jointly designs hardware and algorithms to push beyond the classical limits of imaging\, enabling measurement of new quantities (e.g. 3D\, phase\, and super-resolution) with simple\, inexpensive hardware. These approaches have already transformed consumer photography; our goal is to achieve a similar transformation in scientific microscopy. \nIn this talk\, I will show how end-to-end learning is reshaping the design of imaging systems\, from programmable illumination with LED arrays to compact\, lensless cameras built from Scotch tape. By combining physical models with neural networks\, we can jointly learn how to capture data\, reconstruct images\, and self-calibrate systems that would otherwise be too complex to model. However\, many computational methods rely on multiple measurements\, limiting their use for live\, dynamic samples. I will introduce new space-time algorithms based on implicit neural representations (INRs) that jointly recover structure and motion\, correct artifacts\, and enable high-resolution imaging in regimes where traditional approaches fail. \nBio: \nLaura Waller is the Charles A. Desoer Professor of Electrical Engineering and Computer Sciences at UC Berkeley. She received B.S.\, M.Eng. and Ph.D. degrees from the Massachusetts Institute of Technology in 2004\, 2005 and 2010. After that\, she was a Postdoctoral Researcher and Lecturer of Physics at Princeton University from 2010-2012. She is a Packard Fellow for Science & Engineering\, Moore Foundation Data-driven Investigator\, OSA Fellow\, and Chan-Zuckerberg Biohub Investigator. She has received the Carol D. Soc Distinguished Graduate Mentoring Award\, OSA Adolph Lomb Medal\, the SPIE Early Career Award and the Max Planck-Humboldt Medal. \nHosted by: Professor Alvaro Cardenas \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-learning-to-image-computational-microscopy-for-dynamic-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260526T103000
DTEND;TZID=America/Los_Angeles:20260526T123000
DTSTAMP:20260512T164007Z
CREATED:20260512T164007Z
LAST-MODIFIED:20260512T164007Z
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SUMMARY:Castro\, S. (CSE) - Agentic AI for Security: Adversarial Foundations for Autonomous Cyber Operations
DESCRIPTION:Autonomous Cyber Operations (ACO) agents promise effective security automation with minimal human intervention\, yet their deployment raises three interconnected challenges: agents must be realistic (reproducing diverse attacker sophistication)\, secure (preventing autonomy from becoming an attack surface)\, and feasible (safely replicating human behavior at full autonomy). \nWe argue that these three properties are requirements for ACO agents. Existing approaches do not address them together and lack diverse adversarial coverage\, formal threat models for attacks against the agents themselves\, and systematic evaluation of multi-agent topologies. \nWe advance all three ACO properties: (1) For realism\, we establish adversarial foundations by discovering Windows OS vulnerabilities and releasing two exploits reliable across XP through 11. (2) For security\, we formalize ACO meta-attacks and meta-defenses\, propose the first invariant-based Meta-IDS detecting both sensor and actuator meta-attacks\, and introduce the first hybrid LLM–RL ACO integration for defense with a novel inter-agent communication protocol. (3) For feasibility\, we present MaLO\, the first dynamic-topology multi-agent ACO system\, achieving a 78.6\% success rate across a new 42-task security benchmark and solving operations up to 40× faster than human experts. We further propose the Security Operation Complexity Index (SOCX) classification and the T×V×O taxonomy as the first objective-driven evaluation methodology for coding-agent attacks. \nTogether\, these contributions demonstrate that ACO agents can match real-world adversarial sophistication\, resist meta-attacks\, and outperform human operators on complex security tasks. Open challenges remain in adaptive adversaries\, LLM–RL co-training\, dynamic topology selection\, and deployment beyond simulated environments. \n  \nEvent Host:  Sebastián R. Castro\, PhD Candidate\, Computer Science & Engineering \nAdvisor: Alvaro A. Cárdenas \nZoom: https://ucsc.zoom.us/j/2267557290?pwd=S0dNTTV3emZGUzlqV3dLbTg3a0NFUT09&omn=92791061627 \nPasscode: G20c06
URL:https://events.ucsc.edu/event/castro-s-cse-agentic-ai-for-security-adversarial-foundations-for-autonomous-cyber-operations/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260526T100000
DTEND;TZID=America/Los_Angeles:20260526T110000
DTSTAMP:20260518T190031Z
CREATED:20260518T185313Z
LAST-MODIFIED:20260518T190031Z
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SUMMARY:Harsh\, B. (CSE) - SUPERSCALAR\, MULTIPLE TAKEN BRANCH PREDICTOR
DESCRIPTION:This work addresses improvements in branch prediction mechanism to support high perfor-\nmance processors. The state of the art aims to balance the prediction latency and prediction\naccuracy using multi level correcting predictors [27]. Prior published work focusses on scalar\ndesigns and prediction accuracy improvement for hard to predict branches employing tailor\nmade\, non generic and non transferrable solutions [8]. Recent work also proposes ahead pre-\ndiction [42–44] to solve the problem of low accuracy of L0 predictor. \nThis work proposes efficent\, generic and transferrable solutions to reduce mispredic-\ntions and to use the fetch bandwidth more efficiently. This includes a biased overriding multi-\nlevel hierarchy with three predictor levels (L0\, L1\, L2). L0 uses a High-Confidence-Only Taken\n(HOTP) predictor that only predicts high-confidence taken control-flow instructions. This work\nfurther uses L1-L2 biased training to decrease mispredictions by L2 while it trains on branches\non which L1 has reached high confidence. This work proposes a superscalar predictor built\nusing the state of the art scalar predictor. Superscalar predictor is implemented by sizing a su-\nperscalar TAGE variant (BATAGE) using Optuna-based search. with varying table sizes and\naspect ratios. The work further proposes a branch predictor frontend design (nTakenBP) to de-\nliver multiple taken branch predictions per cycle. Unlike prior work\, nTakenBP achieves this by\nextending the existing BTB and TAGE tag-comparison logic rather than deepening lookahead. \n  \nEvent Host: Bhawandeep Singh Harsh\, Ph.D. Candidate\, Computer Science & Engineering \nAdvisor: Jose Renau \nZoom: https://ucsc.zoom.us/j/4166778865?pwd=cS9NcnVjRjArYlRRcDcrY3d5N0ZKQT09
URL:https://events.ucsc.edu/event/harsh-b-cse-superscalar-multiple-taken-branch-predictor/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTEND;TZID=America/Los_Angeles:20260526T110000
DTSTAMP:20260520T182036Z
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LAST-MODIFIED:20260520T182036Z
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SUMMARY:ECE Seminar: Advanced Sensing and AI Technologies for Food Safety and Precision Agriculture
DESCRIPTION:Presenter: Hamid Jafarbiglu\, Agricultural Technology Evaluator\, Big Idea Ventures \nDescription: California agriculture is increasingly adopting organic and regenerative production systems\, creating a growing need for technologies capable of monitoring complex agricultural environments\, assessing food safety risks\, and supporting data-driven management decisions. Emerging tools such as drones\, hyperspectral scanning\, environmental sensors\, and artificial intelligence provide new opportunities for continues field-scale monitoring\, risk detection\, and precision management while supporting sustainable agricultural practices. This talk highlights several applied research projects focused on the use of drone-based sensing\, spatio-spectral responses\, soil and environmental sensors\, and machine learning approaches to address real- world challenges in specialty crop production. These projects demonstrate how sensing technologies and advanced analytics can improve field-scale monitoring\, continuous risk assessment\, early detection\, and suitability in food production. Building on these experiences\, future research directions will focus on the intersection of food safety\, organic and regenerative agriculture\, and precision agricultural technologies. \nBio: Hamid Jafarbiglu is a researcher specializing in remote sensing\, spectral analysis\, and machine learning for agricultural systems. His work focuses on enhancing food safety\, crop monitoring\, and precision decision-making in high-value specialty crops.\n \nDr. Jafarbiglu earned his Ph.D. in Biological Systems Engineering from the University of California\, Davis\, following six years of intensive field research. His expertise integrates drone-based remote sensing\, hyperspectral imaging\, and AI to identify crop stress\, pest/disease outbreaks\, and nutrient deficiencies at their earliest stages.\n \nDuring his tenure at the UC Davis Digital Agriculture Lab\, Dr. Jafarbiglu’s doctoral and postdoctoral research resolved critical limitations in aerial spectral measurements. This work led to superior accuracy in drone-based sensing under variable field conditions and the development of scalable image-processing pipelines and digital orchard models for deep learning applications.\nBeyond research\, Dr. Jafarbiglu is an experienced extension professional. He has delivered hands-on training in drone operations and geospatial analysis to growers\, researchers\, and industry stakeholders\, bridging the gap between data-driven innovation and real-world adoption.\n \nHis background also extends to the commercial sector; as an Agricultural Technology Evaluator with Big Idea Ventures\, he conducted technical and market assessments for agri-food innovations\, including early-stage bio-based products. Today\, Dr. Jafarbiglu’s work continues to advance the integration of AI and remote sensing to foster sustainable\, regenerative farming and robust food systems across California and beyond. \nHosted by: Professor Marco Rolandi\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/96727838511?pwd=1Qzl9HTV3G2BxaSEG8GeKOPZVu2NWj.1
URL:https://events.ucsc.edu/event/ece-seminar-hamid-jafarbiglu/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260520T110000
DTEND;TZID=America/Los_Angeles:20260520T121500
DTSTAMP:20260518T155149Z
CREATED:20260518T155149Z
LAST-MODIFIED:20260518T155149Z
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SUMMARY:CSE Colloquium - Safety Alignment of LMs via Non-cooperative Games
DESCRIPTION:Presenter: Arman Zharmagambetov\, Meta \nAbstract:\nEnsuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rely on sequential adversarial training: generating adversarial (harmful) prompts and fine-tuning LMs to defend against them. We introduce a different paradigm: framing safety alignment as a non-zero-sum game between an Attacker LM and a Defender LM trained jointly via online reinforcement learning. Each LM continuously adapts to the other’s evolving strategies\, driving iterative improvement. Our method uses a preference-based reward signal derived from pairwise comparisons instead of point-wise scores\, providing more robust supervision and potentially reducing reward hacking. Our RL recipe\, AdvGame\, shifts the Pareto frontier of safety and utility\, yielding a Defender LM that is simultaneously more helpful and more resilient to adversarial attacks. In addition\, the resulting Attacker LM converges into a strong\, general-purpose red-teaming agent that can be directly deployed to probe arbitrary target models. \nBio:\nArman Zharmagambetov is a research scientist in the Fundamental AI Research (FAIR) team at Meta. His research primarily focuses on machine learning and optimization\, recently exploring their application in enhancing the security and robustness of AI systems. He received his PhD from the University of California – Merced. Afterward\, he completed his postdoctoral research at FAIR\, focusing on Reinforcement Learning\, AI-guided design and Optimization. \nHosted by: Professor Alvaro Cardenas and Professor Sungjin Im \nDate and Time: Wednesday\, May 20\, 2026 from 11:00 am – 12:15 pm \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-safety-alignment-of-lms-via-non-cooperative-games/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260520T090000
DTEND;TZID=America/Los_Angeles:20260520T110000
DTSTAMP:20260507T160500Z
CREATED:20260507T160500Z
LAST-MODIFIED:20260507T160500Z
UID:10014616-1779267600-1779274800@events.ucsc.edu
SUMMARY:Lucas\, J. (BMEB) - Enabling Population-Scale Analysis of Human Centromere Diversity
DESCRIPTION:Centromeric DNA is critical for accurate chromosome segregation and genome stability\, but due to its repetitive nature\, it was only recently fully included in a human reference. Rapid evolution and sequence diversity in these regions limit the utility of one reference sequence\, however. Integrating centromeric and pericentromeric satellite DNA – which together constitute over 5% of the human genome – into genetic research requires access to diverse sequences and the variation between them. The HPRC’s Release 2 dataset\, together with recent advancements in long-read assembly algorithms and new tools for sequence alignment and annotation\, now make characterization of centromeric variation possible. In this proposal\, I outline my work as part of the Human Pangenome Reference Consortium (HPRC) to create a diverse set of reference assemblies that accurately represent centromeric variation (aim 1)\, use novel tooling to characterize variation in centromeric regions (aim 2)\, and define the mutational processes that drive centromere evolution (aim 3). Completion of these aims will create a resource to enable the analysis and interpretation of centromeric variation data\, bringing these historically inaccessible regions into mainstream studies of human genetics\, evolution\, and disease. \nEvent Host: Julian Lucas\, Ph.D. Student\, Biomolecular Engineering & Bioinformatics \nAdvisor: Karen Miga \nZoom: https://ucsc.zoom.us/j/94129246296?pwd=QAs2hW8QZRNgpfaGJXvmaVfo52tIh7.1 \nPasscode: 669318
URL:https://events.ucsc.edu/event/lucas-j-bmeb-enabling-population-scale-analysis-of-human-centromere-diversity/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260519T100000
DTEND;TZID=America/Los_Angeles:20260519T120000
DTSTAMP:20260512T163057Z
CREATED:20260512T163057Z
LAST-MODIFIED:20260512T163057Z
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SUMMARY:Paul Pena\, D. (CSE) - Efficient Pattern Counting in Sparse Graphs and Hypergraphs
DESCRIPTION:Pattern counting is a fundamental problem in computer science with applications in many domains. For a fixed small pattern H\, we are given a large graph G and we are asked to count the number of subgraphs or homomorphisms (edge-preserving maps) of H in G. For practical applications where the input graph can be very large\, we are interested in finding efficient algorithms\, that is\, algorithms that run in linear or subquadratic time with respect to the size of the input. \nFinding such algorithms in general (when G can be any graph) is not possible. Instead\, we restrict our input to sparse classes of graphs. One family of graph classes that has been widely studied in the context of subgraph and homomorphism counting is bounded-degeneracy graph classes. Real-world graphs in many domains have bounded degeneracy\, so studying these classes in theory can lead to practical algorithms. \nA series of advances in the study of homomorphism counting led to a dichotomy theorem that exactly characterized which patterns were linear-time computable for bounded-degeneracy inputs. This dissertation builds on this result\, extending it to other variants of this problem\, and generalizing it to other different settings\, like counting hypergraphs and notions of sparsity beyond degeneracy. \nOur results help develop the theory of subgraph counting in sparse graphs and hypergraphs\, and showcase how sparsity can be used both in theory and practice to develop faster algorithms. \n  \nEvent Host: Daniel Paul Pena\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: C. Sheshadhri \nZoom: https://ucsc.zoom.us/j/97685906168?pwd=O35brsWilyn2m8AgMn0dKgALBe6wi1.1
URL:https://events.ucsc.edu/event/paul-pena-d-cse-efficient-pattern-counting-in-sparse-graphs-and-hypergraphs/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260519T100000
DTEND;TZID=America/Los_Angeles:20260519T110000
DTSTAMP:20260514T225808Z
CREATED:20260514T195842Z
LAST-MODIFIED:20260514T225808Z
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SUMMARY:ECE Seminar: Multiscale Sensing for Specialty Crop Systems: From Field Monitoring to Food Safety Application
DESCRIPTION:Presenter: Eve Laroche-Pinel\, Postdoctoral Researcher\, California State University\, Fresno \nDescription: Advances in remote sensing\, drone platforms\, and data analytics are enhancing the ability to monitor agricultural systems at fine spatial and temporal scales. This presentation will highlight applied research using multispectral and hyperspectral data from satellites\, drones\, aircraft\, and ground platforms to assess crop water status\, detect disease\, and estimate fruit composition. These efforts are developed in collaboration with growers and industry partners\, with an emphasis on methods that are robust under field conditions and scalable across production systems. Building on this foundation\, the talk will examine how similar sensing approaches could be extended to address food safety challenges in California agriculture\, particularly in systems transitioning toward organic and regenerative practices . By linking environmental variability\, water dynamics\, and landscape features with potential contamination pathways\, sensing technologies may support improved risk assessment and monitoring. \nBio: Eve Laroche-Pinel is a researcher specializing in the application of sensing technologies to agricultural systems\, with a focus on translating data-driven methods into tools that support decision-making in real production environments. Her work sits at the intersection of agricultural engineering\, remote sensing\, and applied machine learning.  \nShe holds a PhD from the National Polytechnic Institute of Toulouse (France)\, completed in partnership with industry\, where she developed an operational service to monitor vineyard water status using satellite imagery. This work fostered a strong emphasis on applied research\, system integration\, and technology transfer to end users.  \nShe is currently a postdoctoral researcher at California State University\, Fresno\, contributing to a research program that uses multispectral and hyperspectral data collected from satellites\, drones\, aircraft\, and ground-based platforms. Her work addresses plant water status\, disease detection\, and crop composition\, combining field measurements\, laboratory analyses\, and predictive modeling. These projects are conducted in collaboration with growers\, industry partners\, and multidisciplinary academic teams\, with the objective of producing methods that are robust under field conditions and scalable across production systems.  \nShe plans to increasingly focus on how sensing technologies could contribute to food safety challenges in specialty crops. By linking environmental variability\, crop condition\, and landscape features with potential contamination pathways\, her future work would aim to support improved risk assessment and monitoring strategies\, particularly in systems transitioning toward organic and regenerative practices.  \nExtension and stakeholder engagement are central to her approach. She works closely with growers and partners to co-develop field trials\, adapt methodologies to operational constraints\, and translate technical outputs into actionable guidance. Her work includes participation in workshops\, training activities\, and collaborative projects that connect research with practice.  \nHer long-term goal is to build integrated research and extension programs that combine drones\, spectral sensing\, and environmental monitoring to support safe\, resilient\, and technology-enabled agriculture. \nHosted by: Professor Marco Rolandi\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/96727838511?pwd=1Qzl9HTV3G2BxaSEG8GeKOPZVu2NWj.1
URL:https://events.ucsc.edu/event/ece-seminar-researcher-in-agricultural-sensing-remote-sensing-and-applied-ai/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260518T104000
DTEND;TZID=America/Los_Angeles:20260518T114500
DTSTAMP:20260514T225630Z
CREATED:20260514T225630Z
LAST-MODIFIED:20260514T225630Z
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SUMMARY:ECE 290 Seminar: AI for Enhancing Power Grid Resilience Against Extreme Weather Events
DESCRIPTION:Presenter: Masood Parvania\, Roger P. Webb Endowed Professor\, University of Utah \n  \nDescription: Many communities across the world are experiencing more frequent and severe extreme weather disturbances such as wildfires\, heatwaves\, drought\, storms\, rising sea levels\, and flooding\, which not only pose threats to human health\, and the environment but also affect the ability of the power grid to continue powering the communities. This requires upgrading the operation of power grid from passive and manual applications to making complex decisions in real-time to facilitate the automated recovery of the system after major disturbances. This talk will review the application of various AI and ML techniques for detection\, response and mitigation of cyber anomalies and extreme weather events in power distribution systems.\n \n  \nBio: Masood Parvania is the Roger P. Webb Endowed Professor of Electrical and Computer Engineering and the Director of Utah Smart Energy Laboratory (U-Smart) at the University of Utah. Dr. Parvania is the Principal Investigator and Director of the U.S.-Canada Center on Climate-Resilient Western Interconnected Grid (NSF WIRED Global Center)\, co-funded by U.S. National Science Foundation (NSF) and Natural Sciences and Engineering Research Council of Canada (NSERC). He is also the Founder and President of the Energy-AI company\, Grid Elevated\, which specializes on developing and commercializing AI technology for resilient and efficient power grid operation. \n  \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-ai-for-enhancing-power-grid-resilience-against-extreme-weather-events/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260518T100000
DTEND;TZID=America/Los_Angeles:20260518T110000
DTSTAMP:20260514T203152Z
CREATED:20260514T195027Z
LAST-MODIFIED:20260514T203152Z
UID:10014638-1779098400-1779102000@events.ucsc.edu
SUMMARY:ECE Seminar: From Plumes to Produce: Leveraging Atmospheric Modeling and Smart Sensing for Food Safety
DESCRIPTION:Presenter: Derek Hollenbeck\, postdoctoral research scholar\, University of California\, Merced  \nDescription: Advances in drone-based environmental sensing\, atmospheric modeling\, and intelligent monitoring systems are creating new opportunities for addressing emerging challenges in food safety and agricultural resilience. This talk explores how methodologies originally developed for methane emission detection and quantification could be translated toward agricultural and food safety applications. The presentation begins with an overview of research experiences in autonomous sensing and environmental monitoring\, including work associated with the inaugural CITRIS Aviation Prize before outlining some key potential areas for food safety with drones. Then\, the talk overviews previous research on the topics related to drone-based environmental monitoring\, Digital Twins\, and Smart Sensing – with a focus on methane emission source quantification\, atmospheric transport modeling of a point source\, and inverse problem methodologies for real-time parameter estimation. Finally\, the talk examines how these concepts may be adapted to food safety research questions\, as well as highlight opportunities for interdisciplinary collaboration alongside emerging priorities from organizations and certification frameworks. \nBio: Derek Hollenbeck is a postdoctoral research scholar at the University of California\, Merced (UCM)\, where he serves as the manager of the Center for Methane Emissions Research and Innovation (CMERI) under the supervision of Dr. YangQuan Chen. He earned his B.Sc. (2016) and Ph.D. (2023) in Mechanical Engineering from UCM\, where he conducted research in the Mechatronics Embedded Systems and Automation (MESA) Lab.\n \nHis work sits at the intersection of fluid mechanics\, controls\, dynamics\, and inverse problems\, with a focus on developing intelligent environmental monitoring systems using small unmanned aerial systems (sUAS). His research integrates machine learning and physics-based modeling to detect\, localize\, and quantify methane emissions in complex environments.\n \nDr. Hollenbeck is the author of Smart Sensing with Digital Twins: Methane Emission Source Determination with sUAS\, which presents a framework for combining digital twins\, inverse modeling\, and autonomous sensing to improve environmental observability. His work emphasizes how data-driven and physics-informed approaches can be fused to optimize sensor placement\, enhance estimation accuracy\, and enable real-time decision-making in single/distributed mobile sensing systems. \nHosted by: Professor Marco Rolandi\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/96727838511?pwd=1Qzl9HTV3G2BxaSEG8GeKOPZVu2NWj.1
URL:https://events.ucsc.edu/event/ece-seminar-from-plumes-to-produce-leveraging-atmospheric-modeling-and-smart-sensing-for-food-safety/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260514T090000
DTEND;TZID=America/Los_Angeles:20260514T110000
DTSTAMP:20260427T162920Z
CREATED:20260427T162713Z
LAST-MODIFIED:20260427T162920Z
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SUMMARY:Shadmon\, R. (CS) - Proximal Byzantine Agreement
DESCRIPTION:Research on fault-tolerance protocols for approximate Byzantine agreement\n(ABA) has largely focused on ensuring that distributed processes remain\nconsistent despite fewer than 1/3 faulty processes. Yet in many\nreal systems\, consistency is only useful when it enables processes to\nmake accurate decisions from replicated\, noisy\, and potentially\nadversarially corrupted data relative to an ideal fault-free baseline.\nThis limitation is increasingly important in edge applications such as\nautonomous vehicles\, drone networks\, smart cities\, manufacturing\, and\nsensor-based systems\, where agreement directly drives downstream\nactions. At the same time\, many existing ABA protocols impose\nimpractical requirements\, such as replica counts that grow with data\ndimensionality or prior knowledge of the maximum distance between values\nproposed by each process. \nWe introduce Stochastic Byzantine Agreement (SBA)\, a new problem\nformulation in which the goal is to estimate an output from n replicated\nvalues consisting of n-f nonfaulty outputs generated by an\nunderlying stochastic process and f arbitrarily chosen\nByzantine outputs. We then present Proximal Byzantine Agreement\n(PBA)\, a stochastic agreement protocol that solves SBA by enabling\nconsumers to infer the most likely ideal output conditioned on the\noutputs they receive. In addition\, PBA provides a region\nguarantee that\, as we prove\, always contains the corresponding\nfault-free stochastic estimate of the true value. \nWe describe the design of PBA\, formalize its guarantees\, and evaluate\nits accuracy against existing techniques using stochastic simulations\nacross symmetric and asymmetric distributions and multiple system\nconfigurations. We also evaluate runtime overhead and performance in a\nfollow-the-leader drone network simulator and in a Java implementation on\nRaspberry Pis using a real-world adaptive cruise control dataset. Our\nresults show that PBA performs competitively across all evaluated\nsettings and especially well under simulated Byzantine attack. Most\nnotably\, PBA maintains stable accuracy as dimensionality increases\,\noutperforming methods that require up to 10x more replicas}\nand incur up to 10x greater computation time per agreement\ndecision. \nEvent Host: Roy Shadmon\, Ph.D. Candidate\, Computer Science  \nAdvisor: Owen Arden \nZoom: https://ucsc.zoom.us/j/98390167664?pwd=DwkNuUSRaZRKXYb7pQbDYXgf7HFFPg.1 \nPasscode: pba
URL:https://events.ucsc.edu/event/shadmon-r-cs-proximal-byzantine-agreement/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260513T110000
DTEND;TZID=America/Los_Angeles:20260513T121500
DTSTAMP:20260330T203417Z
CREATED:20260330T203158Z
LAST-MODIFIED:20260330T203417Z
UID:10011814-1778670000-1778674500@events.ucsc.edu
SUMMARY:CSE Colloquium - The EU’s Cybersecurity Framework: what it is\, what it means
DESCRIPTION:Presenter: Chris Jay Hoofnagle\, Frederik Zuiderveen Borgesius\, Lothar Determann\, Pieter T.J. Wolters \nAbstract: \nThe European Union has enacted a comprehensive cybersecurity framework (the “Framework”) that imposes far-reaching obligations on developers of standalone software and connected products. This Article describes the European legislative approach before turning to a description of the Framework. Anchored by the Cyber Resilience Act and the Cybersecurity Act\, and reinforced by a constellation of sector-specific measures\, the Framework effectively creates a California-like-products-liability regime for software. It mandates extensive security-by-design obligations\, imposes stringent conformity assessment and incident-reporting duties\, and shifts substantial compliance burdens onto manufacturers\, importers\, and distributors. It even treats emotional wrongs caused by software as injurious. The Framework will take full effect in December 2027\, meaning that companies must integrate its requirements into their current product cycles. \nBio: Chris Hoofnagle is professor of law in residence at the University of California\, Berkeley\, where he teaches tort law and cybersecurity. \nHosted by: Professor Alvaro Cardenas \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-the-eus-cybersecurity-framework-what-it-is-what-it-means/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260512T100000
DTEND;TZID=America/Los_Angeles:20260512T120000
DTSTAMP:20260421T160759Z
CREATED:20260421T160759Z
LAST-MODIFIED:20260421T160759Z
UID:10013625-1778580000-1778587200@events.ucsc.edu
SUMMARY:Chen\, Q. (CSE) - New Approximation and Online Algorithms using Novel Combinatorial Structures
DESCRIPTION:Most optimization problems face the challenge of computing an optimum solution requiring superpolynomial time. In particular\, they are classified as NP-hard problems that have no polynomial-time algorithm to date. Instead\, computer scientists turn to find an approximate solution and create numerous elegant algorithms. However\, in the modern era\, computational environments have changed drastically\, and we are not able to afford to design new algorithms for each new problem via repeated trial and error. Therefore\, systematic ways to understand the possibilities and limitations of these problems are desired. This dissertation studies several central combinatorial optimization problems\, focusing on understanding the key structural obstacles and developing unified frameworks. Mainly\, we study two types of combinatorial optimization problems:\n(1) Scheduling. The problem is associated with limited resources\, and our target is to find an allocation method to complete all jobs over time that minimizes the overall budget cost.\n(2) Network Design. Different from scheduling problems. In this problem\, we aim to find a minimum-cost topological network that supports routing for demanding communications. \nOur first work is focused on a group-to-group survivable network design problem that generalizes the classic point-to-point network to support routing between any pair of subsets of nodes. Previous research stops at limited faults\, and the difficulty comes from the way to compress the graph into a tree. We propose a new framework via capacitated tree embeddings against arbitrary faults in the network\, which gives the first polylogarithmic approximation algorithm. Further\, this framework captures nearly all the recent models proposed in the area. \nIn contrast to the offline optimization problems mentioned above\, online algorithms are natural adaptations that have been found in tremendous real applications. In online algorithms\, the algorithm wants to compete against arbitrary uncertainty\, which means the instance is unknown at first and revealed over time. We study various scheduling problems and focus on some important metrics – average flow time\, which measures the average time a job stays in the system from its arrival to completion. Real-world demands give online scheduling problems enormously different settings. Computer scientists need to repeat errors and trials to find a provably good solution. We find the key required combinatorial property is supermodularity for the residual objective\, which measures the average completion time for all alive jobs assuming they have the same arrival time. Further\, we relate supermodularity with gross-substitute/linear-substitute (GS/LS)\, which is a well-studied definition in economics. Finally\, we propose a meta-algorithm that solves all captured problems in one shot. In the end\, we revisit the proportional fairness (PF) algorithm for $L_p$-norms of flow time. By reinterpreting the previous potential function and the corresponding Fisher market\, we show that PF is competitive. \n  \nEvent Host: Qingyun Chen\, Ph.D. Candidate\, Computer Science & Engineering  \nAdvisor: Sungjin Im \nZoom: https://ucsc.zoom.us/j/92628493495?pwd=iJq8YwarrYyofPLF4AmZpwzsZnLyvt.1 \n 
URL:https://events.ucsc.edu/event/chen-q-cse-new-approximation-and-online-algorithms-using-novel-combinatorial-structures-2/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260511T123000
DTEND;TZID=America/Los_Angeles:20260511T133000
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SUMMARY:CM Seminar - Robby Ratan\, "Examining AI-Infused Pedagogy in Non-Technical Undergrad Classes: AI-vatars\, Book-bots\, and CompAInions\, Oh My"
DESCRIPTION:Presented by: Rabindra (Robby) Ratan \nDescription: “Novel communication technologies have always presented challenges and opportunities in education. Since my days as a wee assistant professor of media and information\, I have embraced this chaos. In 2015\, I implemented avatar-based discussion forums into my classes to study the Proteus effect (i.e.\, the phenomenon of avatar characteristics influencing user behavior). In 2022\, I began teaching my undergraduate classes in virtual reality to study how this medium enhances classroom engagement. Most recently\, I have been experimenting with AI-integrated assignments\, such as personalized AI-vatar learning assistants\, a book-bot that supports my flipped-classroom model\, and AI companions that help students learn longitudinal research methods. This talk will share some early research findings on these pedagogical AIpproaches\, highlighting potential contributions to theories of media psychology and the broader scholarship of teaching and learning (SOTL).” \nBio: Rabindra (Robby) Ratan (PhD\, USC Annenberg; MA/BA\, Stanford University) is Professor and AT&T Endowed Chair at Michigan State University’s Department of Media and Information\, where he directs the Social and Psychological Approaches to Research on Technology-Interaction Effects (SPARTIE) Lab. His research examines how media technologies (e.g.\, avatars\, AI\, XR) influence meaningful outcomes (e.g.\, learning\, well-being) across societal contexts (e.g.\, education\, health\, industry)\, with particular focus on avatar-mediated communication\, human-AI interaction\, teaching with VR and AI\, and the Proteus effect (i.e.\, avatar characteristics influencing user behaviors). He has published over 85 peer-reviewed articles and his first book\, Avatars: What they are and why they matter\, is forthcoming in late 2026. \nHosted by: Professor Katherine Isbister \nWhen: Monday\, November 3\, 2025 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. \nZoom info: \nhttps://ucsc.zoom.us/j/98277318572?pwd=sv92ivYkB6OjhHrAORcMh5oPHFv8kt.1\nMeeting ID: 982 7731 8572\nPasscode: 235127
URL:https://events.ucsc.edu/event/cm-seminar-robby-ratan-examining-ai-infused-pedagogy-in-non-technical-undergrad-classes-ai-vatars-book-bots-and-compainions-oh-my/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260511T104000
DTEND;TZID=America/Los_Angeles:20260511T114500
DTSTAMP:20260504T160441Z
CREATED:20260504T160441Z
LAST-MODIFIED:20260504T160441Z
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SUMMARY:ECE 290 Seminar: Speaker Asir Intisar Khan - Engineering Heterogeneous Interfaces for Energy Efficient Electronics
DESCRIPTION:Presenter: Asir Intisar Khan\, Assistant Professor in Electrical Engineering and Computer Sciences (EECS)\, University of California\, Berkeley \nDescription: With the rise in global data demands\, energy efficiency in electronics is becoming increasingly important for sustainable progress in AI\, healthcare\, IoT\, and beyond. Emerging technologies\, such as neuro-inspired computing and the 3D integration of logic and memory devices\, offer great promise for overcoming the energy and latency limits of today’s data-intensive applications. Realizing these advances\, however\, require innovations in materials\, transport physics\, and device engineering. In this talk\, I will discuss how atomic-scale engineering and integration of heterogeneous materials and devices can address these intertwined challenges with a few examples from our recent works on (i) engineering heterostructures for low-power memory and high-frequency logic\, (ii) emerging quantum materials for low-resistance interconnects and (iii) nanoscale thermal management strategies. These advances highlight the innovation opportunities in transformative materials and multifunctional nanodevices for 3D-integrated\, energy-efficient electronics. \nBio: Asir Intisar Khan is an Assistant Professor in Electrical Engineering and Computer Sciences (EECS) at the University of California\, Berkeley. He is a faculty scientist in the Materials Science Division at Lawrence Berkeley National Laboratory and serves as a co-director of Berkeley Emerging Technology Research Center. His research focuses on charge\, heat\, and spin transport at nanoscale interfaces of electronic materials to address the energy and latency limits of emerging computing technologies. Khan received his Ph.D. in Electrical Engineering from Stanford University and his BSc from Bangladesh University of Engineering and Technology. His interdisciplinary work has been recognized with the AVS Russell & Sigurd Varian Award\, IEEE Electron Device Society Ph.D. Fellowship\, Materials Research Society Gold Graduate Award\, and several best paper and presentation awards at leading venues\, including the IEEE VLSI\, MRS Fall Meetings\, and the AVS Symposium. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-speaker-asir-intisar-khan-engineering-heterogeneous-interfaces-for-energy-efficient-electronics/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260511T080000
DTEND;TZID=America/Los_Angeles:20260511T100000
DTSTAMP:20260415T202226Z
CREATED:20260415T202034Z
LAST-MODIFIED:20260415T202226Z
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SUMMARY:Johns\, M. (CMPM) - Playing Together in a Co-Designed Future: Building Resilience Through Community-Centered Gameful Design
DESCRIPTION:Complex societal problems (e.g. wicked problems) such as those brought on by climate change can be addressed through a combination of Research through Design (RtD)\, co-design\, and Serious Games (SG) by inviting affected communities to take part in developing iterative\, experimental solutions and exploring their potential impact. In the course of my research\, I have proposed a framework for design research that engages with wicked problems at the community level through gameful design\, which is based on existing literature in HCI drawing from RtD\, co-design\, and SG. Core elements of the framework include supporting diverse perspectives\, interdisciplinarity\, working with local knowledge\, and aligning different concepts with specific gameful elements to support meaningful interactions and discussion. \nIn a specific case study\, my proposed framework is applied to create a gameful intervention to support wildfire resilience in communities at the Wildland-Urban Interface (WUI) which face particular risks from natural hazards. Through a community co-design process\, open discussions have identified consistent pain-points and challenges faced by communities who have experienced wildfires or evacuations\, e.g. traffic congestion in areas with one road in and out\, while also pinpointing differences in their approaches based on local conditions\, such as whether or not to encourage people to evacuate on foot. Through an RtD approach\, important ideas have emerged about how serious games can be utilized in this space. For example\, a common approach to serious game design is to align the win condition of a game with specific learning outcomes or desired changes. However\, when working with wicked problems there are often complex social dilemmas and conflicting values without clear right answers. In these cases there is a need to map dilemmas and trade-offs to game mechanics rather than mapping learning outcomes to win conditions. \nThe gameful intervention developed through this dissertation integrates local knowledge from communities alongside expert knowledge from disciplines including fire science\, social science\, engineering\, and design. The resulting artifact leverages a minigame design to map different concepts to specific and approachable game mechanics. Through universal and inclusive design practices\, the games can be accessible to a broad audience including both children and older adults. The cooperative multiplayer aspects of the games encourage discussion and collaborative play between friends\, community members\, and particularly intergenerational play within families. In addition to contributing RtD reflections as a result of the project\, I also measured change in resilience at the individual and community levels after deployment of the games through qualitative and quantitative methods. This dissertation contributes to knowledge about what game design has to offer to addressing wicked problems\, with specific approaches to better serve communities facing complex risks such as those associated with a rapidly changing climate. \nEvent Host: MJ Johns\, Ph.D. Candidate\, Computational Media  \nAdvisor: Katherine Isbister \nZoom: https://ucsc.zoom.us/j/7959349044?pwd=cVYraU9yMUVwVFhYWHp6T05OZm5rZz09
URL:https://events.ucsc.edu/event/johns-m-cmpm-playing-together-in-a-co-designed-future-building-resilience-through-community-centered-gameful-design/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260506T110000
DTEND;TZID=America/Los_Angeles:20260506T121500
DTSTAMP:20260505T154459Z
CREATED:20260505T154459Z
LAST-MODIFIED:20260505T154459Z
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SUMMARY:CSE Colloquium - The Wallenberg AI\, Autonomous Systems and Software Program
DESCRIPTION:Presenters: Prof. Karl-Erik Arzen (Co-Director of WASP and Lund University)\, Dr. Paul Townend (WASP Graduate School management and Umeå University)\, and Carl Magnus Bruhner (Linkoping University) \nAbstract: The Wallenberg AI\, Autonomous Systems\, and Software Program (WASP) is the largest research initiative in Swedish history\, with a budget of over $700M and a research focus AI and autonomous systems acting in collaboration with humans. The program funds over 500 current PhD students\, has recruited over 70 international faculty\, engages with over 80 companies and organizations\, and has formal agreements with academic organizations including Stanford\, UC Berkeley\, MIT\, Caltech\, ETH Zurich\, and Imperial College London. \nAs part of its internationalization efforts\, WASP has organized a visit to the Bay Area for 13 PhD students and 2 faculty – all of whom specialize in Cloud and AI systems and software. Topics studied by the students include modeling and predicting network dynamics\, verification and accountability in agentic AI systems\, using underwater robotic systems to inspect and maintain subsea data infrastructures\, compliance engineering with the EU AI act\, runtime requirements conflict management in AI-driven autonomous systems\, and cloud-native traffic management for mobile networks. \nBio: The talk will be led by Prof. Karl-Erik Arzen (Co-Director of WASP and Lund University)\, Dr. Paul Townend (WASP Graduate School management and Umeå University)\, and Carl Magnus Bruhner (Linkoping University). We will present the program in detail\, and discuss potential opportunities for collaboration and future research visits from our students. More information on WASP can be found at: https://wasp-sweden.org \nHosted by: Professor Alvaro Cardenas \nDate and Time: Wednesday\, May 6 from 11:00 am – 12:15 pm \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-the-wallenberg-ai-autonomous-systems-and-software-program/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260504T170000
DTEND;TZID=America/Los_Angeles:20260504T190000
DTSTAMP:20260430T221807Z
CREATED:20260410T070115Z
LAST-MODIFIED:20260430T221807Z
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SUMMARY:Analyzing AI Security and Vulnerabilities in the Current Landscape
DESCRIPTION:Interested in careers in AI and cybersecurity? Then don’t miss this highly informative workshop covering today’s most relevant trends in this space. \n  \nIn this 2-part session\, you’ll get expert insight from security leaders at Microsoft. Here’s a breakdown of each part: \n  \nWhen AI Breaks\, Be the One Who Notices\nSpeaker: Raji Vanninathan \nDiscover how AI Security and AI Safety vulnerability research can lead to real‑world impact\, public credit\, and a competitive edge in the current job market. This talk focuses on how students can understand what qualifies as a real AI vulnerability\, how meaningful findings are assessed and validated\, and how responsible disclosure\, CVEs\, and bug bounty programs translate research into recognized impact across the industry We will also explore emerging challenges facing bounty programs as AI-assisted discoveries drivers higher volume and how the signal‑to‑noise problem of “AI slop” is reshaping vulnerability triage and detection. \nReimagining Security for the Agentic AI \nSpeaker: Neta Haiby \nAs AI evolves from tools into autonomous agents that can plan\, act\, and collaborate\, traditional security models start to break down. This session explores how agentic AI changes the rules of trust\, access\, and accountability – introducing challenges like agent sprawl\, permission misuse\, and unintended actions across systems.\nBuilding on foundational AI security concepts\, we’ll dive into practical strategies for securing and governing AI agents covering identity\, access control\, monitoring\, and human oversight. Students will leave with a clear mental model for securing agent-based systems and the skills to think critically about the next generation of AI security architectures. \n  \nDon’t miss this highly relevant and compelling event! And be sure to register as space is limited! \n  \n  \nIf you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \n  \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/analyzing-ai-security-and-vulnerabilities-in-the-current-landscape/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Undergraduate
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260504T104000
DTEND;TZID=America/Los_Angeles:20260504T114500
DTSTAMP:20260501T215119Z
CREATED:20260501T215119Z
LAST-MODIFIED:20260501T215119Z
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SUMMARY:ECE 290 Seminar: Speaker - Dr. Jaeyoung Lim "Autonomous Information Gathering using Long Endurance Aerial Vehicles"
DESCRIPTION:Presenter: Jaeyoung Lim\, Postdoctoral Scholar at the Agile Robotics and Perception Lab at the Electrical Engineering and Computer Science Department\, University of California\, Berkeley \nDescription: Monitoring large-scale environments is essential for natural hazard management\, environmental process observation\, and search and rescue operations. Yes\, meaningful coverage of the target environment demands vast infrastructure and dense sensor networks. Unlike stationary sensors\, robotic systems can navigate autonomously and actively select where measurements are taken. Autonomous systems that can reason on observations would enable efficient\, targeted observation without vast infrastructure requirements.\nIn this seminar\, we explore the challenges of enabling autonomous information-gathering using long-endurance aerial vehicles. Using avalanche monitoring in mountainous terrain as a motivating application\, we examine key problems in information quantification and safe navigation for deploying autonomous systems in complex\, real-world environments. \nBio: Jaeyoung Lim is currently a Postdoctoral Scholar at the Agile Robotics and Perception Lab at the Electrical Engineering and Computer Science Department at the University of California\, Berkeley. He earned his Ph.D. in Robotics at ETH Zurich in 2024\, where he focused on enabling safe navigation and autonomous information gathering using long-endurance aerial vehicles in challenging mountainous environments. Beyond his research\, Jaeyoung is actively involved in the PX4 Autopilot project as a component maintainer for simulation. He received his M.Sc. in Mechanical Engineering from ETH Zurich in 2019 and his B.Sc. in Mechanical and Aerospace Engineering from Seoul National University in 2016. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-speaker-dr-jaeyoung-lim-autonomous-information-gathering-using-long-endurance-aerial-vehicles/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260429T110000
DTEND;TZID=America/Los_Angeles:20260429T121500
DTSTAMP:20260402T185047Z
CREATED:20260402T185047Z
LAST-MODIFIED:20260402T185047Z
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SUMMARY:CSE Colloquium - Towards Safe and Resilient Large-scale Distributed Programming
DESCRIPTION:Presenter: Philipp Haller\, KTH Royal Institute of Technology \nAbstract: \nDistributed programming is notoriously difficult. Not only are distributed systems concurrent\, they pose additional challenges including data consistency and fault tolerance. At the same time\, the share of software systems that are necessarily distributed systems is growing rapidly. As a result\, too many software developers are asked to become distributed systems experts. Thus\, tools and techniques for ensuring the correctness of distributed systems are urgently needed in order to leave this unsustainable trajectory. This talk presents research results towards the design and implementation of programming systems that support emerging applications and workloads; provide reliability and trust; and embrace simplicity and accessibility. Concretely\, the presented work focuses on two directions. \nThe first direction explores a distributed programming model that provides consistency while enabling high availability for workloads operating on join-semilattices without sacrificing partition tolerance. We propose a new consistency protocol\, called observable atomic consistency protocol (OACP)\, which leverages on-demand coordination to support both coordination-free operations as well as totally-ordered operations on replicated data types. We present a formal\, mechanized model of OACP in rewriting logic and verify key correctness properties using the model checking tool Maude. Furthermore\, we present the evaluation of a prototype implementation of OACP based on Akka\, a widely-used actor-based middleware. The second direction explores a programming system that aims to reconcile the scalability and fault tolerance of stream processing systems with the flexibility of the actor concurrency model. The programming system ensures a failure-transparency property\, effectively masking failures through transparent recovery. Our work is the first to formalize failure transparency using a small-step operational semantics\, and to provide proofs of failure transparency for stateful dataflow streaming and a fault-tolerant actor-based programming model. \nBio: \nPhilipp Haller is an Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology in Stockholm\, Sweden. His main research interests are in the design and implementation of programming languages\, type systems\, concurrency\, and distributed programming. He was part of the team that received the 2019 ACM SIGPLAN Programming Languages Software Award for the development of the Scala programming language. Prior to KTH\, he was an early employee at Akka (previously Lightbend\, Inc.)\, a start-up company developing and supporting Scala as well as frameworks for large-scale distributed programming. Prior to Akka\, he was a post-doctoral fellow at Stanford University\, USA\, and at EPFL\, Switzerland. In 2010 he received his PhD in computer science from EPFL\, including a nomination for the 2010 EPFL Doctorate Award. In 2006 he received his Dipl.-Inform. degree from Karlsruhe Institute of Technology (previously University of Karlsruhe)\, Germany. \nHosted by: Professor Mohsen Lesani \nLocation: Engineering 2\, Room E2-180 (Refreshments such as fruit\, pastries\, coffee\, and tea will be provided.) \nZoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-towards-safe-and-resilient-large-scale-distributed-programming/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260427T110000
DTEND;TZID=America/Los_Angeles:20260427T130000
DTSTAMP:20260423T210320Z
CREATED:20260420T225301Z
LAST-MODIFIED:20260423T210320Z
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SUMMARY:Quality First Coding Contest
DESCRIPTION:This is a programming contest\, but with a twist! Instead of scoring you based on your speed and solution accuracy\, we score you based on your programming quality and solution accuracy. This means that instead of looking at how fast you can program a solution\, we look at your number of compiles/runs instead.* The contestant that uses the least number of compiles/runs to produce passing code is the winner. Ties are broken by time. \nFood will be provided. QFCC 20260427 – Poster
URL:https://events.ucsc.edu/event/quality-first-coding-contest/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260427T104000
DTEND;TZID=America/Los_Angeles:20260427T114500
DTSTAMP:20260423T164929Z
CREATED:20260423T164929Z
LAST-MODIFIED:20260423T164929Z
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SUMMARY:ECE 290 Seminar: Speaker Luat T. Vuong - Biospeculative approaches to the “needle in a haystack”: vortex encoders and hybrid optical neural-networks
DESCRIPTION:Presenter: Luat Vuong\, Associate Professor in Mechanical Engineering\, UC Riverside \nDescription: Given the growing computational demands of machine learning\, how can we scale approaches for sifting through large volumes of data—including patterned or delayed information embedded as “noise”? Many computer vision applications have a strict power budget and demand robust\, rapid-response\, and even real-time image processing. In this talk\, I’ll describe our “biospeculative” approaches to efficiently offload traditional computer vision tasks to diffractive optics. Such hybrid approaches leverage the benefits of preprocessing optics and shallow electronic algorithms. With optics\, we spatially encode multiple dimensions of light (color\, polarization) and decode with simple\, back-end neural networks. I will focus the discussion on the role of encoding from vortex optical singularities. With vortex and multi-vortex encoders\, we identify sparse and reconstruct low-signal features\, tracking the “needle in a haystack”. \nBio: Luat Vuong is currently Associate Professor in Mechanical Engineering at UC Riverside\, with cooperating faculty memberships in Physics\, Electrical and Computer\, and Materials Science and Engineering. She is also affiliate faculty in Robotics and at the Center for Environmental Research and Technology. She is trained as an optical applied physicist\, received her undergrad at UC Berkeley\, PhD at Cornell University. She is a recipient of the 2007 Fulbright Fellowship (which she took at the Technical University of Delft in The Netherlands)\, 2010 European Council MC-IIF Global Postdoctoral Fellowship (which she took at the Institute of Photonic Sciences in Spain)\, 2012 NSF Career Award\, a 2016 J-FRASE\, Sloan- funded Award\, the 2019 DARPA Young Faculty Award\, and the 2021 DARPA Director’s Fellowship. Her research is broadly at the intersection of optics\, nonlinear dynamics\, and data science. \nHosted by: Professor Soumya Bose\, ECE Department \nZoom Link: https://ucsc.zoom.us/j/97975378707?pwd=ljcgaCfhMmhZ88Vt5dqQUBVQRjehOx.1
URL:https://events.ucsc.edu/event/ece-290-seminar-speaker-luat-t-vuong-biospeculative-approaches-to-the-needle-in-a-haystack-vortex-encoders-and-hybrid-optical-neural-networks/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20260424T130000
DTEND;TZID=America/Los_Angeles:20260424T150000
DTSTAMP:20260408T175733Z
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LAST-MODIFIED:20260408T175733Z
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SUMMARY:Zheng\, Z. (STATS) - Semi-Supervised Statistical Learning for Oceanographic Data
DESCRIPTION:Oceanographic data\, generated by modern technologies that measure biological systems across time\, space\, and cell populations\, are often rich\, high-dimensional\, and highly heterogeneous. Such data provide valuable opportunities to study subcellular organization\, cellular heterogeneity\, and dynamic biological processes in marine environments. However\, because marine plankton systems remain relatively understudied and less well characterized than many model biological systems\, both data generation and labeling are particularly challenging. Limited domain knowledge and less mature laboratory protocols often produce noisy observations\, while reliable annotation requires substantial expert effort and is therefore difficult to obtain at scale.\nThis proposal develops statistical methodology for oceanographic data settings in which a small amount of expert-labeled data must be combined with a much larger collection of unlabeled or imperfectly processed data. A central goal is to incorporate limited scientific knowledge into statistical learning procedures to improve interpretability\, component identifiability\, and inferential reliability. In particular\, I develop semi-supervised statistical methods that explicitly quantify the information contributed by expert annotation.\nTo address this goal\, I study three related problems: semi-supervised functional clustering for subcellular spatial proteomics\, anchored semi-supervised mixture-of-experts models for flow cytometry\, and temporally structured latent-variable models that separate smooth trend and seasonal variation from scientific signals of interest. Together\, these projects aim to develop principled and interpretable methodology for partially labeled\, structured\, and high-dimensional oceanographic data\, with an emphasis on valid uncertainty quantification. \nEvent Host: Ziyue Zheng\, Ph.D. Student\, Statistical Science \nAdvisor: Sangwon Hyun \nZoom: https://ucsc.zoom.us/j/93229540289?pwd=8bsBOSBFmISlexmS4OWTmTZKp420u2.1
URL:https://events.ucsc.edu/event/zheng-z-stats-semi-supervised-statistical-learning-for-oceanographic-data/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260423T170000
DTEND;TZID=America/Los_Angeles:20260423T183000
DTSTAMP:20260410T065806Z
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LAST-MODIFIED:20260410T065806Z
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SUMMARY:Careers in Climate Tech & Sustainability
DESCRIPTION:Ready to explore career pathways that matter? \nAttend our very special Careers in Climate Tech & Sustainability Panel for an inside look at careers that will help build a sustainable future. Panelists representing different roles and organizations will share their career journeys and offer practical insights into working in climate tech. There will also be a catered networking reception that follows\, don’t miss it! \nGet informed\, inspired\, and discover your path to a career in sustainability! \n  \nThis event is part of Baskin Engineering’s Climate Tech Day featuring a community fair where students\, faculty\, climate/sustainability tech companies\, and community organizations will showcase their works through various means like demos\, poster presentations\, and tabling. This will be in the Baskin Courtyard from 2pm – 5pm.  \n  \n  \nIf you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \n  \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/careers-in-climate-tech-sustainability-2/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Undergraduate
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