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DTSTART;TZID=America/Los_Angeles:20260406T160000
DTEND;TZID=America/Los_Angeles:20260406T170000
DTSTAMP:20260404T074655
CREATED:20260204T222651Z
LAST-MODIFIED:20260325T181208Z
UID:10009162-1775491200-1775494800@events.ucsc.edu
SUMMARY:AM Seminar: The Thinking Eye: AI That Sees\, Reads\, and Reasons in Medicine
DESCRIPTION:Presenter: Yuyin Zhou\, Assistant Professor\, UCSC \nDescription: Medical AI is undergoing a profound transformation\, evolving from simple pattern recognition to systems capable of complex clinical reasoning. This talk will chart this evolution across three dimensions: data\, models\, and evaluation. I will first highlight the shift from limited\, unimodal datasets to massive multimodal resources. In particular\, I will introduce MedTrinity-25M—a novel collection of over 25 million richly annotated medical images that serves as a foundation for multimodal tasks such as visual question answering and report generation. Building on this\, I will describe how grounding decision processes in a structured medical knowledge graph enables the generation of high-fidelity reasoning chains. Using these chains\, we construct a large-scale medical reasoning dataset\, which in turn allows us to develop a new class of reasoning models. These models not only achieve state-of-the-art performance on multiple clinical Q&A benchmarks but also produce reasoning outputs that physicians across seven specialties have independently verified as clinically reliable\, interpretable\, and more factually accurate than existing large language models. Finally\, the talk will offer a deep dive into the critical evaluation of these advanced models\, moving beyond standard benchmarks to expose their current limitations—particularly in interpreting dynamic clinical scenarios such as tracking disease progression from temporal image sequences. To foster a holistic understanding of the mechanisms underlying these reasoning models\, I will introduce a new evaluation framework that examines performance from two complementary perspectives: their grasp of static knowledge versus their capacity for dynamic reasoning. Together\, these advances point toward a future where AI systems can holistically analyze patient information and function as true collaborative partners in complex medical decision-making. \nBio: Yuyin Zhou is an Assistant Professor of Computer Science and Engineering at UC Santa Cruz. Her research interests lie at the intersection of machine learning and computer vision\, with a primary focus on AI for healthcare and scientific discovery. Her work (70+ peered-reviewed publications with18\,000+ citations) has been recognized with honors including 2025 Google Research Scholar Award\, Best Paper Award at KDD 2025 Health Day and at Computerized Medical Imaging and Graphics 2024\, 2023 Hellman Fellowship\, Best Paper Honorable Mention at DART 2022\, and finalist recognition for the MICCAI Young Scientist Publication Impact Award in 2022. Beyond her research\, Yuyin has organized over 20 workshops and tutorials at major conferences including ICML\, MICCAI\, ML4H\, ICCV\, CVPR\, and ECCV\, with coverage in media outlets such as ICCV Daily and Computer Vision News. She serves as a regular Area Chair for CVPR\, ICLR\, MICCAI\, CHIL\, and ISBI\, an associate editor for SPIE medical imaging\, Image and Vision Computing\, and was the Doctoral Consortium Chair for WACV 2025. \nHosted by: Applied Mathematics Department
URL:https://events.ucsc.edu/event/am-seminar-the-thinking-eye-ai-that-sees-reads-and-reasons-in-medicine/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/ph.d.-presentation-graphic-option2.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260406T160000
DTEND;TZID=America/Los_Angeles:20260406T170000
DTSTAMP:20260404T074655
CREATED:20260318T171956Z
LAST-MODIFIED:20260318T171956Z
UID:10011340-1775491200-1775494800@events.ucsc.edu
SUMMARY:Statistics Seminar: Some Recent Results on Transfer Learning
DESCRIPTION:Presenter: Oscar Hernan Madrid Padilla\, Assistant Professor\, University of California\, Los Angeles \nDescription: In the first part of the talk\, I will introduce TRansfer leArning via guideD horseshoE prioR (TRADER)\, a novel approach enabling multi-source transfer through pre-trained models in high-dimensional linear regression. TRADER shrinks target parameters towards a weighted average of source estimates\, accommodating sources with different scales. Theoretical investigation shows that TRADER achieves faster posterior contraction rates than standard continuous shrinkage priors when sources align well with the target while preventing negative transfer from heterogeneous sources. Extensive numerical studies and a real-data application demonstrate that TRADER improves estimation and inference accuracy over state-of-the-art transfer learning methods. In the second part of the talk\, I will discuss some ongoing work involving transfer learning in nonparametric regression with ReLU networks \nBio: Oscar Madrid Padilla is a tenure-track Assistant Professor in the Department of Statistics at the University of California\, Los Angeles. Previously\, from July 2017 to June 2019\, he was a Neyman Visiting Assistant Professor in the Department of Statistics at the University of California\, Berkeley. Before that\, he earned his Ph.D. in Statistics from The University of Texas at Austin in May 2017 under the supervision of Professor James Scott. He completed his undergraduate degree\, a B.S. in Mathematics\, at CIMAT in Mexico in April 2013. \nHosted by: Statistics Department 
URL:https://events.ucsc.edu/event/statistics-seminar-some-recent-results-on-transfer-learning/
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260413T160000
DTEND;TZID=America/Los_Angeles:20260413T170000
DTSTAMP:20260404T074655
CREATED:20260312T223749Z
LAST-MODIFIED:20260312T223836Z
UID:10011318-1776096000-1776099600@events.ucsc.edu
SUMMARY:Statistics Seminar: Calibration Weighting-Style Diagnostics for Nonlinear Bayesian Hierarchical Models
DESCRIPTION:Presenter: Dr. Ryan Giordano\, UC Berkeley Statistics \nDescription: Multilevel Regression with Post-stratification (MrP) has become a workhorse method for estimating population quantities using non-probability surveys\, and is the primary alternative to traditional survey calibration weights\, e.g.~ as computed by raking. For simple linear regression models\, MrP methods admit “equivalent weights”\, allowing for direct comparisons between MrP and traditional calibration weights (Gelman 2006). In the present work\, we develop a more general framework for computing and interpreting “MrP local equivalent weights” (MrPlew)\, which admit direct comparison with calibration weights in terms of important diagnostic quantities such as covariate balance\, frequentist sampling variability\, and partial pooling. MrPlew is based on a local approximation\, which we show in theory and practice to be accurate and meaningful for the target diagnostics. Importantly\, MrPlew can be easily computed based on existing MCMC samples and conveniently wraps standard MrP software implementations. \nBio: Dr. Ryan Giordano is currently an assistant professor of statistics at UC Berkeley. Dr. Ryan Giordano earned a PhD in Statistics from UC Berkeley advised by Michael Jordan\, Tamara Broderick\, and Jon McAuliffe\, an MSc with distinction in econometrics and mathematical economics from the London School of Economics\, and undergraduate degrees in mathematics and engineering mechanics from the University of Illinois in Urbana-Champaign. Dr. Ryan Giordano has worked as a postdoctoral researcher at MIT under Tamara Broderick\, as an engineer for Google and HP\, and served for two years as an education volunteer in the US Peace Corps in Kazakhstan. Dr. Ryan Giordano’s research interests include machine learning\, variational inference\, Bayesian methods\, robustness quantification\, and what it even means to do statistics at all. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-calibration-weighting-style-diagnostics-for-nonlinear-bayesian-hierarchical-models/
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260420T160000
DTEND;TZID=America/Los_Angeles:20260420T170000
DTSTAMP:20260404T074655
CREATED:20260331T180549Z
LAST-MODIFIED:20260331T180549Z
UID:10011821-1776700800-1776704400@events.ucsc.edu
SUMMARY:AM Seminar: Variational Inference and Density Estimation with Non-Negative Tensor Train
DESCRIPTION:Presenter: Dr. Xun Tang\, Stanford University \nDescription: This talk covers an efficient numerical approach for compressing a high-dimensional discrete distribution function into a non-negative tensor train (NTT) format. The two settings we consider are variational inference and density estimation\, whereby one has access to either the unnormalized analytic formula of the distribution or the samples generated from the distribution. In particular\, the compression is done through a two-stage approach. In the first stage\, we use existing subroutines to encode the distribution function in a tensor train format. In the second stage\, we use an NTT ansatz to fit the obtained tensor train. For the NTT fitting procedure\, we use a log barrier term to ensure the positivity of each tensor component\, and then utilize a second-order alternating minimization scheme to accelerate convergence. In practice\, we observe that the proposed NTT fitting procedure exhibits drastically faster convergence than an alternative multiplicative update method that has been previously proposed. Through challenging numerical experiments\, we show that our approach can accurately compress target distribution functions. \nBio: Xun Tang is a postdoc in Stanford University\, department of mathematics\, hosted by Prof. Lexing Ying. Xun works on tensor network methods for scientific computing and data science\, and Xun also works on optimal transport algorithms. Xun will join HKUST department of mathematics in August 2026 as an incoming assistant professor. \nHosted by: Applied Mathematics Department
URL:https://events.ucsc.edu/event/am-seminar-variational-inference-and-density-estimation-with-non-negative-tensor-train/
LOCATION:Jack Baskin Engineering Building\, 372
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/03/BElogoWHITE.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260420T160000
DTEND;TZID=America/Los_Angeles:20260420T170000
DTSTAMP:20260404T074655
CREATED:20260331T181211Z
LAST-MODIFIED:20260331T181211Z
UID:10011822-1776700800-1776704400@events.ucsc.edu
SUMMARY:Statistics Seminar: Hierarchical Clustering with Confidence
DESCRIPTION:Presenter: Snigdha Panigrahi\, Associate Professor\, Department of Statistics\, University of Michigan \nDescription:Agglomerative hierarchical clustering is one of the most widely used approaches for exploring how observations in a dataset relate to each other. However\, its greedy nature makes it highly sensitive to small perturbations in the data\, often producing different clustering results and making it difficult to separate genuine structure from spurious patterns. In this talk\, I will show how randomizing hierarchical clustering can be useful not just for measuring stability but also for designing valid hypothesis testing procedures based on the clustering results. We propose a simple randomization scheme to construct valid p-values at each node of a hierarchical clustering dendrogram\, quantifying evidence against greedy merges while controlling the Type I error rate. Our method applies to any linkage without case-specific derivations\, is substantially more powerful than existing selective inference approaches\, and provides an estimate of the number of clusters with a probabilistic guarantee on overestimation. \nBio:Snigdha Panigrahi is an Associate Professor of Statistics at the University of Michigan\, where she also holds a courtesy appointment in the Department of Biostatistics. She received her PhD in Statistics from Stanford University in 2018 and has been a faculty member at Michigan since then. Her research focuses on converting purely predictive machine learning algorithms into principled inferential methods. She is an elected member of the International Statistical Institute\, and her work has been recognized with an NSF CAREER Award and the Bernoulli New Researcher’s Award. Her editorial service\, past and present\, includes Journal of Computational and Graphical Statistics\, Bernoulli\, and Journal of the Royal Statistical Society: Series B. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-hierarchical-clustering-with-confidence/
LOCATION:Jack Baskin Engineering Building\, 156
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/03/ph.d.-presentation-graphic-option-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260504T160000
DTEND;TZID=America/Los_Angeles:20260504T170000
DTSTAMP:20260404T074655
CREATED:20260312T222740Z
LAST-MODIFIED:20260312T222740Z
UID:10011317-1777910400-1777914000@events.ucsc.edu
SUMMARY:Statistics Seminar: Advancing Statistical Rigor in Single-Cell and Spatial Omics Using In Silico Control Data
DESCRIPTION:Presenter: Guan’ao Yan\, Assistant Professor\, Michigan State University \nDescription: Single-cell and spatial transcriptomics technologies now let us map cellular diversity and tissue organization at high resolution\, but the computational methods built to analyze these data are difficult to evaluate in a rigorous\, reproducible way. Two key barriers are the lack of realistic synthetic data with known ground truth and the ambiguity in how we define biologically meaningful spatial patterns. This talk will introduce two simulation frameworks—scReadSim for single-cell RNA-seq and ATAC-seq data\, and scIsoSim for isoform-level expression and splicing—that generate realistic sequencing reads while preserving user-specified truth. These tools enable fair\, controlled benchmarking of quantification and splicing methods across experimental protocols. The talk will also present a systematic review of 34 methods for detecting spatially variable genes (SVGs) in spatial transcriptomics data\, proposing a new categorization of SVGs and outlining how future benchmarks should be designed. Overall\, the goal is to improve statistical rigor\, interpretability\, and comparability in single-cell and spatial omics analysis. \nBio: Guan’ao Yan is an Assistant Professor of Computational Mathematics\, Science & Engineering at Michigan State University. He received his Ph.D. in Statistics from UCLA. His research focuses on statistical and computational methods for modern statistical genomics\, particularly single-cell and spatial omics\, with an emphasis on rigorous benchmarking\, interpretability\, and biomedical discovery. \nHosted by: Statistics Department
URL:https://events.ucsc.edu/event/statistics-seminar-advancing-statistical-rigor-in-single-cell-and-spatial-omics-using-in-silico-control-data/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/ph.d.-presentation-graphic-option-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260513T120000
DTEND;TZID=America/Los_Angeles:20260513T190000
DTSTAMP:20260404T074655
CREATED:20260312T162246Z
LAST-MODIFIED:20260312T162246Z
UID:10011309-1778673600-1778698800@events.ucsc.edu
SUMMARY:Santa Cruz Launchpad Student Startup Competition & Job Fair
DESCRIPTION:The 10th annual Santa Cruz Launchpad event combines a student startup competition with a community career fair\, all under one roof! This year’s event takes place at the The Grove at the Santa Cruz Beach Boardwalk (400 Beach St\, Santa Cruz\, CA 95060) on Wednesday\, May 13\, 2026. \nThe first half of the day spotlights emerging startups in a live startup competition\, with cash prizes. The second half shifts into a job fair featuring 25+ local companies and 300+ opportunities\, including part-time roles\, full-time positions\, and internships. \nTHIS EVENT IS FREE AND OPEN TO THE PUBLIC TO ATTEND. ADVANCED REGISTRATION IS REQUIRED. \n\n\n\n\n\n\n\n\n2026 Schedule\n12-4pm: Student business plan pitches (open to the public) \n4-4:45pm: Employer Table Setup \n5-7pm: Job Fair + Networking (open to the public) \nStudent Startup Competition | 12-4pm \nFrom 1-4pm\, students will compete in a startup competition for cash prizes. The pitch competition portion of the event typically includes 12 student teams who each have five minutes each to deliver their pitches to a judge panel. Check out 2025 winners here. This year’s competition is open to both college and high school students in Santa Cruz County. If you are a student at UC Santa Cruz\, Cabrillo College or a high school student in Santa Cruz County or Pajaro Valley Unified School District and would like to compete\, click the button below. \nApplications are due Wednesday\, April 8\, 2026 at 5pm: https://bit.ly/4d9MaqW \nPitch Prize Categories for 2026  \n\n\n• Biotech/Health (QB3) = $5\,000\n• Social Impact = $5\,000\n• Technology = $5\,000\n• Main Street = $2\,000\n• Runners Up =  $500 each\n• People’s Choice Award = $2\,000\n• High School Award = $2\,000\n\n\n\n\n\n\n– Top winners eligible to participate in the SC Accelerates program.\n– All teams will receive Santa Cruz Works Perks Package by OneValley (Value $1M)\n\n– Every team that qualifies for the final round will receive a cash prize!\n\n\n\n\n\n\n\n\n\n\n\nJob Fair | 5-7pm \nFrom 5-7pm\, job seekers will have the opportunity to interact with 20+ local companies offering 200+ jobs and internships ranging from engineering to marketing\, healthcare\, project management\, sales\, customer support\, tech\, and more. \nThis event allows students\, job seekers\, and professionals of all experience levels and backgrounds the opportunity to show off their resumes\, find career opportunities\, and make new connections. There is no charge for job seekers to attend the job fair. The job fair is open to the public (you do not need to be a student or pitch contest participant to participate). But all attendees must register in advance! https://www.eventbrite.com/e/santa-cruz-launchpad-2026-tickets-1976673979082 \nPrevious employers included Joby Aviation\, Capstan Medica\, Paystand\, Santa Cruz Bicycles\, Cruz Foam\, Digital NEST\, Bay Federal Credit Union\, Mynt\, Central California Alliance for Health\, Unnatural Products\, Santa Cruz Seaside Company\, California Highway Patrol\, BMO\, PVUSD\, and more. \nA list of participating employers will be shared at the beginning of May. \n\n\n\n\nThis year’s event is proudly hosted by UCSC Center for Innovation and Development (CIED)\, UC Santa Cruz Innovation & Business Engagement Hub\, UCSC Career Success\, and UCSC QB3 Santa Cruz Works\, Cabrillo College\, \, Pajaro Valley Unified School District (PVUSD)\, and Santa Cruz County Office of Education (SCCOE)\, \n\n\n\n\n\n\n\nFree Attendee Registration\n\n\n\n\n\n\nEmployer Registration
URL:https://events.ucsc.edu/event/santa-cruz-launchpad-student-startup-competition-job-fair/
LOCATION:the Grove\, 400 Beach Street\, Santa Cruz\, CA\, 95060\, United States
CATEGORIES:Social Gathering,Undergraduate
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/03/LP26EventBrite.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20270315T000000
DTEND;TZID=America/Los_Angeles:20270315T235959
DTSTAMP:20260404T074655
CREATED:20251118T004258Z
LAST-MODIFIED:20251118T004433Z
UID:10005174-1805068800-1805155199@events.ucsc.edu
SUMMARY:Summer Live in the Schedule of Classes
DESCRIPTION:The Summer Session Schedule of Classes goes live today. Explore course descriptions\, prerequisites\, and meeting times to start planning early for summer enrollment. Email summer@ucsc.edu with questions or call 831-459-5373.
URL:https://events.ucsc.edu/event/summer-live-in-the-schedule-of-classes/2027-03-15/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20280315T000000
DTEND;TZID=America/Los_Angeles:20280315T235959
DTSTAMP:20260404T074655
CREATED:20251118T004258Z
LAST-MODIFIED:20251118T004433Z
UID:10005175-1836691200-1836777599@events.ucsc.edu
SUMMARY:Summer Live in the Schedule of Classes
DESCRIPTION:The Summer Session Schedule of Classes goes live today. Explore course descriptions\, prerequisites\, and meeting times to start planning early for summer enrollment. Email summer@ucsc.edu with questions or call 831-459-5373.
URL:https://events.ucsc.edu/event/summer-live-in-the-schedule-of-classes/2028-03-15/
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/11/Events-Calendar-Enrollment-Open-1-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20290315T000000
DTEND;TZID=America/Los_Angeles:20290315T235959
DTSTAMP:20260404T074655
CREATED:20251118T004258Z
LAST-MODIFIED:20251118T004433Z
UID:10005176-1868227200-1868313599@events.ucsc.edu
SUMMARY:Summer Live in the Schedule of Classes
DESCRIPTION:The Summer Session Schedule of Classes goes live today. Explore course descriptions\, prerequisites\, and meeting times to start planning early for summer enrollment. Email summer@ucsc.edu with questions or call 831-459-5373.
URL:https://events.ucsc.edu/event/summer-live-in-the-schedule-of-classes/2029-03-15/
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/11/Events-Calendar-Enrollment-Open-1-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20300315T000000
DTEND;TZID=America/Los_Angeles:20300315T235959
DTSTAMP:20260404T074655
CREATED:20251118T004258Z
LAST-MODIFIED:20251118T004433Z
UID:10005177-1899763200-1899849599@events.ucsc.edu
SUMMARY:Summer Live in the Schedule of Classes
DESCRIPTION:The Summer Session Schedule of Classes goes live today. Explore course descriptions\, prerequisites\, and meeting times to start planning early for summer enrollment. Email summer@ucsc.edu with questions or call 831-459-5373.
URL:https://events.ucsc.edu/event/summer-live-in-the-schedule-of-classes/2030-03-15/
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