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DTSTART;TZID=America/Los_Angeles:20251203T110000
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DTSTAMP:20260406T082114
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SUMMARY:When Less is More: Applications of Type-Based Underapproximate Reasoning
DESCRIPTION:Presenter: Suresh Jagganathan\, Purdue University\n\n\nAbstract:\nUnlike program verifiers\, symbolic execution and property-based testing tools underapproximate program behavior: they aim to report only real bugs (no false positives)\, at the cost of potentially missing some (false negatives). Recent work has sought to place such tools on a more formal footing\, primarily through the development of incorrectness logics that capture a program’s ‘must’ rather than ‘may’ behavior. This talk explores how to transplant these ideas of underapproximation into an expressive refinement type system. Our development enables us to:\n\n(a) Typecheck the completeness of property-based testing (PBT) generators\, ensuring that a well-typed generator produces all values (i.e.\, fully covers) its output type;\n\n(b) Synthesize effectful generators by extending the type system to model underapproximations of sequences of effects rather than just values; and\n\n(c) Guide symbolic execution in effectful functional programs\, prioritizing execution paths capable of falsifying data structure safety properties.\n\nOur results demonstrate that viewing types through the lens of underapproximation offers a principled foundation for designing\, implementing\, and reasoning about program analyzers and test generators\, significantly improving their reliability and practical utility in the process.\n\n\nBio:\nSuresh Jagannathan is the Samuel D. Conte Professor of Computer Science at Purdue University. His interests span functional programming\, program verification\, distributed and concurrent systems\, and trustworthy machine learning. In recent years\, he has spent time as an Amazon Scholar\, a program manager at the Information Innovoation Office (I2O) at DARPA\, and a visiting researcher at the University of Cambridge. He serves an Associate Editor of ACM TOPLAS\, and has served as both General and PC Chair of POPL (ACM Symposium on Programming Languages).\n\n\nHosted by: Professor Mohsen Lesani\n\n\nLocation: E2-180\n*Refreshments such as coffee and pastries will be provided\n\n\n\nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/when-less-is-more-applications-of-type-based-underapproximate-reasoning/
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:20251203T115000
DTEND;TZID=America/Los_Angeles:20251203T131000
DTSTAMP:20260406T082114
CREATED:20251108T002424Z
LAST-MODIFIED:20251125T164318Z
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SUMMARY:Applied Microeconomics and Trade Seminar Series presents: Matt Weinberg
DESCRIPTION:Applied Microeconomics and Trade Seminar\nDate: Wednesday\, December 3\, 2025\nTime: 11:50am – 1:10 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Matt Weinberg \nTitle: Professor of Economics \nAffiliation: Ohio State University\nHost: Jon Robinson\n \nSeminar title: Oligopsony and Collective Bargaining: Evidence from K-12 Teachers \n\nABSTRACT:  Employers facing limited labor market competition may suppress wages below socially optimal levels. Unions can counteract this wage suppression through collective bargaining\, though the may also push wages above the socially optimal level. To assess these forces\, we estimate a structural model of labor supply\, labor demand\, and Nashin-Nash bargaining over wages between teacher unions and school districts in Pennsylvania’s K-12 public school system from 2013 to 2020. Using the estimated parameters\, we compare negotiated equilibrium wages and employment to the pure oligopsony scenario and the social planner scenario. On average\, pure oligopsony reduces wages 16 percent below the social optimum\, while collective bargaining raises wages by 9 percent above the optimum. This average masks substantial district-level heterogeneity driven by variation in bargaining power. Twenty-seven percent of schools have negotiated salaries below the social optimum due to cross-district externalities\, where high salaries at one school lead to hiring reductions\, which increase labor supply in competing districts. 
URL:https://events.ucsc.edu/event/applied-microeconomics-and-trade-seminar-series-presents-matt-weinberg/
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:20251204T114000
DTEND;TZID=America/Los_Angeles:20251204T131500
DTSTAMP:20260406T082114
CREATED:20251203T194937Z
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SUMMARY:BME 280B Seminar: Gali Bai & David Haussler
DESCRIPTION:Presenter 1: Gali Bai\, BME/PBSE Doctoral Candidate\, Brooks Lab\, UC Santa Cruz \nTitle 1: Dissecting the contribution of chromatin accessibility to RNA transcription and processing with long-read sequencing \nDescription: Although all cells in an organism share the same genomic sequence\, transcriptional programs vary dramatically across cell types. This diversity is governed by epigenetic regulation involving the coordinated activities of chromatin remodelers\, histone modifiers\, and histone chaperones that precisely modulate chromatin accessibility. While previous studies have shown that chromatin accessibility at DNase I–hypersensitive sites such as promoters and enhancers is closely associated with gene expression\, much less is known about how chromatin influences transcription and RNA processing. To study how chromatin regulates RNA processing\, we perturbed yeast chromatin accessibility by deleting two highly conserved chromatin remodelers ISW1 and CHD1. With Oxford Nanopore long-read sequencing\, we profiled nascent RNA\, full-length mRNA\, and chromatin fibers in wild-type and chd1 isw1 double-mutant yeast cells. Loss of ISW1 and CHD1 led to increased chromatin accessibility within intragenic regions\, accompanied by aberrant transcription initiation. Leveraging long-read data\, we associated distinct chromatin states with specific RNA processing events and isoform expression outcomes. Despite a similar level of chromatin perturbations across the genome\, genes with low baseline expression showed extensive transcriptional reprogramming\, whereas highly expressed genes remained largely unaffected. These discrepancies can be partially explained by differences in the enrichment of transcription initiation motifs. In intron-containing genes\, loss of ISW1 and CHD1 reduced splicing efficiency and increased intron retention\, likely due to disrupted RNAPII elongation in the double mutant. Together\, our findings highlight the crucial role of ATP-dependent chromatin remodelers in maintaining nucleosome organization and coordinating co-transcriptional RNA processing. \nPresenter 2: David Haussler\, Distinguished Professor\, UC Santa Cruz \nTitle 2: Brain Organoids \nBio: Haussler received his PhD in computer science from the University of Colorado at Boulder. He is a member of the National Academy of Sciences\, the National Academy of Engineering\, the American Academy of Arts and Sciences and a fellow of AAAS and AAAI. He has won a number of awards\, including the 2015 Dan David Prize\, the 2011 Weldon Memorial Prize from University of Oxford\, the 2009 ASHG Curt Stern Award in Human Genetics\, the 2008 Senior Scientist Accomplishment Award from the International Society for Computational Biology\, the 2005 Dickson Prize for Science from Carnegie Mellon University\, and the 2003 ACM/AAAI Allen Newell Award in Artificial Intelligence. \nHosted by: Professor Josh Stuart\, BME Department
URL:https://events.ucsc.edu/event/bme-280b-seminar-gali-bai-david-haussler/
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:20251204T134000
DTEND;TZID=America/Los_Angeles:20251204T150000
DTSTAMP:20260406T082114
CREATED:20251108T001824Z
LAST-MODIFIED:20251120T170815Z
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SUMMARY:Behavioral\, Econometrics and Theory Seminar Series Presents: Jacopo Magnani
DESCRIPTION:Economics Behavioral\, Econometrics\, & Theory Seminar\nDate: Thursday\, December 4\, 2025\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Jacopo Magnani \nTitle:  Associate Professor of Economics \nAffiliation: Norwegian University of Science and Technology\, visiting Caltech\nHost: Kristian Lopez Vargas\n \nSeminar title: Behavioral Limits to Complete Markets\n \nABSTRACT:  Standard economic theory predicts that individuals should prefer complete markets to incomplete markets\, as the former allow state-contingent claims for every possible outcome. Yet real-world markets remain incomplete\, and the demand-side origins of the phenomenon are poorly understood. We develop an experimental framework to examine whether investors may themselves prefer incomplete markets\, and highlight two potential mechanisms: preference instability\, which exposes agents to greater regret or temptation in complete markets\, and complexity costs\, which arise because higher dimensionality increases cognitive effort and errors. In our experiment\, participants consistently reveal a preference for in complete markets\, contradicting the rational benchmark. Comparing homegrown and induced-preference treatments\, we find no evidence that this behavior is driven by preference instability. Instead\, utility losses\, response times\, and subjective ratings indicate that complexity costs drive the preference for incompleteness. Structural estimation confirms that complete markets are several times more complex than incomplete ones\, providing a behavioral foundation for market incompleteness. 
URL:https://events.ucsc.edu/event/behavioral-econometrics-and-theory-seminar-series-presents-jacopo-magnani/
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:20251208T093000
DTEND;TZID=America/Los_Angeles:20251208T104500
DTSTAMP:20260406T082114
CREATED:20251117T202808Z
LAST-MODIFIED:20251119T192125Z
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SUMMARY:CSE Colloquium: Making Systems Secure with Information Flow
DESCRIPTION:Presenter: Andrew Myers\, Cornell University\n\nAbstract:\nModern civilization depends on complex\, interconnected software systems that must safeguard trustworthy or private data. We have ever-growing mountains of code yet lack principled ways to build large systems that are secure. What is missing is a way to securely build these systems compositionally: module by module and layer by layer. Information flow control\, enforced throughout software and hardware\, offers a plausible way to achieve compositional security\, and is increasingly being used by industry. I describe how my research group has incorporated information-flow security into various languages and systems: hardware architectures resilient to timing and speculation attacks\, smart contracts\, and automatically synthesized cryptographic and distributed protocols. Information flow is inherently compositional and makes possible strong\, provable security guarantees that can be connected to cryptographic security definitions. Importantly\, it also guides developers during the design process\, exposing security-critical decisions up front. \nBio:\nAndrew Myers is the Class of 1912 Professor of Engineering in the Department of Computer Science at Cornell University. He received his Ph.D. in Electrical Engineering and Computer Science from MIT\, advised by Barbara Liskov. His research interests include programming languages\, computer security\, and distributed and persistent programming systems. His work on computer security has focused on practical\, sound\, expressive languages and systems for enforcing information security. Myers is an ACM Fellow and has authored several award-winning papers. He currently serves as the chair of the ACM SIGPLAN Executive Committee. \nHosted By: Professor Mohsen Lesani \nLocation: Engineering 2\, E2-180 \nZoom: https://ucsc.zoom.us/j/97682837116?pwd=WZBzhJY4p7rTZshqglmOs6xBtBasbE.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-making-systems-secure-with-information-flow/
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:20251210T153000
DTEND;TZID=America/Los_Angeles:20251210T190000
DTSTAMP:20260406T082114
CREATED:20251124T181454Z
LAST-MODIFIED:20251124T181454Z
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SUMMARY:The Everett Program Presents: Envisioning Digital Justice Together | 7th Annual Project Showcase
DESCRIPTION:The Everett Program Presents: Envisioning Digital Justice Together | 7th Annual Project Showcase \nThis showcase aims to highlight the incredible work of our students\, who have completed a year-long practicum conceptualizing and using digital technology to work with nonprofit organizations on social justice issues from climate justice to the racist impacts of the carceral state. \nThis year\, Showcase is an event in which the audience can not only come together to support these wonderful students and their work\, but also to envision a range of digital futures together. \nAll are welcome! RSVP with the QR Code found on the poster\, we hope to see you there 🙂
URL:https://events.ucsc.edu/event/the-everett-program-presents-envisioning-digital-justice-together-7th-annual-project-showcase/
LOCATION:Merrill Cultural Center\, 200 McLaughlin Dr\, Santa Cruz\, CA\, 95064
CATEGORIES:Exhibits,Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260105T123000
DTEND;TZID=America/Los_Angeles:20260105T133000
DTSTAMP:20260406T082114
CREATED:20251204T220726Z
LAST-MODIFIED:20251209T200624Z
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SUMMARY:CM Seminar - "How Technology-Mediated Food Interactions Support Family Connection and Routine Reconstruction"
DESCRIPTION:Presented by: Aswati Panicker \nDescription: “In this talk\, I draw on work in human-food interaction (HFI) to examine how food can serve as a rich interaction medium for connection and routine reconstruction in long-distance families. I highlight insights from three of my studies that explore this question across different technological forms. First\, I discuss how families navigate shifting meanings of “healthy eating” during life transitions\, and the tensions that arise when disclosing new goals and priorities in health-sharing or tracking tools. Second\, I show how family members expressed hesitations\, value conflicts\, and visions for cultural or playful moments when imagining embodied technology such as a social robot within their domestic spaces. Third\, through a mobile app probe for teaching food knowledge and recipes\, I uncover the subtleties of how family members seek to initiate\, learn\, guide\, or be guided through everyday food practices. Throughout\, I outline design implications and close by reflecting on how technology-mediated food interactions might extend to other contexts and routines beyond family life.” \nBio: Aswati Panicker is a postdoctoral scholar at the University of California\, Santa Cruz\, working with Prof. Christina Chung. Her research is at the intersection of HCI and CSCW\, focusing on how technologies are designed and used in social and health-related contexts. She takes a human-centered\, participatory approach and draws on theories from family studies and sociology in her work. She earned her PhD in Informatics from Indiana University Bloomington in July 2025. You can read more at aswatipanicker.com \n  \nHosted by: Professor Christina Chung \nWhen: Monday\, January 5\, 2026 from 12:30PM to 1:30PM \nLocation:  \nIN-PERSON @  SVC 3212. \nViewing room @ UCSC Main Campus\, E2-280. \nLUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend. \nZoom info: \nhttps://ucsc.zoom.us/j/98742808551?pwd=3UaQbY0YMMAgfdJhkQzN8mSrzYhfCG.1\nMeeting ID: 987 4280 8551\nPasscode: 866098 \n 
URL:https://events.ucsc.edu/event/cm-seminar-how-technology-mediated-food-interactions-support-family-connection-and-routine-reconstruction/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260105T160000
DTEND;TZID=America/Los_Angeles:20260105T170000
DTSTAMP:20260406T082114
CREATED:20251217T182411Z
LAST-MODIFIED:20251218T002005Z
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SUMMARY:AM Seminar with Dr. Truong Vu
DESCRIPTION:Presenter: Dr. Truong Vu\, IPAM and MSU \nDescription: We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a penalty method to develop families of locally incompressible gradient flows that couple interface stretching or compression to local flux of interfacial mass. We establish the convergence of the penalty method to an incompressible flow both formally for a broad family of surface energies and rigorously for a more narrow class of surface energies. \nBio: Dr. Vu received a Ph.D. in Applied Mathematics from the Department of Mathematics\, Statistics\, and Computer Science at University of Illinois at Chicago. Dr. Vu is currently a Postdoctoral Fellow at the Institute for Pure and Applied Mathematics (UCLA) and a visiting faculty in the Department of Mathematics at Michigan State University. \nHosted by: Applied Mathematics 
URL:https://events.ucsc.edu/event/am-seminar/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260108T114000
DTEND;TZID=America/Los_Angeles:20260108T131500
DTSTAMP:20260406T082114
CREATED:20251216T231619Z
LAST-MODIFIED:20251216T231619Z
UID:10005856-1767872400-1767878100@events.ucsc.edu
SUMMARY:BME 280B Seminar: Nature’s Miniature Masterpieces - Nanobodies as Small but Mighty Antibodies for the next Pandemic
DESCRIPTION:Presenter: Katja Hanack\, Founder and CEO\, New/Era/Mabs \nDescription: Nanobodies combine remarkable simplicity with surprising power. Their small size allows them to reach targets that remain inaccessible to conventional antibodies\, while maintaining high specificity and stability. Their compact architecture allows them to access targets that conventional antibodies cannot reach\, yet they preserve the specificity and power that make antibody therapeutics so transformative. In this talk I will introduce the science behind selma\, a cell based discovery platform developed over more than a decade to rapidly identify high quality antibodies and nanobodies. I will explore why these tiny binders matter\, how they differ from classical antibodies\, and what their unique biology enables for diagnostics and therapeutics. \nThe presentation will conclude with my current project on immune infrastructure and how pre validated nanobody archives can shift the pandemic response from a reactive model to proactive preparedness for future outbreaks. \nBio: Katja Hanack\, PhD\, MBA\, is the Founder and CEO of new/era/mabs and a leading expert in antibody discovery for diagnostic and therapeutic applications\, with a particular focus on nanobody technologies. With more than 20 years of experience\, she has developed pioneering platforms that enable the efficient generation and selection of next-generation monoclonal antibodies and nanobodies. She holds a Biology degree from Humboldt University of Berlin and a PhD in Biotechnology from the University of Potsdam. As a former Professor of Biochemistry and Biology at the University of Potsdam\, she built and led a research group of 25 scientists\, secured over €16 million in external funding\, and authored more than 40 peer-reviewed publications. Since 2017\, Dr. Hanack has contributed to translational innovation as an industrial advisor for SPARK Stanford and SPARK Berlin\, supporting academic teams in bringing biomedical discoveries to patients. \nHosted by: Professor Rebecca Dubois\, BME Department
URL:https://events.ucsc.edu/event/bme-280b-seminar-natures-miniature-masterpieces-nanobodies-as-small-but-mighty-antibodies-for-the-next-pandemic/
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:20260112T160000
DTEND;TZID=America/Los_Angeles:20260112T170000
DTSTAMP:20260406T082114
CREATED:20251219T164251Z
LAST-MODIFIED:20251219T164251Z
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SUMMARY:Kathleen Schmidt: Sequential Experimental Design for Materials Strength Model Calibration
DESCRIPTION:Presenter: Katie Schmidt\, UQ & Optimization Group Leader\, Lawrence Livermore National Laboratory \nDescription: Due to the time and expense associated with physical experiments\, there is significant interest in optimal selection of the conditions for future experiments. Selection based on reduction in parameter uncertainty provides a natural path forward. We consider this type of optimal sequential design in the context of Bayesian calibration of materials strength models with the strength model characterizing the evolving resistance of a material to permanent strain. This problem is particularly challenging because different types of experiments and associated diagnostics are employed across strain rate regimes. For lower-strain-rate experiments\, stress-strain curves can be measured directly. For higher-strain-rate experiments\, strength must be inferred (e.g.\, from the deformation of a cylinder of material in a Taylor cylinder experiment). We employ data fusion in our sequential design methodology to incorporate these multiple experimental modalities. \nLLNL-ABS-835231 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. \nBio: Katie Schmidt is the UQ & Optimization Group Leader at Lawrence Livermore National Laboratory. She joined LLNL in 2016 after earning a PhD in Applied Mathematics from North Carolina State University. During her time at the lab\, Katie has been involved in a variety of uncertainty quantification problems related to national security as well as outreach and education through LLNL’s Data Science Institute. Her research interests include mixed-effects models\, Bayesian inference\, sequential design\, and sensitivity analysis. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/kathleen-schmidt-sequential-experimental-design-for-materials-strength-model-calibration/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260112T160000
DTEND;TZID=America/Los_Angeles:20260112T170000
DTSTAMP:20260406T082114
CREATED:20260112T164010Z
LAST-MODIFIED:20260112T164010Z
UID:10008343-1768233600-1768237200@events.ucsc.edu
SUMMARY:AM Seminar: Science in the Age of Foundation Models
DESCRIPTION:Presenter: Dr. Danielle Robinson\, AWS AI \nDescription: In this talk\, I will discuss the large impact of foundation models within the sciences with a particular focus on the importance of physical constraints and uncertainty quantification. First\, I will detail our novel ProbConserv framework for enforcing hard constraints within black-box deep learning models. ProbConserv provides uncertainty quantification\, and can be used to enforce conservation law constraints as well as other nonlinear constraints. Next\, I will discuss its extensions to ensembles of Neural Operators and out-of-distribution (OOD) estimations\, as well as how it can be used in constrained generative modeling of PDEs. I will then show applications of our work in computational fluid dynamics (CFD)\, including weather forecasting\, aerodynamics and chaotic systems. Lastly\, I will conclude with a forward-looking view of the next steps for designing a physics foundation model that can be applied across various types of flows\, geometries and boundary conditions\, and what is needed for such a model to be developed. \n\n\n\n\n\n\n\n\n\nBio: Danielle Maddix Robinson is a Senior Applied Scientist in the Machine Learning Forecasting Group within AWS AI. She graduated with her PhD in Computational and Mathematical Engineering from the Institute of Computational and Mathematical Engineering (ICME) at Stanford University. She was advised by Professor Margot Gerritsen and developed robust numerical methods to remove spurious temporal oscillations in the degenerate nonlinear Generalized Porous Medium Equation. She is passionate about the underlying numerical analysis\, linear algebra and optimization methods behind numerical PDEs and applying these techniques to deep learning. During her PhD\, she also did an internship at NVIDIA with Joe Eaton and Alex Fender\, and implemented an efficient and load-balanced sparse matrix vector multiplication (spmv) in cuSPARSE and nvGRAPH libraries. She is excited to be back at NVIDIA today. After graduating\, Danielle joined AWS in 2018\, and has been working on developing statistical and deep learning foundation models for time series forecasting including Chronos. Over the last several years\, she has been leading the research initiative on developing models for physics-constrained machine learning for scientific computing on the DeepEarth team. In particular\, she has researched how to apply ideas from numerical methods\, e.g.\, finite volume schemes\, to improve the accuracy of black-box ML models for PDEs with applications to ocean and climate models\, aerodynamics and chaotic systems. \n\n\n\nHosted by: Applied Mathematics\n\n\n\nLink: https://ucsc.zoom.us/j/96136632376?pwd=yb27lop8mnhnsairAPgezmVJZzFb74.1.
URL:https://events.ucsc.edu/event/am-seminar-science-in-the-age-of-foundation-models/
LOCATION: https://ucsc.zoom.us/j/96136632376?pwd=yb27lop8mnhnsairAPgezmVJZzFb74.1.
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260112T170000
DTEND;TZID=America/Los_Angeles:20260112T183000
DTSTAMP:20260406T082114
CREATED:20251209T200526Z
LAST-MODIFIED:20251218T001742Z
UID:10005751-1768237200-1768242600@events.ucsc.edu
SUMMARY:Be Inspired: Explore Graduate Studies in STEM
DESCRIPTION:Not sure if graduate school is right for you? \nJoin us to learn what graduate school is really about and explore whether it’s the right path for you. We’ll cover topics such as qualifying exams\, funding options\, common misconceptions\, and more! \nClick the link below to register for the event: \nhttps://ucsc.zoom.us/webinar/register/WN_31OHhwc7QPqJ7nSyiuAUNg
URL:https://events.ucsc.edu/event/be-inspired-explore-graduate-studies-in-stem/
LOCATION:CA
CATEGORIES:Seminars,Workshop
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/12/Graduate-Student-Workshop-Flyer.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260113T134000
DTEND;TZID=America/Los_Angeles:20260113T150000
DTSTAMP:20260406T082114
CREATED:20251211T224403Z
LAST-MODIFIED:20251219T220255Z
UID:10005826-1768311600-1768316400@events.ucsc.edu
SUMMARY:Macroeconomics & International Finance Seminar Series Presents: Dean Corbae
DESCRIPTION:Macroeconomics and International Finance Seminar\nDate: Tuesday\, January 13\, 2026\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Dean Corbae\nTitle: William Sellery Trukenbrod Chair in Finance\nAffiliation: University of Wisconsin – Madison\nHost: Grace Gu Steadmon\n \nSeminar title:  A Quantitative Model of Bank Merger Dynamics\n \n\nABSTRACT: \nWe develop a simple model of the bank merger process to study the rise in bank concentration following the deregulation of bank branching in the Riegle-Neal Act of 1994. Motivated by the data where currently 10 (dominant) banks have over 55 percent of the U.S. deposit market share while the remaining over 4000 (fringe) banks cover the rest\, we apply a dominant-fringe framework with a merger stage to model the rise in concentration following the change in regulation making interstate branching possible. First\, we study the effect of the merger wave on competition\, efficiency\, and stability of the banking industry. Then we use our model to understand the interaction between regulatory and monetary policy. Specifically\, how has the bank lending channel of monetary policy been affected by rising concentration; has it amplified or dampened the effectiveness of monetary policy? How might monetary policy itself contribute to mergers and rising concentration?
URL:https://events.ucsc.edu/event/macroeconomics-international-finance-seminar-series-presents-dean-corbae/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260115T014000
DTEND;TZID=America/Los_Angeles:20260115T014000
DTSTAMP:20260406T082114
CREATED:20251211T212236Z
LAST-MODIFIED:20251219T220029Z
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SUMMARY:Applied Microeconomics and Trade Seminar Series Presents: Olivia Bordeu
DESCRIPTION:Applied Microeconomics and Trade Seminar\nDate: Thursday\, January 15\, 2026\nTime: 1:40 – 3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Olivia Bordeu \nTitle: Assistant Professor of Economics \nAffiliation: University of California\, Berkeley  \nHost: Jeremy West \nSeminar title: Bank Branches and the Allocation of Capital across Cities\n\nABSTRACT: We study how banking market structure and branch networks shape the spatial mobility of capital. Using administrative loan-level data from Chile\, we show that bank-level deposit shocks lead receiving banks to increase lending and lower interest rates relative to other banks. Interest rate reductions are concentrated in cities where the bank has a small market share\, consistent with local market power. We develop and estimate a quantitative spatial model with multi-city banks\, oligopolistic local credit markets\, and frictions in interbank lending. These channels lead to spatial dispersion in interest rates and the marginal productivity of physical capital\, reducing GDP. Interbank frictions reduce steady-state GDP by 0.04%\, while spatial variation in loan markups reduces GDP by 0.5%. Bank mergers improve financial integration between cities but reduce competition\, generating heterogeneous welfare effects that depend on the merging banks’ geographic overlap.
URL:https://events.ucsc.edu/event/applied-microeconomics-and-trade-seminar-series-presents-olivia-bordeu/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260120T134000
DTEND;TZID=America/Los_Angeles:20260120T150000
DTSTAMP:20260406T082115
CREATED:20251211T224823Z
LAST-MODIFIED:20260108T184635Z
UID:10005827-1768916400-1768921200@events.ucsc.edu
SUMMARY:Behavioral\, Econometrics and Theory Seminar Series Presents: Roberto Corrao
DESCRIPTION:Economics Behavioral\, Econometrics\, & Theory Seminar\nDate: Tuesday\, January 20\, 2026\nTime: 1:40-3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Roberto Corrao\nTitle:  Assistant Professor of Economics \nAffiliation:  Stanford University\nHost: Gerelt Tserenjigmid\n \nSeminar title: Contractibility Design\n \nABSTRACT: \nWe introduce a model of incentive contracting in which the principal\, in addition to\nwriting contracts\, must engage in contractibility design: creating an evidence structure\nthat allows them to prove when the agent has breached the contract. Designing an\nevidence structure entails both (i) front-end costs borne ex ante\, such as those of\ndrafting contracts\, and (ii) back-end costs borne ex post\, such as those of generating\nevidence. We find that\, under even small front-end costs\, optimal contracts are coarse\,\nspecifying finitely many contingencies out of a continuum of possibilities. In contrast\,\nunder even large back-end costs\, optimal contracts are complete. Applied to the design\nof procurement contracts\, our results rationalize: (i) the discreteness of contracts\, (ii)\nthe presence of similarly vague contracts in low-stakes and high-stakes settings\, and\n(iii) the discontinuous adjustment of contracts to changes in the economic environment.
URL:https://events.ucsc.edu/event/behavioral-econometrics-and-theory-seminar-series-presents-roberto-corrao/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260121T110000
DTEND;TZID=America/Los_Angeles:20260121T123000
DTSTAMP:20260406T082115
CREATED:20260105T203936Z
LAST-MODIFIED:20260105T205329Z
UID:10008262-1768993200-1768998600@events.ucsc.edu
SUMMARY:CSE Colloquium - Constraining Chaos: Toward Faithful and Semantic Decoding in Language Models
DESCRIPTION:Presenter: Loris D’Antoni\, UC San Diego \nAbstract:\nLanguage models excel at producing fluent text\, but in domains like code and math\, fluency isn’t enough — outputs must obey strict syntactic and semantic rules. A new wave of research is rethinking decoding itself: not as a process of sampling words\, but as a negotiation between probability\, structure\, and meaning. In this talk\, I’ll explore how grammar and semantics can be embedded into the decoding loop\, how we can sample from the true model conditional distribution under constraints\, and how programmable abstractions make it possible to enforce properties like type safety or program invariants. The result is a vision of decoding that is faithful to the model yet governed by rules\, pointing toward a future where LLMs generate not just plausible text\, but reliably correct output. \nBio:\nLoris D’Antoni is a Jacobs Faculty Scholar and Associate Professor in the Department of Computer Science and Engineering at the University of California San Diego. His research helps people build trustworthy software. His work has introduced new frameworks for verifying and synthesizing programs—ranging from resilient network configurations to robust decision-making systems—and\, more recently\, methods for aligning language models with user intent. \nHe is the recipient of an NSF CAREER Award and a Microsoft Research Faculty Fellowship\, and was selected as a Vilas Associate at the University of Wisconsin-Madison. He has also received Google\, Amazon\, and Meta Faculty Awards\, and the Morris and Dorothy Rubinoff Dissertation Award. His papers have earned several best paper awards and nominations\, including at TACAS\, ESOP\, ICDCN\, and SBES. \nLoris received his B.S. and M.S. in Computer Science from the University of Torino\, and his Ph.D. in Computer Science from the University of Pennsylvania. Before joining UC San Diego\, he was a faculty member at the University of Wisconsin–Madison. \nHosted by: Professor Nikos Tziavelis \nLocation: Engineering 2\, Room E2-180 \n*Light refreshments such as coffee\, pastries\, and fruit will be available. \nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-constraining-chaos-toward-faithful-and-semantic-decoding-in-language-models/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/01/ldantoni-scaled.jpg
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260122T014000
DTEND;TZID=America/Los_Angeles:20260122T014000
DTSTAMP:20260406T082115
CREATED:20251211T230012Z
LAST-MODIFIED:20260108T184752Z
UID:10005828-1769046000-1769046000@events.ucsc.edu
SUMMARY:Applied Microeconomics and Trade Seminar Series Presents: Guo Xu
DESCRIPTION:Applied Microeconomics and Trade Seminar\nDate: Thursday\, January 22\, 2026\nTime: 1:40 – 3:00 p.m.\nLocation: E2-499\n\n \n\nSpeaker: Guo Xu\nTitle: Associate Professor of Economics \nAffiliation: University of California\, Berkeley  \nHost: Ajay Shenoy \n  \nSeminar title: Personnel is Policy: Delegation and Political Misalignment in the Rulemaking Process\n\nABSTRACT: We combine comprehensive data on the U.S. federal rulemaking process with individuallevel personnel and voter registration records to study the consequences of partisan misalignment between regulators and the president. We present three main results. First\, even important pieces of new regulation are frequently delegated to bureaucrats who are politically misaligned. Second\, rules that are overseen by misaligned regulators take systematically longer to complete\, are more verbose\, generate more negative feedback from the public\, and are more likely to be challenged in court. Third\, in assigning regulators to rules\, agency leaders often face a sharp tradeoff between political alignment and expertise. Agency frictions notwithstanding\, they tend to resolve this tradeoff in favor of expertise.
URL:https://events.ucsc.edu/event/applied-microeconomics-and-trade-seminar-series-presents-guo-xu/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Seminars
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260122T114000
DTEND;TZID=America/Los_Angeles:20260122T131500
DTSTAMP:20260406T082115
CREATED:20260115T232014Z
LAST-MODIFIED:20260115T232014Z
UID:10008410-1769082000-1769087700@events.ucsc.edu
SUMMARY:BME Seminar: Rotation Talks
DESCRIPTION:Presenter: Grad Students \nDescription: Rotation Talks \nBio: N/A \nHosted by: Professor Rebecca DuBois\, BME Department
URL:https://events.ucsc.edu/event/bme-seminar-rotation-talks/
LOCATION:Physical Sciences Building\, Physical Sciences Building\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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GEO:36.9996638;-122.0618552
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Physical Sciences Building Physical Sciences Building Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Physical Sciences Building:geo:-122.0618552,36.9996638
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260123T120000
DTEND;TZID=America/Los_Angeles:20260123T130000
DTSTAMP:20260406T082115
CREATED:20260120T214846Z
LAST-MODIFIED:20260122T174111Z
UID:10008680-1769169600-1769173200@events.ucsc.edu
SUMMARY:Statistics Seminar: Heterogeneous Statistical Transfer Learning
DESCRIPTION:Presenter: Subhadeep Paul\, Associate Professor\, Ohio State University \nDescription: In the first part of the talk\, we consider the problem of Transfer Learning (TL) under heterogeneity from a source to a new target domain for high-dimensional regression with differing feature sets. Most homogeneous TL methods assume that target and source domains share the same feature space\, which limits their practical applicability. In applications\, the target and source features are frequently different due to the inability to measure certain variables in data-poor target environments. Conversely\, existing heterogeneous TL methods do not provide statistical error guarantees\, limiting their utility for scientific discovery.  Our method first learns a feature map between the missing and observed features\, leveraging the vast source data\, and then imputes the missing features in the target. Using the combined matched and imputed features\, we then perform a two-step transfer learning for penalized regression. We develop upper bounds on estimation and prediction errors\, assuming that the source and target parameters differ sparsely but without assuming sparsity in the target model. We obtain results for both when the feature map is linear and when it is nonparametrically specified as unknown functions.  Our results elucidate how estimation and prediction errors of HTL depend on the model’s complexity\, sample size\, the quality and differences in feature maps\, and differences in the models across domains. In the second part of the talk\, going beyond linear models\, I will discuss a transfer learning method for nonparametric regression using a random forest. The unknown source and target regression functions are assumed to differ for a small number of features. Our method obtains residuals from a source domain-trained Centered RF (CRF) in the target domain\, then fits another CRF to these residuals with feature splitting probabilities proportional to feature-residual distance covariance. We derive an upper bound on the mean square error rate of the procedure that theoretically brings out the benefits of transfer learning in random forests. Our results explain why shallower trees in the residual random forest in the target domain provide implicit regularization. \nBio:Subhadeep Paul is an Associate Professor in the Department of Statistics at The Ohio State University. He is also a faculty fellow and previously served as a co-director of the foundations of data science and AI community at the Translational Data Analytics Institute at Ohio State. He received his PhD in Statistics from the University of Illinois at Urbana-Champaign in 2017. His research focuses on statistical analysis of complex network-linked data and transfer and federated statistical learning. His research has been funded by two NSF grants from the algorithms of threat detection and mathematics of digital twins programs. \nHosted by: Statistics Department \nZoom link: https://ucsc.zoom.us/j/94465292273?pwd=bQ6MCX0OHYxHqgqNwbEYfgbKWqgNVy.1
URL:https://events.ucsc.edu/event/statistics-seminar-heterogeneous-statistical-transfer-learning/
LOCATION:https://ucsc.zoom.us/j/94465292273?pwd=bQ6MCX0OHYxHqgqNwbEYfgbKWqgNVy.1
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260126T104000
DTEND;TZID=America/Los_Angeles:20260126T114500
DTSTAMP:20260406T082115
CREATED:20260112T223834Z
LAST-MODIFIED:20260112T223834Z
UID:10008350-1769424000-1769427900@events.ucsc.edu
SUMMARY:ECE Seminar: Tactile sensing: At the boundary between mechanical and computational intelligence in robotic grippers
DESCRIPTION:Presenter: Dr. Hannah Stuart\, Associate Professor in the Department of Mechanical Engineering\, University of California at Berkeley \nDescription: Robot grippers typically include mechanical intelligence (e.g.\, underactuation\, compliance) or computational intelligence (e.g.\, fully actuated with a wide array of sensors). Next generation grippers and hands will require both intelligences to work in concert across applications with resilience and dexterity. This talk will introduce the concept of mechanical and computational intelligence co-design through example case studies that focus on the particular importance of embodied sensitivity as a feature of the co-design process. For example\, the most recent work on the Smart Suction Cup\, conducted largely by Dr. Jungpyo Lee\, demonstrates how design decisions like the number of sensitive chambers influences the resultant robot arm controller as well as physical compliance and manufacturing feasibility and cost. \nBio: Dr. Hannah Stuart is an Associate Professor in the Department of Mechanical Engineering at the University of California at Berkeley. She received her BS in Mechanical Engineering at the George Washington University in 2011\, and her MS and PhD in Mechanical Engineering at Stanford University in 2013 and 2018\, respectively. Her research focuses on understanding the mechanics of physical interaction in order to better design systems for dexterous manipulation. Applications range from remote robotics to assistive orthotics. Recent awards include the NSF CAREER grant\, NASA Early Career Faculty grant\, Hellman Fellows Fund grant\, and Johnson & Johnson Women in STEM2D grant. She is a Senior Member of IEEE. \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-seminar-tactile-sensing-at-the-boundary-between-mechanical-and-computational-intelligence-in-robotic-grippers/
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:20260126T120000
DTEND;TZID=America/Los_Angeles:20260126T130000
DTSTAMP:20260406T082115
CREATED:20260121T182735Z
LAST-MODIFIED:20260121T182735Z
UID:10009084-1769428800-1769432400@events.ucsc.edu
SUMMARY:Statistics Seminar: Boosting Biomedical Imaging Analysis via Distributed Functional Regression and Synthetic Surrogates
DESCRIPTION:Presenter: Guannan Wang\, Associate Professor\, The College of William & Mary \nDescription: Generative AI has emerged as a powerful tool for synthesizing biomedical images\, offering new solutions to challenges such as data scarcity\, privacy constraints\, and modality imbalance. However\, the reliable use of synthetic images in scientific analysis requires principled statistical frameworks that can assess fidelity and rigorously quantify uncertainty. In this talk\, I present a distributed functional data analysis approach for comparing original and AI- generated biomedical images through their mean and covariance structures. Using spline-based representations on complex imaging domains\, we construct simultaneous confidence regions\, enabling formal inference on original-synthetic differences and providing statistical safeguards for downstream analyses. Building on this foundation\, I demonstrate how synthetic images can\nbe safely incorporated into functional regression models to learn spatially varying covariate effects when key imaging modalities are partially observed. Applications to large-scale neuroimaging studies illustrate how integrating generative AI with rigorous statistical inference enhances the reliability\, interpretability\, and scientific value of modern biomedical imaging analyses. \nBio: Guannan Wang is a Diamond Term Distinguished Associate Professor in the Department of Mathematics at William & Mary. She received a Ph.D. in Statistics and an M.S. in Computer Science from the University of Georgia in 2015. Her research focuses on the statistical foundations of generative AI\, distributed and federated learning\, and spatial and functional data analysis\, with applications to neuroimaging\, public health\, and environmental and social sciences. She has published over 30 peer-reviewed articles in leading statistical journals\, including JASA\, JCGS\, Statistica Sinica\, Biometrics\, and JMLR\, and her work has been supported by the NIH\, NSF\, and the Simons Foundation. \nHosted by: Statistics Department \nZoom link: https://ucsc.zoom.us/j/92479478035?pwd=S6b9SNtCorApA04sISbDwWqaF3wyPZ.1
URL:https://events.ucsc.edu/event/statistics-seminar-boosting-biomedical-imaging-analysis-via-distributed-functional-regression-and-synthetic-surrogates/
LOCATION:https://ucsc.zoom.us/j/92479478035?pwd=S6b9SNtCorApA04sISbDwWqaF3wyPZ.1
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260126T123000
DTEND;TZID=America/Los_Angeles:20260126T133000
DTSTAMP:20260406T082115
CREATED:20260113T202943Z
LAST-MODIFIED:20260113T202943Z
UID:10008380-1769430600-1769434200@events.ucsc.edu
SUMMARY:CM Seminar - "Revealing Hidden Stories: Co-Designing the Thámien Ohlone Augmented Reality Tour"
DESCRIPTION:Presented by: Kai Lukoff \nDescription: \nThe Santa Clara University campus is adorned with symbols and monuments\, including a Spanish Mission Church\, that highlight its Catholic heritage. However\, the presence and history of the Ohlone Native Americans\, who have inhabited this land for thousands of years and continue to live in the region\, receive little to no recognition. How can we utilize augmented reality (AR) to share these hidden stories? \nIn collaboration with the Muwekma Ohlone Tribe\, our interdisciplinary team developed the Thámien Ohlone AR tour. This tour reveals hidden stories\, encourages visitors to engage in critical reflection\, and inspires visions of a more just future and received the Best Movie Award at CHI 2024\, the leading conference in the field of human-computer interaction. This talk will share insights on co-designing location-based AR experiences for social impact and explore the potential of AR in preserving cultural heritage. \nBio: Kai Lukoff is an assistant professor in the Department of Computer Science & Engineering at Santa Clara University. He leads the Human-Computer Interaction Lab\, focusing on technologies with social impact. His recent work focuses on co-design methods for location-based augmented reality. His research has been featured in prominent conferences such as CHI\, CSCW\, IMWUT\, and DIS\, and he was honored with the 2023 Outstanding Dissertation Award from ACM SIGCHI. \n  \nHosted by: Professor Sri Kurniawan \nWhen: Monday\, January 26\, 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/95105219890?pwd=PXG6uexrh6P0Ry06aRkxfdTsLhaNhK.1\nMeeting ID: 951 0521 9890\nPasscode: 160917
URL:https://events.ucsc.edu/event/cm-seminar-revealing-hidden-stories-co-designing-the-thamien-ohlone-augmented-reality-tour/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
GEO:37.0009723;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260126T160000
DTEND;TZID=America/Los_Angeles:20260126T170000
DTSTAMP:20260406T082115
CREATED:20260120T184336Z
LAST-MODIFIED:20260120T184604Z
UID:10008394-1769443200-1769446800@events.ucsc.edu
SUMMARY:AM Seminar: Probing Forced Responses and Causality in Data-Driven Climate Emulators: Conceptual Limitations and the Role of Reduced-Order Models
DESCRIPTION:Presenter: Fabrizio Falasca\, New York University \nDescription: A central challenge in climate science and applied mathematics is developing data-driven models of multiscale systems that capture both stationary statistics and responses to external perturbations. Current neural climate emulators aim to resolve the atmosphere–ocean system in all its complexity but often struggle to reproduce forced responses\, limiting their use in causal studies such as Green’s function experiments. To explore the origin of these limitations\, we first examine a simplified dynamical system that retains key features of climate variability. We argue that the ability of emulators of multiscale systems to reproduce perturbed statistics depends critically on (i) the choice of an appropriate coarse-grained representation and (ii) careful parameterizations of unresolved processes. These insights highlight reduced-order models\, tailored to specific goals\, processes\, and scales\, as valid alternatives to general-purpose emulators. We next consider a real-world application\, developing a neural model to investigate the joint variability of the surface temperature field and radiative fluxes. The model infers a multiplicative noise process directly from data\, largely reproduces the system’s probability distribution\, and enables causal studies through forced responses. We discuss its limitations and outline directions for future work. These results expose key challenges in data-driven modeling of multiscale physical systems and underscore the value of coarse-grained\, stochastic approaches.Throughout\, we propose linear response theory as a rigorous framework for evaluating neural models beyond stationary statistics\, probing causal mechanisms\, and guiding model design. \nBio: Fabrizio Falasca is physicist working at the intersection of statistical physics\, applied mathematics and climate science. He acquired his master degree in Physics of Complex Systems in the University of Turin in Italy. He then moved to Atlanta to pursue a PhD in Climate Science under the supervision of Annalisa Bracco. In the last 5 years he has been working in the Courant Institute of Mathematical Science in the group of Laure Zanna. His work span response theory\, causal inference\, data-driven modeling\, and their applications to climate dynamics and change. \n\n\n\n\n\nHosted by: Applied Mathematics \nZoom Link: https://ucsc.zoom.us/j/97450297092?pwd=Bp4GIgR8dAuBeCd1Sz9vXo8unkYWQW.1
URL:https://events.ucsc.edu/event/am-seminar-probing-forced-responses-and-causality-in-data-driven-climate-emulators-conceptual-limitations-and-the-role-of-reduced-order-models/
LOCATION: https://ucsc.zoom.us/j/97450297092?pwd=Bp4GIgR8dAuBeCd1Sz9vXo8unkYWQW.1
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260128T110000
DTEND;TZID=America/Los_Angeles:20260128T121500
DTSTAMP:20260406T082115
CREATED:20260120T191337Z
LAST-MODIFIED:20260120T191337Z
UID:10008678-1769598000-1769602500@events.ucsc.edu
SUMMARY:CSE Colloquium - Towards Relational Foundation Models: Zero-Shot Forecasting over Relational Databases
DESCRIPTION:Presenter: Charilaos I. Kanatsoulis\, Stanford University \nAbstract: Foundation models have transformed unstructured domains such as language and vision\, yet relational datasets\, where most enterprise knowledge lives\, still rely on brittle\, task-specific ML pipelines. I will begin by introducing Relational Deep Learning (RDL)\, a general framework for learning directly from heterogeneous multi-table data\, capturing structure across entities\, attributes\, and relationships without handcrafted schemas or features. \nBuilding on this paradigm\, I will present the Relational Transformer (RT)\, a schema-invariant model pretrained across diverse relational databases that performs structural learning with in-context information and transfers zero-shot to new databases and predictive tasks. By modeling both inter- and intra-table dependencies and reframing prediction as pattern recognition inside a unified latent relational space\, RT represents a concrete step toward relational foundation models that can be prompted\, reused\, and generalized for new problems. \nBio: Charilaos I. Kanatsoulis is a Research Scientist in the Department of Computer Science at Stanford University. He previously was a Postdoctoral Researcher in the Department of Electrical and Systems Engineering at the University of Pennsylvania and received his Ph.D. in Electrical and Computer Engineering from the University of Minnesota\, Twin Cities. His research lies at the intersection of machine learning and signal processing\, with a focus on Transformer and foundation model design for structured data\, graph representation learning\, tensor analysis\, and explainable AI. His work has been recognized with the Best Paper Award at the KDD Temporal Graph Learning Workshop (2025) and the Best Student Paper Award at IEEE CAMSAP (2023). He co-instructs CS246 and CS224W at Stanford and previously taught ESE 5140 at Penn. He has organized several community events\, including the Graph Signal Processing short course at IEEE ICASSP 2023\, the Stanford Graph Learning Workshop (2024–2025)\, the Relational Deep Learning tutorial at ACM KDD 2025\, and the New Perspectives in Advancing Graph Machine Learning Workshop at NeurIPS 2025. \nHosted by: Professor Nikos Tziavelis \nLocation: Engineering 2\, Room E2-180 (Refreshments such as coffee\, pastries\, and fruit will be provided.) \nZoom: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3
URL:https://events.ucsc.edu/event/cse-colloquium-towards-relational-foundation-models-zero-shot-forecasting-over-relational-databases/
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:20260128T120000
DTEND;TZID=America/Los_Angeles:20260128T130000
DTSTAMP:20260406T082115
CREATED:20260121T235125Z
LAST-MODIFIED:20260128T171042Z
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SUMMARY:Statistics Seminar:  Inferring Unobserved Trajectories from Multiple Temporal Snapshots
DESCRIPTION:Presenter: Yunyi Shen\, Ph.D. Candidate\, Department of Electrical Engineering and Computer Science\, Massachusetts Institute of Technology \n\nDescription: Practitioners often aim to infer an unobserved population trajectory using sample snapshots at multiple time points. E.g. given single-cell sequencing data\, scientists would like to learn how gene expression changes over a cell’s life cycle. But sequencing any cell destroys that cell. So we can access data for any particular cell only at a single time point\, but we have data across many cells. The deep learning community has recently explored using Schrödinger bridges (SBs) and their extensions in similar settings. However\, existing methods either (1) interpolate between just two time points or (2) require a single fixed reference dynamic (often set to Brownian motion within SBs). But learning piecewise from adjacent time points can fail to capture long-term dependencies. And practitioners are typically able to specify a model family for the reference dynamic but not the exact values of the parameters within it. So I propose a new method that (1) learns the unobserved trajectories from sample snapshots across multiple time points and (2) requires specification only of a family of reference dynamics\, not a single fixed one. I demonstrate the advantages of my method on simulated and real data\, across applications in biology and oceanography. \nBio: Yunyi Shen is currently a Ph.D. candidate in the Department of Electrical Engineering and Computer Science at MIT. He works in probabilistic machine learning and statistics on problems where data are scarce or noisy\, and as a result require adaptive data collection\, incorporation of domain-specific structure\, and careful downstream evaluation. Drawing on a background in the physical and life sciences\, his work is shaped by close interdisciplinary collaborations and motivated by scientific problems in biology and physics\, such as gene regulation\, fluid dynamics in cells\, wildlife monitoring\, and time-domain astronomy. \nHosted by: Statistics Department  \nZoom link: https://ucsc.zoom.us/j/93769232971?pwd=msPkbjtoK3LiI9qHjLT1bv8idV23qU.1
URL:https://events.ucsc.edu/event/statistics-seminar-inferring-unobserved-trajectories-from-multiple-temporal-snapshots/
LOCATION:https://ucsc.zoom.us/j/93769232971?pwd=msPkbjtoK3LiI9qHjLT1bv8idV23qU.1
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260129T114000
DTEND;TZID=America/Los_Angeles:20260129T131500
DTSTAMP:20260406T082115
CREATED:20260122T232352Z
LAST-MODIFIED:20260122T232352Z
UID:10009095-1769686800-1769692500@events.ucsc.edu
SUMMARY:BME 280B Seminar: Satellite repeats encode megabase-scale transcription factor hubs
DESCRIPTION:Presenter: Matt Franklin\, Postdoctoral Researcher\, Stanford University \nDescription: Eukaryotic genomes contain large stretches of repetitive DNA called satellite DNA\, often found near centromeres and ribosomal DNA regions. In humans\, alpha satellite has well-established roles in centromere biology\, however the functions of other human satellite DNAs remain largely unexplored. \nWe recently identified the Hippo pathway effector TEAD as a novel Human Satellite 3 (HSat3) binding TF. Because HSat3 is highly enriched near ribosomal DNA (rDNA) genes\, we examined whether the Hippo pathway regulates rDNA via HSat3. Our work demonstrates that HSat3 localizes the Hippo factors YAP and TEAD inside the nucleolus\, where YAP directly activates ribosomal RNA (rRNA) transcription. These findings present the first evidence that the Hippo pathway factor YAP directly regulates RNA Polymerase I activity. \nDisparate studies have identified examples of transcription factors that bind repetitive DNA elements through motif recognition. However\, a systematic search for such factors has not been conducted. Using Telomere-to-telomere genome assemblies\, we predicted and validated dozens of new satellite-binding TFs\, many of which are part of highly conserved signaling pathways. Beyond revealing a direct relationship between the Hippo pathway and ribosomal DNA regulation\, this work demonstrates that satellite DNA can encode a broad range of functional motifs\, hinting at new roles for these enormous genomic elements. \nBio: Following his undergraduate studies\, Matt conducted a 1-year research fellowship at EMBL Hamburg\, where he worked on X-ray scattering methods for structural biology. He then earned his PhD in chemical engineering at Stanford University\, where he investigated mechanotransduction and Hippo pathway signaling. Matt continued this research as a postdoc under Kun-Liang Guan at UC San Diego\, where he discovered that Hippo pathway effectors bind repetitive DNA elements. To expand on his newfound interest in repetitive DNA\, Matt returned to Stanford as a postdoctoral researcher under Nicolas Altemose\, where he is studying the functions of satellite repeats as hubs for transcription factor binding. \nHosted by: Professor Karen Miga\, BME Department
URL:https://events.ucsc.edu/event/bme-280b-seminar-satellite-repeats-encode-megabase-scale-transcription-factor-hubs/
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:20260129T130000
DTEND;TZID=America/Los_Angeles:20260129T163000
DTSTAMP:20260406T082115
CREATED:20260105T180456Z
LAST-MODIFIED:20260105T180456Z
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SUMMARY:Allen van Gelder Memorial
DESCRIPTION:You are cordially invited to an event celebrating the life and research legacy of Allen van Gelder\, who passed away in April 2025 after 37 years of dedicated service to the Computer Science and Engineering Department at UC Santa Cruz. \nThursday\, January 29\, 2025\nReception begins 1pm\, Program begins 1:30pm\nAlumni Room\, University Center\, UC Santa Cruz \nPlease RSVP via the following link:\nhttps://forms.gle/iyFTL2aAxLMWdRMU9 \nThe gathering will include three presentations reflecting on Allen’s contributions to computer science\, followed by an opportunity for attendees to share remembrances and stories \nOn Allen’s contributions to databases and logic programming\nJeff Ullman\, Stanford W. Ascherman Professor of Computer Science (Emeritus)\, Computer Science Department\, Stanford University \nOn Allen’s contributions to computer graphics and visualization\nClaudio Silva\, Institute Professor of Computer Science and Engineering\, NYU Tandon School of Engineering\, New York University \nOn Allen’s contributions to satisfiability\nOlaf Beyersdorff\, Professor of Theoretical Computer Science\, Institute of Computer Science\, Friedrich Schiller University Jena \nWhether you were a colleague\, student\, or friend\, we hope you’ll join us in celebrating Allen’s career and its impact.
URL:https://events.ucsc.edu/event/allen-van-gelder-memorial/
LOCATION:University Center\, University Center\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars,Social Gathering
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260202T104000
DTEND;TZID=America/Los_Angeles:20260202T114500
DTSTAMP:20260406T082115
CREATED:20260126T213156Z
LAST-MODIFIED:20260126T213348Z
UID:10009111-1770028800-1770032700@events.ucsc.edu
SUMMARY:ECE Seminar: Advanced Packaging as the Engine of the AI Systems Era
DESCRIPTION:Presenter: Tolga Acikalin\, System and Package Architect\, Lumilens \nDescription: The rapid rise of artificial intelligence and machine learning—most notably recent breakthroughs in large language models—is reshaping the trajectory of the semiconductor industry and ushering in a new era of system innovation. As performance scaling at the device level slows\, heterogeneous integration (HI) has emerged as a foundational technology to sustain advances in computing and communication. By integrating separately manufactured components with diverse functions into a single system\, HI enables new levels of functionality\, performance\, and efficiency that are no longer achievable through traditional scaling alone. \nRealizing the full potential of heterogeneous systems demands a shift toward holistic system-level co-design\, with advanced packaging assuming a central and strategic role. This talk will briefly review the evolution of packaging technologies and then focus on advanced packaging architectures that enable heterogeneous integration.Topics will include advances in 2D and 3D interconnect technologies\, the introduction of novel packaging materials such as glass substrates\, and the growing role of photonic links\, including co-packaged optics enabled by silicon photonics. The talk will conclude with a discussion of power delivery and thermal management as system-level challenges and opportunities that will shape the next generation of high-performance\, energy-efficient systems. \nBio: Tolga Acikalin received his Bachelor of Science degree in Mechanical Engineering from Middle East Technical University in Ankara\, Turkey\, and his Master of Science and Ph.D. degrees from Purdue University in West Lafayette\, Indiana. \nHe joined Intel in 2007 as a Research and Development Engineer\, working on assembly and test pathfinding projects within the Technology and Manufacturing Group in Chandler\, Arizona. From 2013 to 2025\, he was a Principal Engineer at Intel Labs in Santa Clara\, California\, where he led and influenced innovative strategies for heterogeneous system integration\, spanning package- to wafer-scale solutions\, with a strong emphasis on next-generation interconnect technologies. Tolga is currently a System and Package Architect at Lumilens\, where he focuses on next-generation photonic interconnect solutions\, ranging from near-packaged optics to co-packaged optics. \nHis technical interests include co-packaged optics and silicon photonics\, optical and sub-THz to THz RF high-speed interconnects and the associated advanced package architectures\, novel advanced packaging solutions such as glass substrates\, and optical computing. Tolga has authored or co-authored more than 15 peer-reviewed journal and conference publications in leading APS\, ASME\, and IEEE venues\, including best paper awards at IEEE RFIC and JSCC. He holds nine issued patents and more than 27 additional patent filings. \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-seminar-advanced-packaging-as-the-engine-of-the-ai-systems-era/
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:20260202T120000
DTEND;TZID=America/Los_Angeles:20260202T130000
DTSTAMP:20260406T082115
CREATED:20260122T191932Z
LAST-MODIFIED:20260128T171007Z
UID:10009093-1770033600-1770037200@events.ucsc.edu
SUMMARY:Statistics Seminar: Mathematical Foundations for Machine Learning from a Nonlinear Time Series Perspective
DESCRIPTION:Presenter: Jiaqi Li\, William H. Kruskal Instructor\, University of Chicago \nDescription:Modern machine learning (ML) algorithms achieve remarkable empirical success\, yet providing rigorous statistical guarantees remains a major challenge\, particularly in distributional theory and online inference methods. In this talk\, we will introduce a novel framework to provide mathematical foundations for ML by bringing powerful tools in nonlinear time series. First\, we focus on the stochastic gradient descent (SGD) with constant learning rates. By interpreting the SGD sequence as a nonlinear AR(1) process\, we can establish the geometric moment contraction (GMC) for SGD regardless of initializations. By this GMC property\, we can derive refined asymptotic theory of SGD and its averaging variant\, including general moment convergence\, quenched central limit theorems\, quenched invariance principles\, and sharp Berry- Esseen bounds. Then\, we extend this theoretical framework to SGD with dropout regularization\, a widely used but theoretically underexplored technique in deep learning. By establishing GMC under explicit learning-rate and dimensional scaling regimes\, we obtain asymptotic normality and invariance principles for dropout SGD and its averaged version. These results enable online inference\, for which we introduce a fully recursive estimator of the long-run covariance matrix appearing in the limiting distributions. The proposed online confidence intervals with asymptotically correct coverage can be generalized to many other ML algorithms. Overall\, viewing online learning algorithms as nonlinear time series provides a powerful toolkit for deriving statistical guarantees in modern ML\, with implications for high-dimensional stochastic optimization and real-time uncertainty quantification. \nBio:Jiaqi Li is a William H. Kruskal Instructor in the Department of Statistics at the University of Chicago. She obtained her PhD in Statistics from Washington University in St. Louis in 2024. Her research focuses on developing theoretical guarantees and statistical inference methods for machine learning algorithms. She also works on time series data\, especially in the high- dimensional settings with complex temporal and cross-sectional dependency structures. She also\ncollaborates with neuroscientists on applications in fMRI and EEG data. \nHosted by: Statistics Department \nZoom link: https://ucsc.zoom.us/j/96647674332?pwd=rCHfeGpKslaGS5iIPP5Jh29mQiMJID.1
URL:https://events.ucsc.edu/event/statistics-seminar-mathematical-foundations-for-machine-learning-from-a-nonlinear-time-series-perspective/
LOCATION:https://ucsc.zoom.us/j/96647674332?pwd=rCHfeGpKslaGS5iIPP5Jh29mQiMJID.1
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260202T160000
DTEND;TZID=America/Los_Angeles:20260202T170000
DTSTAMP:20260406T082115
CREATED:20260128T184233Z
LAST-MODIFIED:20260128T184233Z
UID:10009126-1770048000-1770051600@events.ucsc.edu
SUMMARY:AM Seminar: Are Graph Learning Methods Actually Learning?
DESCRIPTION:Presenter: Seshadhri Comandur\, Professor of Computer Science\, UCSC \nDescription: There has been a lot of literature on graph machine learning over the past few years\, and a bewildering array of new methods. This talk is based on a series of results making a provocative argument. Maybe many graph machine learning methods are not really that effective\, and the progress we are seeing is an artifact of experimental design and measurement. I will talk about some results showing that low-dimensional embeddings with dot product similarity (arguably the most common graph ML technique) cannot capture salient aspects of real-world graphs. Follow-up work demonstrates that simple benchmarks seem to outperform fancier methods\, and that there are significant shortcomings in existing accuracy measurement. \nBio: C. Seshadhri (Sesh) is a professor of Computer Science at the University of California\, Santa Cruz and an Amazon scholar. Prior to joining UCSC\, he was a researcher at Sandia National Labs\, Livermore in the Information Security Sciences department\, during 2010-2014. His primary interest is the theoretical study of algorithms\, especially those with a mix of graphs and randomization. By and large\, Sesh works at the boundary of theoretical computer science (TCS) and data mining. His work spans many areas: sublinear algorithms\, graph algorithms\, graph modeling\, scalable computation\, and data mining. In the theory world\, his work has resolved numerous open problems in monotonicity testing and graph property testing. A number of his papers in the interface of TCS and applied algorithms have received paper awards at KDD\, WWW\, ICDM\, SDM\, and WSDM. He received the 2019 SDM/IBM Early Career Award for Excellence in Data Analytics. Sesh got his Ph.D from Princeton University and spent two years as a postdoc in IBM Almaden Labs. \nHosted by: Ashesh Chattopadhyay\, Applied Mathematics Department
URL:https://events.ucsc.edu/event/am-seminar-are-graph-learning-methods-actually-learning/
LOCATION:CA
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/01/sesh.jpeg
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