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DTSTART;TZID=America/Los_Angeles:20261012T104000
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CREATED:20261005T192533Z
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SUMMARY:ECE 290 Seminar: "Photon Counting Detectors for X-Ray Imaging"
DESCRIPTION:Presented by: Jin Zhang\, Chief Engineer @ iRay Group \nDescription: “Photon-counting detectors measure individual X-ray interactions\, enabling fine spatial sampling and energy-resolved imaging. This seminar connects semiconductor signal formation and readout electronics to imaging benefits and practical limitations in medical and industrial applications. It examines charge sharing\, pulse pileup\, calibration drift\, and material decomposition\, then surveys clinical PCCT systems and detector technologies from Siemens\, GE\, Canon\, Varex\, CERN\, DECTRIS\, and iRay. Examples span diagnostic CT\, industrial inspection\, and laboratory and synchrotron measurements. The discussion concludes with research priorities in sensor manufacturing\, high-rate electronics\, module integration\, and quantitative validation. The central question is how to preserve useful spatial and spectral information at realistic flux\, dose\, and throughput\, and demonstrate improvements through fair\, task-specific comparisons.” \nBio: Jin Zhang\, Ph.D.\, is an engineering and R&D leader with more than 20 years of experience in medical imaging\, semiconductor detectors\, and AI-enabled sensing. Currently Chief Engineer at iRay Group\, he previously held leadership roles at Varex Imaging\, Quanergy\, and PerkinElmer\, leading global teams across North America\, Europe\, and Asia. His expertise spans photon-counting detectors\, image processing\, and bringing advanced imaging technologies into commercial products. He earned his Ph.D. from the University of Rochester and completed postdoctoral research at Stanford University. He has authored more than 40 publications and holds a granted U.S. patent. \n  \nHosted by: Professor Zhicong Yu\, Electrical & Computer Engineering Department \nWhen: Monday\, October 12th from 10:40 to 11:45 AM PST \nLocation: Classroom E2-194
URL:https://events.ucsc.edu/event/ece-seminar-photon-counting-detectors-for-x-ray-imaging/
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:20261015T114000
DTEND;TZID=America/Los_Angeles:20261015T131500
DTSTAMP:20261012T162618Z
CREATED:20261012T162215Z
LAST-MODIFIED:20261012T162618Z
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SUMMARY:BME 280B Seminar: Dr. Kiley Graim "Beyond the Majority: Correcting for Genetic Ancestry Bias in Disease Genomics"
DESCRIPTION:Welcome to the 3rd week of our BME 280B seminar series\, a weekly seminar covering topics of current research in computational biology and bioinformatics. \nOpen to all\, food is provided. Class enrollment is not required. \nPlease join us this week to learn more about the works of Dr. Kiley Graim: \n  \nPresenter: Dr. Kiley Graim\, Assistant Professor of Computer & Information Science & Engineering\, University of Florida \nDescription: Advances in high-throughput sequencing have transformed disease genomics\, yet persistent sampling biases continue to confound downstream analyses. Omics datasets remain overwhelmingly enriched for individuals of European ancestry\, introducing population stratification that is frequently conflated with disease-relevant signals. This is compounded by the fact that local adaptation has shaped allele frequency distributions differentially across ancestral populations\, producing lineage-specific variants that modulate both disease susceptibility and drug response. AI models often fail to generalize across populations\, exacerbating disparities in precision medicine. I will present approaches for mitigating these confounds by integrating population-scale genomic resources (e.g.\, gnomAD\, 1000 Genomes) with comparative evolutionary genomics across species\, enabling ancestry-aware and cross-species-informed modeling strategies for more generalizable disease genomics. \nBio: Dr. Kiley Graim is an Assistant Professor in the Department of Computer & Information Science & Engineering at the University of Florida. She earned a B.S. and M.S. in Computer Science from Colorado State University and a Ph.D. in Biomolecular Engineering from the University of California\, Santa Cruz\, followed by postdoctoral training at the Simons Foundation and Princeton University. Her research combines biology\, genomics\, and computer science to develop multi-omic artificial intelligence methods for identifying the molecular drivers of human disease. Her lab’s research spans cancer evolution across mammalian species\, precision medicine\, equitable AI\, and sepsis. \nHosted by: Professor of Biomolecular Engineering\, Dr. Benedict Paten
URL:https://events.ucsc.edu/event/bme-280b-seminar-101526/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261015T160000
DTEND;TZID=America/Los_Angeles:20261015T170000
DTSTAMP:20261012T195741Z
CREATED:20261012T193244Z
LAST-MODIFIED:20261012T195741Z
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SUMMARY:Statistics Seminar: A Latent Factor Multivariate Point Process Model for Inferring the Neural Code
DESCRIPTION:Presenter: Reza Ramezan\, Associate Professor\, Teaching Stream (Research Active)\, University of Waterloo \nDescription: Neural spike trains are electrochemical signals that are localized in time and serve as the primary means of communication among nerve cells. The analysis of simultaneously recorded spike trains from multiple neurons presents substantial statistical and computational challenges. In this talk\, I will introduce a biologically inspired multivariate point process model for analyzing such data\, formulated as a continuous-time latent factor model (LFM). To the best of our knowledge\, this is the first continuous-time multivariate LFM developed to investigate neuronal interactions and functional connectivity using neural spike trains. By leveraging the computational advantages of approximate Bayesian inference\, I will demonstrate that the proposed model can accommodate larger neuronal ensembles than existing methods\, thereby providing an efficient framework for studying population coding. I will also discuss an application to experimental data from a classical conditioning study of the rat prefrontal cortex\, illustrating how the proposed approach can enhance our understanding of the neural encoding of cue and outcome values. \nAbout the speaker: Reza Ramezan is an Associate Professor\, Teaching Stream (Research Active)\, in the Department of Statistics and Actuarial Science at the University of Waterloo\, where he is also a core member of the institution’s Centre for Theoretical Neuroscience. His methodological research focuses on developing computationally efficient stochastic\, multivariate\, and high-dimensional models\, with applications in neuroscience. Reza earned his PhD in Statistics from the University of Waterloo in 2014. He subsequently joined the Department of Mathematics at California State University\, Fullerton\, before returning to Waterloo in 2017. He has received numerous awards and recognitions for his teaching and research. His professional leadership includes serving as the former President of the Business and Industrial Statistics Section of the Statistical Society of Canada. \n\n\n \n\n\n\nThis seminar is hosted by Professor Yunyi Shen
URL:https://events.ucsc.edu/event/statistics-seminar-a-latent-factor-multivariate-point-process-model-for-inferring-the-neural-code/
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:20261016T144000
DTEND;TZID=America/Los_Angeles:20261016T154500
DTSTAMP:20261016T153215Z
CREATED:20261014T172120Z
LAST-MODIFIED:20261016T153215Z
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SUMMARY:CSE Colloquium: From Syntax to Taste
DESCRIPTION:Presenter: Titus Winters\, Adobe \nAbstract: \nComputing education has long emphasized intelligence\, knowing how a thing works\, over wisdom\, knowing when to use it. We teach syntax\, functional correctness\, and the internals of classic data structures\, while giving students little guidance on tradeoffs\, quality\, and judgment. Generative AI makes this old critique urgent: source code is becoming a secondary artifact\, and competent implementation is available on tap. This talk argues that the skills now at a premium are design before code generation and testing after it\, both of which rest on conceptual vocabulary\, architectural judgment\, and domain knowledge. It considers what this means for curricula: assuming AI use\, grading process over output\, replacing single-right-answer assignments with open-ended ones\, and deciding what we are willing to stop teaching. Absent that reinvention\, CS risks becoming a service discipline rather than the center of computing education. \nBio:  \nTitus is a Senior Principal Scientist at Adobe\, focusing on Developer Experience. He has served on the C++ standards committee\, chairing the working group for the design and evolution of the C++ standard library. He has also served on the ACM/IEEE/AAAI CS2023 steering committee\, helping set curriculum requirements for Computer Science undergraduate degrees\, focusing on the requirements for software engineering. Titus was a thought leader at Google for many years\, focusing on C++\, software engineering practice\, technical debt\, and culture. He is the lead author for the book Software Engineering at Google. \nHosted by: Professor Daniel Fremont and Professor Leilani Gilpin \nDate and Time: Fridays from 2:40 pm – 3:45 pm \n(The CSE Social will take place after the Colloquium until 5:30 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/95300285113?pwd=62tnEPUtRrsmbW7SHTavaRbaF2afSr.1 \n\n  \n 
URL:https://events.ucsc.edu/event/cse-colloquium-from-syntax-to-taste/
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:20261019T104000
DTEND;TZID=America/Los_Angeles:20261019T114500
DTSTAMP:20261012T193720Z
CREATED:20261012T193634Z
LAST-MODIFIED:20261012T193720Z
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SUMMARY:ECE 290 Seminar: "Photon Counting CT: How Counting X-Ray Photons Enables a Major Advance in Medical Imaging"
DESCRIPTION:Presented by: Adam Wang\, Assistant Professor of Radiology @ Stanford University \nDescription: “Computed tomography (CT) is a mainstay of medical imaging\, but its capabilities are constrained by radiation dose and the information captured by conventional x-ray detectors. Photon-counting CT (PCCT) measures individual x-ray photons and their energies\, creating new opportunities for high-resolution\, low-dose\, and quantitative imaging. Realizing these benefits requires addressing challenges that span detector physics\, system design\, reconstruction\, and image analysis. \nThis talk will introduce the principles of photon-counting CT\, explain how it differs from conventional CT\, and discuss its advantages and practical limitations. These technical benefits are contributing to clinical advancements and applications in neuro\, chest\, cardiac\, abdominal\, and musculoskeletal imaging. Throughout\, I will highlight how engineering choices affect imaging performance and clinical utility\, and discuss ongoing research in translating photon-counting measurements into reliable diagnostic information.” \nBio: Adam Wang\, PhD\, is an Assistant Professor of Radiology and\, by courtesy\, of Electrical Engineering at Stanford University\, where he leads the Advanced X-ray and CT Imaging research group. His research includes photon-counting detectors\, spectral imaging\, and low-dose techniques for x-ray and CT imaging. His group’s work spans imaging system design\, computational modeling\, image reconstruction\, and quantitative image analysis\, with the goal of improving diagnostic information while reducing radiation dose. \n  \nHosted by: Professor Zhicong Yu & Professor Shiva Abbaszadeh\, Electrical & Computer Engineering Department \nWhen: Monday\, October 19th 2026 from 10:40 to 11:45 AM PST \nLocation: Classroom E2-194
URL:https://events.ucsc.edu/event/ece-290-seminar-photon-counting-ct-how-counting-x-ray-photons-enables-a-major-advance-in-medical-imaging/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/10/AdamWang.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261019T123000
DTEND;TZID=America/Los_Angeles:20261019T133000
DTSTAMP:20261013T203230Z
CREATED:20261013T203030Z
LAST-MODIFIED:20261013T203230Z
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SUMMARY:CM Seminar: Professor Jim Whitehead - "Sides Taken: Generative Artists Made by Generative AI"
DESCRIPTION:Welcome to the second Computational Media seminar of the fall quarter. Open to all\, class enrollment is not required. Food will be provided. \nPlease join us in-person at E2-280 or via Zoom to learn more about the works of Professor Jim Whitehead: \n\nTitle: Sides Taken: Generative Artists Made by Generative AI \nPresenter: Dr. Jim Whitehead\, Professor of Computational Media and Associate Dean for the Undergraduate Experience in the Baskin School of Engineering\, University of California\, Santa Cruz \nDescription: Can generative AI be creative? Skeptics call large language models “stochastic parrots” that recombine their training data; others grant them creativity but find it pedestrian; a third camp sees genuinely original work. This talk offers evidence for you to weigh. \nSides Taken is a framework for creating autonomous generative artists. Each artist is endowed with dossiers on a few human artists (among them Vera Molnár\, Jim Campbell\, Okazz\, and Verena Loewensberg)\, notes on craft\, and a contract for its code. When creating an artwork\, the artist is presented with the most recent pieces in its archive and ability to view the rest. The artist has one obligation: every piece must take sides\, writing what it builds upon and what it argues against. When executed\, each artwork creates a time-varying interactive display on a 64×64 pixel LED panel. Each artwork thus exists in three media: an argument\, software\, and a time-varying (interactive) light display. Over time\, artists accumulate a lineage of variations and contrasts\, record lessons learned from their own successes and failures\, and eventually name themselves through an evidence-gated ceremony. \nI will present work by two artists\, Wake (apprentice name Saccade) and Register (apprentice name Selvedge)\, trace how each developed distinct themes from different influences\, and compare output across language models. Finally\, I will observe that Sides Taken performs search without an explicit objective function\, with the use of argumentation against an archive achieving similar goals as novelty search. The approach may prove useful well beyond art. \nBio: Jim Whitehead is a Professor of Computational Media and Associate Dean for the Undergraduate Experience in the Baskin School of Engineering. Jim leads the Augmented Design Lab which explores generative art\, mixed-initiative co-creative systems\, and procedural content generation. Within Baskin Engineering\, Jim has helped create the Slugworks creatorspace\, and the Experiential Learning Program which holds the Pathways to Research and Lead By Design/Early Design-Build programs. Jim received his PhD from UC Irvine in 2000 with a dissertation on hypertext versioning. \n\n\nZoom Link: https://ucsc.zoom.us/j/94103955103?pwd=od4ueavRt06ECpwAwqvgofwn5Suyal.1Meeting ID: 941 0395 5103 \nPasscode: 124806
URL:https://events.ucsc.edu/event/cm-seminar-101926/
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:20261019T160000
DTEND;TZID=America/Los_Angeles:20261019T170000
DTSTAMP:20260921T164141Z
CREATED:20260921T164141Z
LAST-MODIFIED:20260921T164141Z
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SUMMARY:Statistics Seminar: Advancing Science on the Sea and Stars with Modern Statistical Techniques
DESCRIPTION:Presenter: J. Xavier Prochaska\, Professor\, UC Santa Cruz \nDescription: I will present two current and challenging research problems from the domains of astrophysics and oceanography which are leveraging standard Bayesian methods. After describing the datasets\, scientific goals\, and currently methodology\, I will welcome a discussion on ways to improve\, advance\, and/or replace the current approaches. Ideally within the realm of tradiational/modern statistics\, but I will welcome soluation with machine learning/AI approaches. I will then conclude by describing forthcoming\, large datasets that could leverage expertise from members of the Department of Statistics. For those who wish a preview of the data and current techniques\, I will circulate a README a day or two in advance of the seminar. \nAbout the speaker: PhD Physics — UC San Diego; Professor Astronomy & Astrophysics and Ocean Sciences — UC Santa Cruz \n\n\n\n\n\nThis seminar is hosted by Professor Yunyi Shen.
URL:https://events.ucsc.edu/event/statistics-seminar-advancing-science-on-the-sea-and-stars-with-modern-statistical-techniques/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261019T160000
DTEND;TZID=America/Los_Angeles:20261019T170000
DTSTAMP:20260922T181210Z
CREATED:20260922T181210Z
LAST-MODIFIED:20260922T181210Z
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SUMMARY:AM Seminar: Analysis of Flagellar Gait Changes Across Fluid Viscosities
DESCRIPTION:Presenter: Dr. Kelli Gutierrez\, CSU Monterey Bay \nDescription: Many microswimmers propel themselves using flagella\, which are thin\, threadlike filaments that beat in a periodic wavelike motion. The flagellar beat emerges from the coupled interactions between the surrounding fluid and the active and passive responses of the flagellum. Previous studies have observed the qualitative shape of the flagellar waveform and the swimming speed to change with fluid viscosity. We quantify changes in the flagellar waveforms of \textit{Chlamydomonas reinhardtii} in response to changes in fluid viscosity using (i) shape mode analysis and (ii) a full swimmer simulation to analyze how shape changes affect the swimming speed. By decomposing the gait into the time‑independent mean shape and the time‑varying stroke\, we find that the time-independent mean shape changes substantially in response to viscosity\, while the changes in the time-varying stroke are more subtle. \nAbout the speaker: Dr. Gutierrez received her Ph.D. in Applied Mathematics from UC Davis. She joined the Department of Mathematics and Statistics Department at Cal State Monterey Bay in 2026. Her research interests include mathematical biology\, fluid dynamics\, and applied mathematics. \nThis seminar is hosted by Applied Mathematics.
URL:https://events.ucsc.edu/event/am-seminar-analysis-of-flagellar-gait-changes-across-fluid-viscosities/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261019T180000
DTEND;TZID=America/Los_Angeles:20261019T193000
DTSTAMP:20261006T165803Z
CREATED:20260917T183243Z
LAST-MODIFIED:20261006T165803Z
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SUMMARY:North Stars of Emancipation: Navigating Movements and Institutions to Change Food Systems
DESCRIPTION:Dr. Antonio Roman-Alcalá has been participating in food and farming movements in California for over two decades. He’s founded urban farms\, taught organic horticulture\, and made documentary films about why food systems continue to be unsustainable.  \nMore recently\, he’s turned towards participatory\, movement-based research to develop an understanding of what “emancipation” might mean for those who’ve long faced the brunt of food systems injustices\, especially in a context of rising right wing\, racist politics at the national level. \nThe result is North Stars of Emancipation: California’s Diverse Food and Farming Movements in Times of Racial Reckoning\, Antonio’s book now out on MIT Press. You can find info on the book here. \nThe book describes a shift in recent decades of US food movement politics – driven by the greater inclusion and influence of people of color – towards more radical political ideals of anti-capitalism and anti-colonialism\, and skepticism of the state as a tool for emancipation. North Stars tackles questions of social movement convergence amidst the recent right wing rise\, and offers strategic and scholarly lessons based on decades of experience and analysis. \nCome join Antonio in conversation with other thinkers and doers\, about organizing for food systems transformation\, fraught times of political regression\, reckoning with legacies of racism\, and holding onto radical visions for a world otherwise. \nFeaturing: \nLeonard Diggs\, Long time Farmer and Educator\nMireya Gomez-Contreras\, Esperanza Farms\, Community Farm in Watsonville\nMaywa Montenegro de Wit\, Critical agrarian studies scholar at UCSC
URL:https://events.ucsc.edu/event/north-stars-of-emancipation-navigating-movements-and-institutions-to-change-food-systems/
LOCATION:Hay Barn\, 94 Ranch View Road\, Santa Cruz\, CA\, 95064\, United States
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261023T144000
DTEND;TZID=America/Los_Angeles:20261023T154500
DTSTAMP:20261016T153543Z
CREATED:20261015T174218Z
LAST-MODIFIED:20261016T153543Z
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SUMMARY:CSE Colloquium: Relational Attention for Data-Efficient Language Modeling
DESCRIPTION:Title: Relational Attention for Data-Efficient Language Modeling \nPresenter: Adrian Brasoveanu\, UCSC Linguistics (Joint work with Ece Takmaz and Jakub Dotlačil) \nAbstract: We present Relational BabyLM\, a system submission to the BabyLM 2026 challenge that combines two cognitively motivated inductive biases in a single decoder-only Transformer. Architecturally\, we replace standard self-attention with a Dual Attention Transformer (DAT)\, which separates the routing of object-level (“sensory”) lexical features from structural/relational information (Altabaa and Lafferty\, 2025; Altabaa et al.\, 2024; Webb et al.\, 2024; Kerg et al.\, 2022; Webb et al.\, 2021). Relational attention (RA) disentangled from self-attention greatly increases data efficiency and out-of-training-sample generalization on purely relational tasks\, but language modeling requires object-level and relational information to be integrated as well as disentangled\, and RA-based LMs have remained largely unexplored. BabyLM’s data-constrained training and comprehensive evaluation is an ideal testing ground for whether that data efficiency transfers. As a training intervention\, we add a Next-Latent Prediction (NextLat; Teoh et al. 2026) objective that encourages hidden states to compress history incrementally into a dense belief state. Architecture is the dominant factor for structural linguistic generalization; the objective is secondary but still significant. DAT’s three relational attention types (full RA vs. the simpler RCA and DisRCA variants) are largely interchangeable at 10M words; full RA pulls ahead at 100M. We also introduce a novel symbol-retrieval mechanism (RoPE-based\, as opposed to learned\, relative symbols) that matches learned symbol libraries while adding no parameters. On the strict (100M-word) track\, our best model ranks 6th of 55 overall and 3rd of 55 on the leaderboard’s NLP-task subset at the time of writing; our two strongest models outperform the GPT-2 baseline on most benchmarks\, with one attaining the highest EWoK score among strict-track entries. \nPaper: https://arxiv.org/abs/2609.20530 \nCode: https://github.com/abrsvn/babylm_dat_2026 \nBio: I am a  professor in computational (psycho)linguistics focusing largely on natural language semantics and pragmatics at UCSC. I was also associate campus provost (tout court for 2 years\, then of strategic initiatives for 1 year) in the UCSC EVC office between 2021 and 2024.  For some more of my recent work\, see https://github.com/abrsvn/. \nHosted by: Professor Daniel Fremont and Professor Leilani Gilpin \nDate and Time: Fridays from 2:40 – 3:45 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/95300285113?pwd=62tnEPUtRrsmbW7SHTavaRbaF2afSr.1
URL:https://events.ucsc.edu/event/cse-colloquium-relational-attention-for-data-efficient-language-modeling/
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:20261030T103000
DTEND;TZID=America/Los_Angeles:20261030T120000
DTSTAMP:20261009T184943Z
CREATED:20261009T184943Z
LAST-MODIFIED:20261009T184943Z
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SUMMARY:ECE Special Seminar: "Bilevel Optimization for Agentic AI: From Theory to Retrieval-augmented Agentic Reinforcement Learning"
DESCRIPTION:Presented by: Quan Xiao\, PhD Candidate @ Cornell University \nDescription: “Agentic AI systems combine large language models with system-level design choices such as post-training data selection\, retrieval\, tool use\, and memory management in augmented inference. Training these systems involves multiple coupled objectives beyond task success\, including safety\, retrieval quality\, and adaptation efficiency. Sequential tuning can cause catastrophic forgetting\, while direct objective mixing training can introduce unit mismatch and obscure credit assignments across components. \nIn this talk\, I will present bilevel optimization as a framework for jointly learning LLM parameters and agentic-system design variables. I will introduce an efficient first-order penalty formulation that replaces lower-level optimality with a merit constraint\, avoiding Hessian inverses and differentiation through full inner trajectories. By turning the bilevel problem into a penalized objective with analyzable structure\, this formulation enables landscape analysis that leads to global convergence guarantees. \nI will conclude with an application to bilevel retrieval optimization for tool-using agents\, where retrieval enables LLMs to access up-to-date information and manage external memory. In this setting\, landscape analysis also guides the design of memory-efficient variants of the penalty method tailored to the application. Experiments on multi-hop and medical question-answering tasks demonstrate the effectiveness of jointly optimizing retrieval and the LLM. Using only a 3B LLM backbone\, the proposed approach outperforms direct inference with GPT-5.6 Luna\, as well as methods based solely on agentic reinforcement learning or retrieval optimization.” \nBio: Quan Xiao (https://jenniferquanxiao.github.io) is a Ph.D. candidate in the Department of Electrical and Computer Engineering at Cornell University. She received her M.S. in Electrical Engineering from Rensselaer Polytechnic Institute in 2023\, and her B.S. in statistics from the University of Science and Technology of China in 2020. Her research focuses on the theoretical foundations of bilevel and multi-objective optimization\, as well as their applications to generative\, agentic AI and hardware-algorithm co-design. Her work has appeared in leading machine learning and signal processing venues\, including NeurIPS\, ICML\, and IEEE Transactions on Signal Processing\, with papers selected for oral and spotlight presentations. \nQuan has received several awards\, including the IEEE Signal Processing Society Scholarship in 2024 and the Belsky Award for Computational Sciences and Engineering in Rensselaer Polytechnic Institute in 2023. Her research has also received supports from industries\, including Google and Lambda Research. \n  \nHosted by: Professor Yu Zhang\, Electrical & Computer Engineering Department \nWhen: Friday\, October 30th from 10:30AM to 12:00PM \nLocation: Engineering 2\, Room 506
URL:https://events.ucsc.edu/event/ece-special-seminar-bilevel-optimization-for-agentic-ai-from-theory-to-retrieval-augmented-agentic-reinforcement-learning/
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:20261102T160000
DTEND;TZID=America/Los_Angeles:20261102T170000
DTSTAMP:20261008T203351Z
CREATED:20260921T170456Z
LAST-MODIFIED:20261008T203351Z
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SUMMARY:Statistics Seminar: Sliced Optimal Transport: From Acceleration to Bayesian Modeling
DESCRIPTION:Presenter: Enter the speaker’s name\, title\, and institution at the top of the event \nDescription: Optimal transport (OT) provides a principled way to match\, compare\, and interpolate distributions\, but its computational cost limits its use at realistic scales. I will present our recent work on reducing that cost and on using OT for statistical modeling and inference. In the first part of the talk\, I will briefly introduce optimal transport and sliced optimal transport (SOT). I will then present sliced-regularized OT\, which uses a cheap sliced plan as an informative prior for approximating the full plan\, yielding an efficient approximate OT solver. In the second part\, I will show how SOT enables new applications in statistical inference. In particular\, I will introduce distributional determinantal point processes\, which use SOT geometry to place repulsive priors on distributions\, giving a Bayesian model for clustering distributional data. Applications include image processing and the clustering of single-cell and epilepsy data. \nAbout the speaker: Dr. Khai Nguyen is an Assistant Professor in the Department of Statistics and Data Science at Texas A&M University. He received his Ph.D. in Statistics from the University of Texas at Austin and his B.Sc. in Computer Science from Hanoi University of Science and Technology. His research develops computational optimal transport\, particularly sliced methods that make large-scale transport tractable. He brings these tools to problems in machine learning and geometric data processing\, as well as to Bayesian approximate inference and nonparametric models for distributional data. \nThis seminar is hosted by Professor Yunyi Shen.
URL:https://events.ucsc.edu/event/am-seminar-sliced-optimal-transport-from-acceleration-to-bayesian-modeling/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261102T160000
DTEND;TZID=America/Los_Angeles:20261102T170000
DTSTAMP:20261001T175836Z
CREATED:20261001T175836Z
LAST-MODIFIED:20261001T175836Z
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SUMMARY:AM Seminar: Data Analysis Workflow from Low-Code Tools to Generative and Agentic AI
DESCRIPTION:Presenter: Reza Fazel-Rezai\, Senior Science and Education Application Engineer\, MathWorks \nDescription: Please join us to learn how to accelerate data analysis using a workflow that spans low-code tools\, Generative AI\, and Agentic AI. Through live demonstrations and practical examples\, you’ll see how to import\, explore\, visualize\, model\, and process data using interactive tools that require minimal coding. The session will demonstrate how these tools can automatically generate reproducible MATLAB code\, how Generative AI can assist with code creation\, explanation\, and troubleshooting\, and how Agentic AI workflows can help plan\, execute code\, validate results\, diagnose issues\, and iteratively refine outcomes. Highlights: – Build a data analysis workflow using low-code and interactive tools. – Use Generative AI to support code generation\, explanation\, and troubleshooting. – Explore how Agentic AI can plan analysis steps\, run code\, test results\, diagnose errors\, and iterate toward reliable outcomes. \nAbout the speaker: Dr. Reza Fazel-Rezai\, with a Ph.D. and MS in Biomedical Engineering and a BS in Electrical Engineering\, brings over two decades of experience in both industry and academia. As a senior research scientist\, research team manager\, and the founding Director and tenured full Professor of Biomedical Engineering\, he has extensive expertise and background in the field. Dr. Fazel-Rezai has authored more than 200 scientific publications\, edited and published seven books\, and pursued diverse research interests in biomedical signal and image processing\, particularly through machine learning and deep learning methods. Passionate about leveraging and sharing his skills to help others achieve their goals\, he currently serves as an ABET PEV for Biomedical Engineering\, works part-time as an instructor at UC San Diego\, and is a full-time Senior Science and Education Application Engineer at MathWorks. \nThis seminar is hosted by Professor Pascale Garaud.
URL:https://events.ucsc.edu/event/am-seminar-data-analysis-workflow-from-low-code-tools-to-generative-and-agentic-ai/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261109T160000
DTEND;TZID=America/Los_Angeles:20261109T170000
DTSTAMP:20261007T210443Z
CREATED:20261007T210443Z
LAST-MODIFIED:20261007T210443Z
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SUMMARY:AM Seminar: Enhanced Resolution Imaging in Strongly Scattering Media
DESCRIPTION:Presenter: Chrysoula Tsogka\, Professor\, Applied Mathematics\, UC Merced \nDescription: In a strongly scattering medium\, waves undergo multiple scattering that is usually seen as an obstacle to imaging. Time-reversal experiments show the opposite: waves re-emitted into the medium refocus on their source more sharply than in a homogeneous medium\, because scattering makes the array appear larger than it is. This effect\, known as super-resolution\, is not available to conventional imaging. Since the medium through which the waves travelled is unknown\, conventional methods back-propagate the data in an approximation of the true background. In this talk I will show how super-resolution can be achieved in imaging when abundant array data are available. The key idea is to learn the Green’s functions of the unknown random medium directly from the data using sparse dictionary learning. The Green’s functions are recovered as unordered columns of the sensing matrix. To associate each column with its location in the imaging window\, we build a graph from cross-correlations of the recovered columns and apply multidimensional scaling to the resulting proxy distances. The learned Green’s functions are then used to form images by back-propagation or by $\ell_2$ and $\ell_1$ methods\, with resolution beyond the homogeneous medium limit. I will also discuss recent extensions: a new dictionary learning algorithm that starts from a random initialization\, imaging on unstructured grids\, and imaging through changing random media. Joint work with M. Moscoso\, A. Novikov\, G. Papanicolaou\, A. Christie\, M. Leibovich and J. Zheng. \nAbout the speaker: Chrysoula Tsogka is a Professor of Applied Mathematics at the University of California\, Merced\, where she also serves as Chair of the Applied Mathematics Graduate Group. She received her Ph.D. in Applied Mathematics from the University Paris IX Dauphine and was a Postdoctoral Fellow at Stanford University. Before joining UC Merced in 2019\, she was a tenured CNRS researcher at LMA in Marseille\, an Assistant Professor at the University of Chicago\, and a Professor at the University of Crete. Her research focuses on numerical methods for direct and inverse wave propagation problems and on imaging in complex media. Her recent work includes quantitative synthetic aperture radar (SAR) imaging for the detection and classification of buried landmines\, and data-driven methods\, such as dictionary learning\, for super-resolution imaging in strongly scattering media. She serves on the editorial boards of Inverse Problems\, the Journal of Computational Physics and the Journal of Mathematical Imaging and Vision.
URL:https://events.ucsc.edu/event/am-seminar-enhanced-resolution-imaging-in-strongly-scattering-media/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261116T153000
DTEND;TZID=America/Los_Angeles:20261116T170000
DTSTAMP:20260922T180840Z
CREATED:20260917T185033Z
LAST-MODIFIED:20260922T180840Z
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SUMMARY:Fall Slow Seminar: The Range of the River by Iftekhar Iqbal
DESCRIPTION:UCSC’s Center for Southeast Asian Coastal Interactions (SEACoast)  and the  Center for South Asian Studies  invite you to join us for a Slow Seminar to discuss Iftekhar Iqbal’s   The Range of the River: Asia’s Great River Systems and the Making of a Transregional World  on  Monday\, November 16\, 2026 from 3:30-5:00pm PST in Room 210\, Humanities 1. \nSpanning nearly four million square kilometers across eastern South Asia\, mainland Southeast Asia\, and southern China\, the Tibetan river system connects some of Asia’s major waterways\, including the Brahmaputra\, Mekong\, and Yangtze. In The Range of the River\, Iqbal traces the intertwined histories of these rivers and the human and other-than-human forces that have shaped them. The book considers rivers not only as sites of imperial power\, territorial contestation\, and economic activity\, but also as dynamic forces and shared commons that have facilitated movement\, exchange\, commerce\, and cultural encounters across political and geographic boundaries. \nProfessor Anna Tsing (UCSC Anthropology) will facilitate our Slow Seminar to focus on three river systems explored in Iqbal’s book: the Brahmaputra\, Mekong\, and Yangtze. Three scholars including Sanjay Barbora (UCSC Sociology)\, David Biggs (UCR History)\, and Ben Read (UCSC Politics) will offer brief reflections on one river each\, providing distinct disciplinary and regional perspectives before the discussion opens to a broader collective conversation. Our seminar conversation will focus on Chapters 1\, 4\, 6\, and 7 of the book. \nPlease register for the Slow Seminar by filling out this Google Form. Registered guests will receive a PDF copy of selected chapters of The Range of the River via email. \nThis is a Hybrid event. Participants may join in-person at UCSC or by Zoom. The Zoom link will be sent out to registered participants at least 1 hour before the event. \nRegistration will close at midnight on November 15\, 2026. \nNew to Slow Seminars?  Check out SEACoast’s definition here.
URL:https://events.ucsc.edu/event/fall-slow-seminar-the-range-of-the-river-by-iftkhar-iqbal/
LOCATION:Humanities 1 Building\, 257 Cowell-Stevenson Road\, Santa Cruz\, CA\, 95064\, United States
CATEGORIES:Lectures & Presentations,Seminars
ORGANIZER;CN="Center for Southeast Asian Social Interactions":MAILTO:seacoast@ucsc.edu
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261116T160000
DTEND;TZID=America/Los_Angeles:20261116T170000
DTSTAMP:20261015T164013Z
CREATED:20261015T164013Z
LAST-MODIFIED:20261015T164013Z
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SUMMARY:Statistics Seminar: Evolutionary Analysis of Biobank-Scale Data to Study Population History\, Mutation Rates\, Natural Selection\, and the Genetics of Complex Traits
DESCRIPTION:Presenter: Joshua Schraiber\, Research Scientist\, University of Southern California and Cornell University \nDescription: The advent of biobank data has presented an unprecedented opportunity to understand the evolutionary history of the human species. By collecting genotype data from hundreds of thousands of individuals\, we can look closely at recent evolutionary history\, including recent demography\, mutation rates\, and the action of strong natural selection. Moreover\, biobank data with phenotypes enables probing into the details of the genetic architecture of complex traits. However\, the large sample sizes and low frequency alleles found in such datasets often result in violations of common modeling assumptions in population and statistical genetics. To address this gap\, and gain the most possible information out of this data\, I will present biobank-scale evolutionary models. I will first show that ultra-rare mutations often violate the assumption that every mutation only occurred once in the history of the sample. By developing a model that explicitly accounts for recurrent mutation\, we are able to use ultra-rare mutations to learn fine-scale details about recent demography history and mutation rates. We then extended this model to account for natural selection\, and developed a Bayesian approach to share information between genes and learn the distribution of fitness effects at the level of individual genes. Finally\, I will show how rare variants violate the standard assumptions of models of complex trait architecture and demonstrate a modeling approach that can account for effect sizes among rare variants. This will show that the distribution of effect sizes among common variants in the human genome is approximately scale-free. Together\, these findings enhance our understanding of human biology and evolution in the biobank era. \nAbout the speaker: Joshua Schraiber is a Research Scientist working with Doc Edge at USC and Matt Pennell at Cornell University. His background is in evolutionary modeling and statistical methods development. Prior to his current role\, he was a Research Scientist at AncestryDNA and Illumina before returning to academia. \nThis seminar is hosted by Professor Yunyi Shen.
URL:https://events.ucsc.edu/event/statistics-seminar-evolutionary-analysis-of-biobank-scale-data-to-study-population-history-mutation-rates-natural-selection-and-the-genetics-of-complex-traits/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261116T160000
DTEND;TZID=America/Los_Angeles:20261116T170000
DTSTAMP:20261015T165727Z
CREATED:20261015T165630Z
LAST-MODIFIED:20261015T165727Z
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SUMMARY:AM Seminar: Heat Transport and Scalar Dissipation in Turbulent Flows: A Constructive Approach
DESCRIPTION:Presenter: Anuj Kumar\, Assistant Professor\, UC Davis \nDescription: Turbulent flows can transport heat and momentum much more efficiently than pure molecular diffusion alone. What flow structures enable this efficient transport and how can they sustain dissipation when diffusivity or viscosity is small? These questions are fundamental to understanding turbulence and have important applications in engineering. In this talk\, I will discuss a constructive approach to these questions through explicitly designed incompressible flows. We will first consider heat transport between walls held at different temperatures. Under a constraint on the power supply\, I will present a three dimensional branching construction that achieves the optimal heat transport scaling. By examining these designs carefully\, we will identify the physical mechanisms responsible for efficient heat transfer and discuss potential applications\, including the pressing problems of cooling in AI data centers. We will then turn to scalar turbulence. I will introduce a universal incompressible flow built from a carefully organized hierarchy of shear flows and explain how these constructions approach the sharp Obukhov–Corrsin regularity threshold for scalar dissipation. These constructions also exhibit eddy-diffusivity effect: advection mimics diffusion of order one even in the transport equation\, where molecular diffusion is entirely absent. Together\, these examples illustrate how the process of constructing flows that achieve sharp scaling laws can also reveal the mechanisms underlying enhanced transport and dissipation\, which are two key features of turbulence. \nAbout the speaker: Anuj Kumar is an Assistant Professor in the Department of Mathematics at the University of California Davis. His research lies at the intersection of fluid dynamics\, partial differential equations (PDEs) and applied mathematics\, combining computational\, mathematical analysis and theoretical approaches. Prior to joining UC Davis\, he was a Visiting Assistant Professor in the Department of Mathematics at the University of California Berkeley. He earned my Ph.D. in Applied Mathematics from the University of California Santa Cruz in 2023. \nThis seminar is hosted by Professor Pascale Garaud.
URL:https://events.ucsc.edu/event/am-seminar-heat-transport-and-scalar-dissipation-in-turbulent-flows-a-constructive-approach/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261123T160000
DTEND;TZID=America/Los_Angeles:20261123T170000
DTSTAMP:20261007T203353Z
CREATED:20261007T203353Z
LAST-MODIFIED:20261007T203353Z
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SUMMARY:Statistics Seminar: Randomization Posteriors and Generalized Bayesian Inference
DESCRIPTION:Presenter: Edric Tam\, Warren Alpert Fellow in AI and Computational Biology\, Department of Biomedical Data Science\, Stanford University \nDescription: A longstanding question in Bayesian analysis concerns the role of randomization. We introduce randomization posteriors\, a class of generalized Bayesian updates obtained by averaging over an auxiliary randomization law. A particularly relevant instance assigns random weights to the log-likelihood contributions of individual observations\, thereby averaging inference over random perturbations of the dataset. The resulting posterior updates are governed by a fundamental design choice: the stage at which the randomization is averaged out. Averaging at the log-likelihood level recovers the power posterior for a broad class of weight distributions\, while averaging at the posterior level\, under suitable choices of weights\, recovers the bagged posterior. Averaging at the likelihood level yields a new family of generalized Bayesian updates\, which we term contamination posteriors. These are indexed by the cumulant transform of the randomization law and require a reference density for well-posedness. For Bernoulli weights\, they recover classical Huber-type contamination models\, while Beta and other weight distributions produce new generalized posteriors. We characterize the theoretical properties of randomization posteriors and illustrate their empirical robustness through simulations and experiments. We also discuss connections with bootstrap methods\, coarsened posteriors\, and other generalized Bayesian updating procedures. \nAbout the speaker: Edric (Ed) Tam is a postdoctoral fellow at the Department of Biomedical Data Science in Stanford University. His research lies at the intersection of Bayesian statistics\, artificial intelligence\, and biomedical applications. His postdoctoral work has been supported by a Warren Alpert Fellowship and a Croucher Postdoctoral Fellowship. He earned his PhD in Statistical Science from Duke University\, where he worked with David Dunson\, and holds degrees in computer science and biomedical engineering from the University of Chicago\, Yale University\, and Johns Hopkins University. He has also held research and engineering roles at Google\, Meta\, Amazon\, and Apple AIML. \nThis seminar is hosted by Professor Yunyi Shen.
URL:https://events.ucsc.edu/event/statistics-seminar-randomization-posteriors-and-generalized-bayesian-inference/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20261130T160000
DTEND;TZID=America/Los_Angeles:20261130T170000
DTSTAMP:20261015T171006Z
CREATED:20261015T171006Z
LAST-MODIFIED:20261015T171006Z
UID:10017823-1796054400-1796058000@events.ucsc.edu
SUMMARY:Statistics Seminar: Robustness\, Model Checking and Hierarchical Models
DESCRIPTION:Presenter: Rafael Cabral\, Member of Technical Staff\, Axiom Math \nDescription: Latent Gaussian models (LGMs) are among the most widely used classes of statistical models\, with applications ranging from biostatistics to spatial modeling. Their central assumption\, that the latent variables are Gaussian\, is nevertheless rarely checked. Many datasets contain sudden jumps or local spikes that a Gaussian latent process over-smooths\, impacting both inference and prediction. This talk presents a two-step workflow for hierarchical models\, in the spirit of George Box’s loop: model criticism\, to check whether the latent assumptions hold\, followed by robustification\, to fit a more flexible model when they do not. In the criticism step\, diagnostic statistics are derived rather than chosen ad hoc\, by targeting the departures from Gaussianity induced by a more flexible alternative model. This connects Bayesian predictive checking with robustness analysis and yields a general recipe for assessing latent assumptions\, and their impact on the results. In the robustification step\, latent non-Gaussian models are fitted using variational Bayes and Laplace approximations. The resulting algorithm iteratively refits LGMs that downweight extreme events in the latent process\, giving robust inferences at a fraction of the cost of MCMC. Both steps are implemented in Stan and R-INLA and illustrated with longitudinal\, areal and geostatistical applications. \nAbout the speaker: Rafael Cabral is a Member of Technical Staff at Axiom Math in Palo Alto\, where he develops AI systems for mathematics and verified reasoning. He received his PhD in Statistics from KAUST in 2023\, advised by Håvard Rue and David Bolin\, where he worked on model criticism and robust inference for latent Gaussian models. He was subsequently a Research Fellow at the National University of Singapore and a Staff Engineer at Huawei\, working on AI safety and reliability. His research interests span Bayesian modeling\, robustness\, and the application of language models to mathematics and formal reasoning. \nThis seminar is hosted by Professor Yunyi Shen.
URL:https://events.ucsc.edu/event/statistics-seminar-robustness-model-checking-and-hierarchical-models/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20270507T130000
DTEND;TZID=America/Los_Angeles:20270507T173000
DTSTAMP:20261014T180426Z
CREATED:20261014T180426Z
LAST-MODIFIED:20261014T180426Z
UID:10017802-1809694800-1809711000@events.ucsc.edu
SUMMARY:Chemical Screening Center 2027 Symposium
DESCRIPTION:Join the UCSC Chemical Screening Center on May 7\, 2027 for our biennial symposium in PSB240. The event is free to all who register by April 15\, 2027 (registration link will be available closer to the time\, at csc.ucsc.edu). We are featuring a distinguished speaker\, Dr. Ethan Perlstein\, CEO of Perlara PBC\, the first biotech nonprofit. There will also be faculty and trainee talks\, vendor tables\, and a reception for networking. If you would like a tour of the CSC facilities\, those can be arranged for the morning before the symposium. Vendors – for information on opportunities to table\, see csc.ucsc.edu/vendors.
URL:https://events.ucsc.edu/event/chemical-screening-center-2027-symposium/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Conference,Employment Fair,Exhibits,Lectures & Presentations,Meetings & Conferences,Reception,Seminars,Tours
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