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DTSTART;TZID=America/Los_Angeles:20260821T110000
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SUMMARY:Nava\, A. (AM) - Machine-Learning Methods for Prediction of Biological Systems
DESCRIPTION:Advances in microscopy have enabled the collection of high-quality single-cell datasets\, providing new opportunities to identify the mechanisms underlying complex biological processes. In this work\, we develop machine-learning frameworks using single-cell temporal data with the goal of predicting and providing insights into these mechanisms. We produce frameworks for two biological systems\, bacterial spore germination\, the process in which bacteria begin metabolic activity\, and embryonic stem cell organization. Bacterial spore germination is a critical transition in which the spore becomes susceptible to control techniques\, however the mechanisms governing this transition are unknown. We develop a machine-learning framework that predicts germination timing at the single-spore level\, enabling identification of predictive features associated with germination that may reflect underlying biological mechanisms. Embryonic stem cell organization has been shown to closely recapitulate formations seen in embryonic development\, but the mechanisms driving their spatial organization remain unclear. Here\, we develop a simple agent-based model in which spatial organization is driven by cell-cell interaction parameters. We then train a machine-learning framework to infer these underlying interaction parameters from simulated data and propose that this approach can be extended to other agent-based models calibrated to experimental stem cell data. These studies demonstrate that machine-learning models can be used for prediction using single-cell temporal data\, as well as tools to develop mechanistic hypotheses. \n  \nEvent Host: Alexandra Nava\, Ph.D. Student\, Applied Mathematics  \nAdvisor: Marcella Gomez \nZoom: https://ucsc.zoom.us/j/98821445104?pwd=OFAKwGrObh02bPLgXieXsDcTxxS1Cj.1 \nPasscode: 392769
URL:https://events.ucsc.edu/event/nava-a-am-machine-learning-methods-for-prediction-of-biological-systems/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260818T140000
DTEND;TZID=America/Los_Angeles:20260818T160000
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SUMMARY:Lupin-Jimenez\, L. (AM) - Data-Driven Deep Learning for Turbulent Phenomena: Regional Ocean Prediction and Assimilation\, Spectral Bias in Diffusion Models\, and Equation Discovery
DESCRIPTION:Deep learning models trained on simulation and reanalysis data can now emulate turbulent geophysical flows at a small fraction of the computational cost of numerical solvers.\nTheir scientific utility depends on physical consistency\, which for the systems studied here\nrests in large part on spectral fidelity\, the accurate reconstruction of variance across spatial\nscales. This document presents two published studies and two studies in progress that develop\, analyze\, and apply data-driven methods for turbulent phenomena along that thread.\nThe first study develops FCDS\, a framework that autoregressively emulates surface ocean\ndynamics over the Gulf of Mexico at 8 km resolution and simultaneously downscales and\nbias-corrects the emulated fields to 4 km\, with a spectral loss that keeps decadal integrations stable and statistically consistent with a high-resolution reanalysis. The second study\ndevelops a neural-operator-conditioned denoising diffusion model that reconstructs regional\nsurface ocean states from Lagrangian-like observations at 99% and 99.9% sparsity without a\nbackground dynamical model\, and shows that the recovered small-scale dynamics are visible\nin spectral diagnostics but not in pointwise metrics. The third study derives a signal-tonoise theory of spectral bias in diffusion models for 2D turbulence\, organized around the\ncrossover wavenumber kc(τ) at which signal and noise contribute equal power\, and validates\nits predictions on a sweep of 28 models spanning seven forcing wavenumbers and four noise\nschedulers. The fourth study develops a window-pair spectral method for discovering governing equations from single-point sensor measurements of soliton dynamics in a superfluid\nwave flume\, replacing noise-amplifying instantaneous derivatives with finite-time spectral\nshifts and verifying the discovered equations against a measured-scalar null model. A concluding chapter summarizes the results and outlines future work on novel architectures and\nmethods for data-driven emulation of physical simulations. \nEvent Host: Leonard Lupin-Jimenez\, Ph.D. Student\, Applied Mathematics  \nAdvisor: Ashesh Chattopadhyay \nZoom: https://ucsc.zoom.us/j/97866640488?pwd=UJdTs3sxKfFbz5mabKLIyx5ZYF90J9.1 \nPasscode: 815911
URL:https://events.ucsc.edu/event/lupin-jimenez-l-am-data-driven-deep-learning-for-turbulent-phenomena-regional-ocean-prediction-and-assimilation-spectral-bias-in-diffusion-models-and-equation-discovery/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260818T100000
DTEND;TZID=America/Los_Angeles:20260818T110000
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SUMMARY:Gutie\, J. (SciCAM) -  SORh: Hyperbolic Relaxation Methods For Elliptic Problems In Computational Fluid Dynamics
DESCRIPTION:This thesis explores iterative methods for solving elliptic partial differential equations (PDEs)\, which are used in computational fluid dynamics (CFD) to model a wide range of physical phenomena. The primary application of interest here is self-gravity\, modeled by Poisson’s equation. Although many numerical approaches exist\, including direct matrix inversion\, FFT-based methods\, and classical iterative methods such as Jacobi and Gauss-Seidel\, these approaches involve tradeoffs in computational cost\, scalability\, implementation complexity\, and adaptability to changing boundary conditions and problem configurations. \nTherefore\, we introduce SORh\, a simple and efficient relaxation method derived from a hyperbolic reformulation of Poisson’s equation. SORh generalizes classical successive over-relaxation (SOR) by providing independent control of residual relaxation and the directional propagation of Gauss–Seidel corrections. We present formulations of SORh in one and two spatial dimensions and investigate its stability\, accuracy\, and computational performance through analytical derivations and numerical comparisons with established relaxation methods. The results identify favorable SORh formulations\, clarify their relationships to classical relaxation methods\, and demonstrate improved convergence on selected test problems. Finally\, we demonstrate applications of SORh to astrophysical self-gravity simulations in the FLASH code and to magnetohydrodynamic (MHD) divergence cleaning. \nEvent Host: Jonathan Guite\, M.S. Candidate\, Scientific Computing & Applied Mathematics  \nAdvisor: Dongwook Lee \nZoom: https://ucsc.zoom.us/j/92153750104?pwd=ZdLiDZeLqOAlVNX9C4bCloKno9tAeB.1 \nPasscode: 769232
URL:https://events.ucsc.edu/event/gutie-j-scicam-sorh-hyperbolic-relaxation-methods-for-elliptic-problems-in-computational-fluid-dynamics/
CATEGORIES:Ph.D. Presentations
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DTSTART;TZID=America/Los_Angeles:20260601T160000
DTEND;TZID=America/Los_Angeles:20260601T170000
DTSTAMP:20260430T211522Z
CREATED:20260421T175854Z
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SUMMARY:AM Seminar: Using Math and Experiments to Study the Control of Cell Metabolism
DESCRIPTION:Presenter: Denis Titov\, Assistant Professor\, University of California\, Berkeley \nDescription: Cells run thousands of chemical reactions simultaneously\, and these reactions must be precisely controlled—like a thermostat that prevents overheating. When this control fails\, diseases including diabetes\, cardiovascular disease\, and fatty liver disease result. One key control mechanism is allosteric regulation\, where a small molecule binds to an enzyme and changes its activity. Allosteric regulation is among the most conserved features of cellular life\, yet the functions it serves remain one of the oldest unsolved problems in biology. Several roles have been proposed\, but since the discovery of allostery in the 1950s\, no one has systematically disabled it in metabolic enzymes and measured the consequences. Four technological advances now converge to make this possible. CRISPR enables precise genome editing of allosteric sites. Structural biology has mapped which residues to target. LC-MS metabolomics makes metabolic phenotyping routine. The speed of modern computers enables detailed modeling of allosteric regulator function. In this talk\, I will describe our work developing and testing the first-in-class biophysical model of a metabolic pathway that accurately predicts responses to the addition or removal of allosteric regulators. Our work provides a framework for developing predictive models of cell metabolism that can be used for drug development or for engineering cells for energy production and chemical synthesis. Within a decade\, we plan to develop a model that accurately predicts metabolic activity in any human cell type under any condition. \nAbout the speaker: Denis Titov is an Assistant Professor at the University of California Berkeley with joint appointments in the Department of Metabolic Biology and Nutrition\, Department of Molecular and Cell Biology\, and Center for Computational Biology. Dr. Titov’s long-term research dream is to improve the understanding of human metabolic pathway regulation to a point where we can accurately predict metabolic pathway activity in any cell type\, under any condition\, and in response to any perturbation. Dr. Titov is interested in the following broad questions: How does metabolic homeostasis emerge from the activities of individual enzymes? What trade-offs drove the evolution of specific metabolic pathways and their control mechanisms? How to effectively combine data and biophysical models to simulate metabolic pathways? To tackle these questions\, Titov lab is using a combination of biochemistry\, mathematical modeling\, physiology\, custom instrumentation\, and genetically encoded tool development to study metabolism in mammalian cells and reconstituted biochemical systems. \nThis seminar is hosted by Professor Nilah Ioannidis.
URL:https://events.ucsc.edu/event/am-seminar-using-math-and-experiments-to-study-the-control-of-cell-metabolism/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260521T090000
DTEND;TZID=America/Los_Angeles:20260521T143000
DTSTAMP:20260326T204610Z
CREATED:20260326T204610Z
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SUMMARY:Annual BE Student Project Showcase
DESCRIPTION:Join Baskin Engineering for our annual Student Project Showcase to celebrate the innovative work and accomplishments of undergraduate engineers in capstone courses and research pathways. The broader campus community\, parents\, and industry partners are invited to view the culmination of student work. \nThe day begins with oral presentations from nominated “best-in-class” teams and those working on industry-sponsored projects. Following this\, all students will participate in a comprehensive Poster Session featuring project outcomes with some teams including table-top demonstrations of functional hardware. \nEvent Details: \n\nDate: May 21\, 2026\nOral Presentations (Nominated/Industry Teams): 9:00 AM to 11:00 AM\, Engineering 2\, Room 180\nPoster Session (All Student Teams): 11:30 AM to 2:30 PM\, Engineering Courtyard
URL:https://events.ucsc.edu/event/be-student-project-showcase-2026/
CATEGORIES:Lectures & Presentations,Undergraduate
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260518T160000
DTEND;TZID=America/Los_Angeles:20260518T170000
DTSTAMP:20260429T152454Z
CREATED:20260429T152454Z
LAST-MODIFIED:20260429T152454Z
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SUMMARY:AM Seminar: Dissecting Complex Disease Mechanisms with Causal Inference and Deep Learning
DESCRIPTION:Presenter: Dr. David A. Knowles\, New York Genome Center & Columbia University \nDescription: Many human diseases have a substantial genetic component\, which association studies are increasingly capable of characterizing\, empowered by ever-growing sample sizes. These associations have the potential to elucidate complex disease biology and prioritize therapeutic interventions. However\, it is challenging to determine the impacted genes\, pathways and cellular states since most risk variants are noncoding. I will describe strategies we have explored to address this challenge\, particularly in the context of Alzheimer’s disease. We have mapped genetic effects on expression\, splicing and RNA editing in over 10k postmortem brain samples\, enabling interpretation of common variant associations. We developed a Mendelian randomization-based causal network inference method to estimate how genetic effects propagate through the gene network to converge on disease risk. We show that deep learning models of pre- and post- transcriptional regulation can refine functional fine-mapping\, improve the portability of polygenic risk scores across ancestries\, and increase power in novel annotation-aware noncoding rare variant association studies. Finally\, we designed a CRISPR/Cas13-based strategy to perform isoform-specific knockdown\, opening the door for isoform-resolved functional characterization of putative disease-causal transcriptomic changes. \nAbout the speaker: Dr. Knowles studied Natural Sciences and Information Engineering at Cambridge before obtaining an MSc in Bioinformatics and Systems Biology at Imperial College London. During his PhD in the Cambridge University Machine Learning Group under Zoubin Ghahramani he worked on variational inference and Bayesian nonparametric models. He was a postdoc at Stanford developing methods for functional genomics with Daphne Koller (CS)\, Sylvia Plevritis (Computational Systems Biology/Radiology) and Jonathan Pritchard (Genetics/Biology). At Columbia\, he is an Associate Professor of Computer Science\, an Interdisciplinary Appointee in Systems Biology and an Affiliate Member of the Data Science Institute. He is also a Core Faculty Member at the New York Genome Center. His group develops methods to better understand the genetic basis of human disease. \n\n\n\nThis seminar is hosted by Professor Nilah Ioannidis.
URL:https://events.ucsc.edu/event/am-seminar-dissecting-complex-disease-mechanisms-with-causal-inference-and-deep-learning/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260515T180000
DTEND;TZID=America/Los_Angeles:20260516T180000
DTSTAMP:20260508T194542Z
CREATED:20260428T221013Z
LAST-MODIFIED:20260508T194542Z
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SUMMARY:NemoClaw NVIDIA x ASUS Hackathon @ UC Santa Cruz
DESCRIPTION:Welcome to the premier physical AI hackathon on the West Coast. We are bringing together the top 200 AI\, infrastructure\, and hardware engineers to build autonomous\, agentic applications on the NVIDIA NemoClaw stack. \n​You aren’t just calling APIs\, you are building on enterprise-grade hardware. \n​The Tracks: \n\nThe Edge Track: 40 exclusive teams will be granted physical\, on-site access to an ASUS DGX Spark unit to build and deploy locally.\n​The Cloud Track: Teams will build the exact same stack utilizing fully sponsored cloud compute instances via Brev.dev.\n\n​The Arsenal & Prizes: Every team builds on a unified playing field. The top projects will take home heavy enterprise hardware\, including: \n\n​NVIDIA Jetson Orin Nanos\n​The ASUS Ascent (DGX Spark)\n​Jensen Huang signed NVIDIA hats & premium swag\n​High-value Brev.dev compute credits\n​Monitors\n​Internship Opportunities\n\n​The Details: \n\n​Who: Open to the top engineers at UC Santa Cruz and local feeder universities.\n​Food: Fully catered for 24 hours. Energy\, caffeine\, and meals are on us.\n​Special Guests*: Opening and closing ceremonies featuring VIP industry leaders (to be announced).\n​Title Sponsors: Nvidia\, ASUS\, Baskin School of Engineering\n\nRegister today!  \n​Space is strictly capped at 200 builders. Registration requires application approval. \n*May subject to change \n 
URL:https://events.ucsc.edu/event/nvidia-hackathon-2026/
LOCATION:Kresge College\, R-3 Suites\, Santa Cruz\, CA\, 95064
CATEGORIES:Competition,Meetings & Conferences
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260515T130000
DTEND;TZID=America/Los_Angeles:20260515T160000
DTSTAMP:20260429T224549Z
CREATED:20260306T005653Z
LAST-MODIFIED:20260429T224549Z
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SUMMARY:STEM Culture Festival
DESCRIPTION:The STEM Culture Festival is returning to UC Santa Cruz on Friday\, May 15 from 1-4pm in the Baskin Engineering Courtyard. Join us! \nThis year\, we’re expanding with even more performances\, activities\, and creative ways to celebrate UCSC’s vibrant\, diverse\, and excellent STEM culture!  \nWhat to expect: \n\nCuban Dance Master Susana Arenas and her troupe of Orisha dancers led by Cuban Drum Master Toribio Garcia return for a rousing\, communal dance\n\nStudent performers: Los Mejicas and their traditional baile folklórico followed by an open dance lesson/performance by Slug N’ Boots\n\nSTEM-themed drag performances and spoken word poetry by student creatives \n\nAssociate Vice Chancellor for Student Success and Equity Dr. Ebonee Williams (Chemical Engineering\, University of Washington ‘04) will share an inspirational talk on “Bringing our whole selves to STEM!”\n\nEl Buen Taco and Falafel Santa Cruz will be serving delicious food\, completely FREE for all attendees who engage with the student orgs and their activities\n\nMore than just your standard student organization tabling: Games\, interactive demos\, culturally themed activities\, and opportunities to learn more about clubs from all over campus \n\nRaffle for gift cards to be awarded every hour from 1-4pm – must be present to win! \n\nThis event will take place in the Baskin Engineering Courtyard and will be open to all UCSC students\, staff\, and faculty. \nThe STEM Culture Festival celebrates and elevates the many backgrounds\, cultures\, and identities that intersect with our work as scientists\, engineers\, educators\, and members of the UCSC community. It is a rare opportunity when all of UCSC is invited to meet at the engineering school for a time of joy and togetherness. We enthusiastically invite you to attend and be in community with us – especially now in these tumultuous times of division and disunity.  \nThis event represents a collaboration between Baskin Engineering\, the Women’s Center\, the Lionel Cantú Queer Resource Center\, El Centro Latinx and Chicanx Resource Center\, the Asian American and Pacific Islander Resource Center\, the Physical and Biological Sciences Division\, and the Genomics Institute.
URL:https://events.ucsc.edu/event/stem-culture-festival-2026/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Concerts,Performances,Social Gathering,Undergraduate
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260511T160000
DTEND;TZID=America/Los_Angeles:20260511T170000
DTSTAMP:20260414T161025Z
CREATED:20260414T161025Z
LAST-MODIFIED:20260414T161025Z
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SUMMARY:AM Seminar: Column Subset Selection: Theory\, Structure\, and Algorithms
DESCRIPTION:Presenter: Anil Damle\, Associate Professor\, Cornell University \nDescription: The column subset selection problem is a classical topic in numerical linear algebra\, with renewed interest driven by applications in computational quantum chemistry\, integral equations\, model reduction\, and model compression in machine learning. This talk surveys recent advances that clarify how structural properties of a matrix influence the performance of column selection algorithms. We focus on structure-aware and randomized methods\, highlighting both theoretical guarantees and practical algorithmic consequences. \nAbout the speaker: Anil Damle is an associate professor of computer science at Cornell University. His research focuses on the development and analysis of robust and efficient algorithms in applied and computational mathematics that exploit structure coming from underlying physical or statisical models. He interfaces with a broad range of application areas\, and his work is inherently interdisciplinary—with the ultimate goal of developing algorithms that are usable for practitioners. He received his PhD from Stanford University in computational and mathematical engineering (ICME)\, and his MS in applied mathematics and BS in applied mathematics and computer engineering from the University of Colorado\, Boulder. \nThis seminar is hosted by Applied Mathematics.
URL:https://events.ucsc.edu/event/am-seminar-column-subset-selection-theory-structure-and-algorithms/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260504T160000
DTEND;TZID=America/Los_Angeles:20260504T170000
DTSTAMP:20260430T212558Z
CREATED:20260430T212558Z
LAST-MODIFIED:20260430T212558Z
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SUMMARY:AM Seminar:  Engineering the Earth’s Climate
DESCRIPTION:Presenter: Dr. Pulkit Dubey\, Postdoc\, UC Santa Cruz \nDescription: Neural climate emulators such as NeuralGCM and LUCIE offer efficient\, differentiable alternatives to General Circulation Models (GCMs)\, producing climate predictions at a fraction of the cost. While work to date has focused largely on predictive accuracy\, we leverage differentiability to study control of long-horizon climatological targets. Classical GCMs approach this via adjoint-based optimization. Backpropagation through time (BPTT) is its neural-network analog and inherits the same chaotic gradient explosion at long rollouts. We combine BPTT-based sensitivities with receding-horizon optimization to mitigate the chaotic divergence and enable meaningful control over climatological targets. We illustrate with two candidate climate-cooling strategies and close by sketching reinforcement-learning extensions. \nAbout the speaker: Pulkit Dubey is a postdoc in the Department of Applied Mathematics at UC Santa Cruz. He earned his PhD at the University of New Hampshire on the simulation and modeling of turbulent flows\, where he developed hybrid solvers for 2D turbulence. He joined UCSC in September 2025\, where he works on control strategies for neural climate emulators\, enabling long-horizon control over statistical targets in chaotic dynamical systems. \nThis seminar is hosted by Professor Nilah Ioannidis.
URL:https://events.ucsc.edu/event/am-seminar-engineering-the-earths-climate/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260427T160000
DTEND;TZID=America/Los_Angeles:20260427T170000
DTSTAMP:20260408T192436Z
CREATED:20260408T192436Z
LAST-MODIFIED:20260408T192436Z
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SUMMARY:AM Seminar: Machine Learning in Molecular Simulations: From Free Energy to Vibrational Spectroscopy
DESCRIPTION:Presenter: Marcos Calegari Andrade\, Assistant Professor\, Chemistry and Biochemistry\, UC Santa Cruz \nDescription: In this talk\, I will demonstrate how neural networks can represent the high-dimensional potential energy surfaces of many-body systems. By achieving the accuracy of first-principles quantum calculations at a fraction of the computational cost\, these models enable atomistic simulations of condensed matter at unprecedented scales. I will discuss how this approach provides a detailed lens into chemical reaction dynamics under experimentally relevant conditions and facilitates the direct calculation of observables\, such as vibrational spectra\, effectively bridging the gap between theoretical simulation and experimental observation. \nAbout the speaker: Marcos Calegari Andrade is an Assistant Professor in the Department of Chemistry and Biochemistry at the University of California\, Santa Cruz. He earned his PhD from Princeton University\, where he developed machine learning models to simulate the chemistry and vibrational spectroscopy of condensed-phase systems. He later joined the Quantum Simulations Group at Lawrence Livermore National Laboratory\, applying deep neural network models to fundamental challenges in climate and energy security. His current research at UCSC focuses on the application of machine learning to molecular simulations\, with a particular emphasis on chemical reaction mechanisms\, vibrational spectroscopy\, and the development of automated simulation frameworks. \nThis seminar is hosted by Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-machine-learning-in-molecular-simulations/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260427T110000
DTEND;TZID=America/Los_Angeles:20260427T130000
DTSTAMP:20260423T210320Z
CREATED:20260420T225301Z
LAST-MODIFIED:20260423T210320Z
UID:10012119-1777287600-1777294800@events.ucsc.edu
SUMMARY:Quality First Coding Contest
DESCRIPTION:This is a programming contest\, but with a twist! Instead of scoring you based on your speed and solution accuracy\, we score you based on your programming quality and solution accuracy. This means that instead of looking at how fast you can program a solution\, we look at your number of compiles/runs instead.* The contestant that uses the least number of compiles/runs to produce passing code is the winner. Ties are broken by time. \nFood will be provided. QFCC 20260427 – Poster
URL:https://events.ucsc.edu/event/quality-first-coding-contest/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
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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:20260423T180000
DTEND;TZID=America/Los_Angeles:20260423T193000
DTSTAMP:20260402T222539Z
CREATED:20260402T213440Z
LAST-MODIFIED:20260402T222539Z
UID:10012030-1776967200-1776972600@events.ucsc.edu
SUMMARY:Climate Week Tech Connect: Energy Solutions
DESCRIPTION:Join Baskin Engineering to explore the frontier of power engineering\, where the rapid rise of electrification and digital infrastructure is creating an unprecedented demand for next-generation talent and a critical opportunity for sustainability.  \nThis networking event bridges the gap between the classroom and the field\, offering students and faculty a front-row seat to the trends and high-impact career opportunities shaping our energy future. The event is part of Baskin Engineering Climate Week\, focused on raising awareness of climate issues and sustainability research and teaching. \nWhere: BE Courtyard\nWhen: Thursday\, April 23\, 6:00-7:30 p.m. \nWe hope to see you there!
URL:https://events.ucsc.edu/event/climate-week-tech-connect-energy-solutions/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/01/BElogoWHITE.png
GEO:37.000369;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260423T170000
DTEND;TZID=America/Los_Angeles:20260423T181500
DTSTAMP:20260402T212222Z
CREATED:20260402T211703Z
LAST-MODIFIED:20260402T212222Z
UID:10011935-1776963600-1776968100@events.ucsc.edu
SUMMARY:Careers in Climate Tech & Sustainability
DESCRIPTION:Ready to explore career pathways that matter? \nAttend our very special Careers in Climate Tech & Sustainability Panel—celebrating Baskin Engineering Climate Week—for an inside look at careers that will help build a sustainable future. Panelists representing different roles and organizations will share their career journeys and offer practical insights into working in climate tech. There will also be a catered networking reception that follows—don’t miss it! \nGet informed\, inspired\, and discover your path to a career in sustainability! \nThis event is part of Baskin Engineering’s Climate Tech Day featuring a community fair where students\, faculty\, climate and sustainability tech companies\, and community organizations will showcase their works through demonstrations\, poster presentations\, tabling\, and more.  \nWhere: E2-180\nWhen: Thursday\, April 23\, 5:00-6:15 p.m. \nRegister via Handshake. \nIf you have disability-related needs\, please contact the Career Success office at csuccess@ucsc.edu or (831) 459-4420 as soon as possible. \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/careers-in-climate-tech-sustainability/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/04/Javier-drone.png
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:20260423T140000
DTEND;TZID=America/Los_Angeles:20260423T170000
DTSTAMP:20260403T220700Z
CREATED:20260403T215527Z
LAST-MODIFIED:20260403T220700Z
UID:10012043-1776952800-1776963600@events.ucsc.edu
SUMMARY:Climate Tech & Sustainability Showcase
DESCRIPTION:Join us for a Climate Tech & Sustainability Showcase\, where students\, faculty\, climate and sustainability-focused companies\, founders\, and community organizations come together to share their work and ideas. The event is part of Baskin Engineering Climate Week\, focused on raising awareness of climate issues and sustainability research and teaching. \nExplore a range of interactive demos\, poster presentations\, and tabling displays highlighting innovative research\, emerging technologies\, and real-world solutions to climate challenges. Baskin Engineering student organizations will also be on hand to share their climate friendly projects! \nCome network\, promote your organization\, and meet up-and-coming talent alongside other passionate\, like-minded members of the climate and sustainability community. \nWhere: BE Courtyard\nWhen: 2:00-5:00 p.m.
URL:https://events.ucsc.edu/event/climate-tech-sustainability-showcase/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
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GEO:37.000369;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260421T100000
DTEND;TZID=America/Los_Angeles:20260421T113000
DTSTAMP:20260401T234645Z
CREATED:20260401T234645Z
LAST-MODIFIED:20260401T234645Z
UID:10011845-1776765600-1776771000@events.ucsc.edu
SUMMARY:BE Climate & Cookies Student Pop-Up!
DESCRIPTION:Come get excited about Baskin Engineering Climate Week at our student pop-up! 🌎 \nClimate Week is a chance to explore how Baskin Engineering is addressing climate challenges through innovative research\, teaching\, and hands-on projects. \nDiscover the events happening throughout the week and find ways to get involved! \nSwing by for FREE BE swag\, coffee\, cookies\, Climate Week stickers\, and more—first come\, first served! \nWhere: BE Courtyard\nWhen: Tuesday\, April 21\, 10:00-11:30 a.m. \nWe hope to see you there!
URL:https://events.ucsc.edu/event/be-climate-week-pop-up-2026/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Social Gathering
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2026/04/BE-climate-week-pop-up.png
GEO:37.000369;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260420T160000
DTEND;TZID=America/Los_Angeles:20260420T170000
DTSTAMP:20260331T180549Z
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/
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:20260415T173000
DTEND;TZID=America/Los_Angeles:20260415T203000
DTSTAMP:20260402T171331Z
CREATED:20260325T220453Z
LAST-MODIFIED:20260402T171331Z
UID:10011772-1776274200-1776285000@events.ucsc.edu
SUMMARY:Kraw Lecture: At the Forefront of AI: Innovation and Discovery
DESCRIPTION:Artificial intelligence is transforming how we understand and solve the world’s most complex challenges—while at the same time causing new challenges and concerns. We invite you to join us for a special UC Santa Cruz Kraw Lecture showcasing the faculty whose groundbreaking research in artificial intelligence is transforming science\, technology\, and society. From advances in autonomous systems and natural language processing to the development of sustainable and responsible AI\, this conversation will highlight the innovative work taking place across disciplines and the real-world impact it is poised to have. \nModerated by special guest Ahmad Thomas\, CEO of the Silicon Valley Leadership Group (SVLG)\, this dynamic discussion will bring together leading researchers to explore how these technologies are shaping the future—accelerating discovery\, addressing complex global challenges\, and opening new frontiers for collaboration. Gain insight into the ideas\, discoveries\, and collaborations shaping the next generation of artificial intelligence research and hear from the leaders advancing this work.\n \n\n\nIn-Person Reception: 5:30 p.m.\nLecture: 6:15 p.m.\n\nRegister Now
URL:https://events.ucsc.edu/event/kraw-lecture-at-the-forefront-of-ai-innovation-and-discovery/
LOCATION:The Quad Conference Center\, 2400 Sand Hill Rd\, Menlo Park\, CA\, 94025\, United States
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/03/2526-014E_Kraw_Lecture_banner-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260413T160000
DTEND;TZID=America/Los_Angeles:20260413T170000
DTSTAMP:20260406T170431Z
CREATED:20260406T170431Z
LAST-MODIFIED:20260406T170431Z
UID:10012045-1776096000-1776099600@events.ucsc.edu
SUMMARY:AM Seminar: Genetically Admixed Groups as a Laboratory for Mathematical Modeling and Discovery
DESCRIPTION:Presenter: Dr. Aw\, Department of Genetics\, University of Pennsylvania \nDescription: Admixed groups consist of individuals descended from two or more historically separated ancestral populations\, and they are underrepresented in biomedical studies. Admixed individuals are unique in that they carry mosaics of ancestral segments within their genome\, so their genetic information is typically summarized as a pair of genotype and local ancestry data matrices. I will present two research projects on admixed groups: one applying statistical models to study genetic architecture and polygenic risk\, and another using biomedical data analysis to motivate combinatorial and probabilistic questions. In the “math to genetics” direction\, we describe structural causal models that show local and global genetic ancestry are instruments for epistasis. These models of genetic architecture imply that certain polygenic scores can differentiate between cis and trans epistases\, and highly similar cross-ancestry genetic effects do not rule out pervasive gene-gene or gene-environment interactions. In the “genetics to math” direction\, we study the enumeration of genotype and local ancestry data matrices — which we call admixed arrays — subject to constraints that arise naturally in biomedical applications. Using saddle-point approximation and complex martingale techniques\, we show that admixed arrays admit a different independence heuristic than the closely related binary contingency tables (e^(–1/4) vs e^(–1/2) correction factor). If time permits\, we will discuss ongoing work on designing algorithms for performing exact and approximate enumeration. \nAbout the speaker: Alan Aw is a mathematical scientist specializing in human statistical and population genomics. He is currently a postdoctoral researcher with the Department of Genetics at the University of Pennsylvania\, having obtained a PhD in Statistics at UC Berkeley and studied Applied Mathematics as an undergraduate. His research centers on the genetics and mathematical modeling of underrepresented groups. This includes statistical modeling and analyses of Biobank-scale admixed cohorts to better understand the genetic architecture of biomedical traits and improve genetic risk prediction\, developing non-parametric hypothesis testing methods for genomics\, and interdisciplinary approaches to studying European demographic history inclusive of indigenous Siberians. He is a member of the PRIMED Consortium and a trainee under a National Institutes of Health T32 Grant in Genomic Medicine. \nHosted By: Applied Mathematics  \n 
URL:https://events.ucsc.edu/event/am-seminar-genetically-admixed-groups/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/04/2023_spring_headshot.jpeg
GEO:37.000369;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260406T160000
DTEND;TZID=America/Los_Angeles:20260406T170000
DTSTAMP:20260325T181208Z
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260330T160000
DTEND;TZID=America/Los_Angeles:20260330T170000
DTSTAMP:20260325T182049Z
CREATED:20260325T182049Z
LAST-MODIFIED:20260325T182049Z
UID:10011767-1774886400-1774890000@events.ucsc.edu
SUMMARY:AM Seminar:  Flexible Filaments and Swimming Cups: Just Go with the Flow
DESCRIPTION:Presenter: Lisa Fauci\, Professor\, Tulane University \nDescription: The motion of waving or rotating filaments in a fluid environment is a common element in many biological and engineered systems. Examples at the microscale include chains of diatoms moving in the ocean\, flagella of individual cells comprising multicellular colonies\, as well as engineered nanorobots designed to deliver drugs to tumors. In this talk we will present mathematical and computational insights into these flows at the microscale. Our modeling approaches will vary from detailed models that capture flagellar material properties and wave geometry to minimal force-dipole models that represent a flagellum by a single point. We will investigate a few intriguing systems\, including the journey of extremely long insect sperm flagella through tortuous female reproductive tracts\, and the hydrodynamic performance of shape-shifting Choanoeca flexa colonies. \nBio: Lisa Fauci received her PhD from the Courant Institute of Mathematical Sciences at New York University\, and directly after that joined the Department of Mathematics at Tulane University in New Orleans\, Louisiana\, USA. Her research focuses on biological fluid dynamics\, with an emphasis on using modeling and simulation to study the basic biophysics of organismal locomotion and reproductive mechanics. Lisa served as president of the Society for Industrial and Applied Mathematics (SIAM) in 2019-2020. She is a fellow of SIAM\, the American Mathematical Society\, the Association for Women in Mathematics\, and the American Physical Society. In 2023\, she was elected to the US National Academy of Sciences. \nHosted by: Applied Mathematics Department
URL:https://events.ucsc.edu/event/am-seminar-flexible-filaments-and-swimming-cups-just-go-with-the-flow/
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:20260309T160000
DTEND;TZID=America/Los_Angeles:20260309T170000
DTSTAMP:20260217T230434Z
CREATED:20260217T230434Z
LAST-MODIFIED:20260217T230434Z
UID:10009244-1773072000-1773075600@events.ucsc.edu
SUMMARY:AM Seminar: Solution Discovery in Fluids with High Precision Using Neural Networks
DESCRIPTION:Presenter: Ching-Yao Lai\, Assistant Professor\, Stanford University \nDescription: I will discuss examples utilizing neural networks (NNs) to find solutions to partial differential equations (PDEs) that facilitate new discoveries. Despite being deemed universal function approximators\, neural networks\, in practice\, struggle to fit functions with sufficient accuracy for rigorous analysis. Here\, we developed multi-stage neural networks (Wang and Lai\, J. Comput. Phys. 2024) that can reduce the prediction error to nearly the machine precision of double-precision floating points within a finite number of iterations. We use accurate NNs to tackle the challenge of searching for singularities in fluid equations (Wang-Lai-Gómez-Serrano-Buckmaster\, Phys. Rev. Lett. 2023). Unstable singularities\, especially in dimensions greater than one\, are exceptionally elusive. With NNs we demonstrate the first discovery of smooth unstable self-similar singularities to unforced incompressible fluid equations (Wang et al.\, arXiv:2509.14185). The example illustrates how deep learning can be used to discover new and highly accurate numerical solutions to PDEs. \nBio: Ching-Yao Lai (Yao) is an Assistant Professor in the Department of Geophysics and an Affiliated Faculty of the Institute for Computational and Mathematical Engineering (ICME) at Stanford. Before joining Stanford\, she was an Assistant Professor at Princeton University. She received an undergraduate degree (2013) in Physics from National Taiwan University and a PhD (2018) in Mechanical and Aerospace Engineering from Princeton University. She completed her postdoctoral research at Columbia University where she received the Lamont Postdoctoral Fellowship. Her current research focuses on enhancing the representation of machine-learning models to tackle multiscale problems. She was the recipient of the 2023 Google Research Scholar Award\, the 2024 Sloan Research Fellowship\, and the 2025 NSF CAREER Award. \nHosted by: Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-solution-discovery-in-fluids-with-high-precision-using-neural-networks/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/ph.d.-presentation-graphic-option2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260302T160000
DTEND;TZID=America/Los_Angeles:20260302T170000
DTSTAMP:20260225T181221Z
CREATED:20260225T181221Z
LAST-MODIFIED:20260225T181221Z
UID:10009355-1772467200-1772470800@events.ucsc.edu
SUMMARY:AM Seminar: The Evolving Landscape of AI for Science and Engineering: Bridging Simulation\, Experiment\, and Multi-scale Dynamics
DESCRIPTION:Presenter: Aditi Krishnapriyan\, Assistant Professor\, UC Berkeley \nDescription: Recent advances in large-scale scientific datasets are creating new opportunities for machine learning (ML) methods to more effectively capture scientific phenomena with greater accuracy and reach. In this talk\, I will discuss how these advances are both shifting ML design paradigms and enabling new scientific inquiries. This includes investigations into understanding if neural networks can autonomously discover fundamental physical relationships from data\, and demonstrating how more flexible machine learning modeling design choices enable capturing physical dynamics across multiple scales. I will also explore how generative modeling approaches rooted in statistical physics can be applied to accelerate the sampling of dynamic pathways\, and as a framework to align and bridge the gap between simulated data and experimental observations. \nBio: Aditi Krishnapriyan is an Assistant Professor at UC Berkeley where she is part of Chemical and Biomolecular Engineering\, Electrical Engineering and Computer Sciences\, and Berkeley AI Research; as well as a faculty scientist in the Applied Mathematics division at Lawrence Berkeley National Laboratory. She holds a PhD from Stanford University\, supported by the DOE Computational Science Graduate Fellowship\, was the Luis W. Alvarez Fellow in Computing Sciences at Lawrence Berkeley National Laboratory\, and is a recipient of the Department of Energy Early Career Award and RCSA Scialog. Her research focuses on developing physics-inspired machine learning methods that bridge machine learning with physical science applications to capture phenomena across multiple length and timescales. \nHosted by: Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-the-evolving-landscape-of-ai-for-science-and-engineering-bridging-simulation-experiment-and-multi-scale-dynamics/
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:20260226T120000
DTEND;TZID=America/Los_Angeles:20260226T140000
DTSTAMP:20260223T200828Z
CREATED:20260129T143555Z
LAST-MODIFIED:20260223T200828Z
UID:10009134-1772107200-1772114400@events.ucsc.edu
SUMMARY:BE Club Bash - Engineers Week
DESCRIPTION:Discover innovation at the Baskin Engineering Club Bash\, an event celebrating National Engineers Week! \nMark your calendars for Thursday\, February 26\, 12–2 PM in the BE Courtyard! The BE Club Bash brings together student organizations across all engineering disciplines to showcase their projects\, demos\, and interactive activities. \nStop by to: \n\nExplore hands-on booths and demonstrations from student organizations\nLearn about engineering opportunities on campus and how to get involved\nChat with student leaders and hear about their experiences\nEnter our 3D printer raffle (must be present to win!)\nGrab snacks and BE swag while you explore\n\nThis is a great way to connect with the engineering community\, discover new ideas\, and have fun. We hope to see you there! RSVP here.
URL:https://events.ucsc.edu/event/be-club-bash-engineers-week/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Social Gathering,Undergraduate
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GEO:37.000369;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Jack Baskin Engineering Baskin Engineering 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Baskin Engineering 1156 High Street:geo:-122.0632371,37.000369
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260225T173000
DTEND;TZID=America/Los_Angeles:20260225T190000
DTSTAMP:20260209T232119Z
CREATED:20260130T054047Z
LAST-MODIFIED:20260209T232119Z
UID:10009139-1772040600-1772046000@events.ucsc.edu
SUMMARY:Exploring Research Pathways at Baskin Engineering
DESCRIPTION:Curious how being part of a research lab can supercharge your experience as a Baskin Engineer?   \nJoin us for this informative event to learn about opportunities to solve open-ended problems\, build deeper technical skills\, and learn how to think like an engineer. \nWe’ll kick things off with a quick overview of the kinds of research opportunities available to undergrads and how to get started\, then you’ll hear directly from students who’ve worked in research labs as undergraduates. They’ll share what they actually did day-to-day\, the skills they built (technical and professional)\, and how research shaped their confidence\, career goals\, and next steps. We’ll then have pizza and networking to end the evening. \nWhether you’re aiming for industry\, graduate school\, or just want hands-on experience that goes beyond coursework\, this panel will help you understand how undergraduate research can set you apart—academically\, professionally\, and personally! \n\nRegister via Handshake. \nYOU BELONG HERE\nPrograms and services are open to all\, consistent with state and federal law\, as well as the University of California’s nondiscrimination policies. Every initiative—whether a student service\, faculty program\, or community event—is designed to be accessible\, inclusive\, and respectful of all identities. To learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications.
URL:https://events.ucsc.edu/event/exploring-research-pathways-at-baskin-engineering/
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:20260224T103000
DTEND;TZID=America/Los_Angeles:20260224T113000
DTSTAMP:20260209T232106Z
CREATED:20260129T145348Z
LAST-MODIFIED:20260209T232106Z
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SUMMARY:Transform Your Future Pop-Up (Cookies Included!)
DESCRIPTION:Join Baskin Engineering to celebrate National Engineers Week with a sweet stop at the Transform Your Future Pop-Up (Cookies Included!) 🍪☕ \nThis year’s Engineers Week theme\, Transform Your Future\, is a powerful reminder that engineering doesn’t just shape our world—it shapes our opportunities\, our communities\, and the futures we can imagine for ourselves. \nSwing by the BE Courtyard to grab cookies\, coffee\, and BE swag (first come\, first served!) and take a moment to celebrate how you are transforming your future. \n📅 Date: Tuesday\, February 24⏰ Time: 10:30 a.m.📍 Location: BE Courtyard \nWe hope to see you there!
URL:https://events.ucsc.edu/event/transform-your-future-pop-up-cookies-included/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Social Gathering,Undergraduate
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260223T160000
DTEND;TZID=America/Los_Angeles:20260223T170000
DTSTAMP:20260219T193254Z
CREATED:20260114T175234Z
LAST-MODIFIED:20260219T193254Z
UID:10008383-1771862400-1771866000@events.ucsc.edu
SUMMARY:AM Seminar: Multiscale Modeling of Cellular Membranes and Oncogenic Proteins
DESCRIPTION:Presenter: Liam Stanton\, Professor\, San Jose State University \nDescription: In this talk\, I will present a multiscale model for cellular membranes\, which is trained on molecular dynamics simulations. The model is constructed within the formalism of dynamic density functional theory and can be extended to include features such as the presence of proteins and membrane deformations. This new framework has enabled simulations that can access length-scales on the order of microns and time-scales on the order of seconds\, all while maintaining near fidelity to the underlying molecular interactions. Such scales are significant for accessing biological processes associated with signaling pathways within cells and experimentally relevant regimes. As applications\, we consider the cellular interactions of two membrane proteins of biological interest: G protein-coupled receptors (GPCRs) and RAS-RAF complexes\, the latter being implicated in roughly 30% of human cancers. \nBio: Dr. Stanton received his PhD in Applied Mathematics from Northwestern University in 2009. He went on to do a postdoc at Lawrence Livermore National Laboratory (LLNL)\, where he later became a staff scientist at the Center for Applied Scientific Computing. In 2018\, he joined the faculty at San Jose State University in the Department of Mathematics and Statistics\, where he is now an associate professor and a recent recipient of the Dean’s Scholar Award in Research Excellence. Dr. Stanton’s current research interests are in the multiscale modeling of non-equilibrium\, many-body systems. In particular\, he focuses on areas such as fusion energy\, biophysical systems and statistical mechanics. \nHosted by: Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-multiscale-modeling-of-cellular-membranes-and-oncogenic-proteins/
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260212T163000
DTEND;TZID=America/Los_Angeles:20260212T173000
DTSTAMP:20260203T173017Z
CREATED:20260203T172912Z
LAST-MODIFIED:20260203T173017Z
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SUMMARY:Sambamurthy\, A. (AM) - Lazy Diffusion: Resolving Spectral Collapse in Generative Models for Turbulence
DESCRIPTION:Diffusion-based generative models offer a principled framework for probabilistic forecasting\, but we show they suffer from a fundamental spectral collapse when applied to turbulent flows. A Fourier-space analysis of the forward SDE reveals that the mode-wise signal-to-noise ratio decays monotonically in wavenumber for power-law spectra\, rendering high-wavenumber content indistinguishable from noise. We reinterpret the noise schedule as a spectral regularizer and introduce power-law schedules that preserve fine-scale structure deeper into diffusion time. We further propose Lazy Diffusion\, a one-step distillation method that leverages the learned score geometry to bypass long reverse trajectories and prevent high-wavenumber degradation. Applied to high-Reynolds-number 2D Kolmogorov turbulence and ocean reanalysis data\, these methods resolve spectral collapse and enable stable long-horizon autoregressive emulation. \nEvent Host: Anish Sambamurthy\, Ph.D. Student\, Applied Mathematics  \nAdvisor: Ashesh Chattopadhyay \nZoom- https://ucsc.zoom.us/j/5144530307?pwd=TllaWnNDc01tcVNpa1NNeVVIMnp5QT09 \nPasscode- 55555
URL:https://events.ucsc.edu/event/sambamurthy-a-am-lazy-diffusion-resolving-spectral-collapse-in-generative-models-for-turbulence/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260209T160000
DTEND;TZID=America/Los_Angeles:20260209T170000
DTSTAMP:20260114T182750Z
CREATED:20260114T182449Z
LAST-MODIFIED:20260114T182750Z
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SUMMARY:AM Seminar: Data Driven Modeling for Scientific Discovery and Digital Twins
DESCRIPTION:Presenter: Dongbin Xiu\, Professor\, Ohio State University \nDescription:We present a data-driven modeling framework for scientific discovery\, termed Flow Map Learning (FML). This framework enables the construction of accurate predictive models for complex systems that are not amenable to traditional modeling approaches. By leveraging data and the expressiveness of deep neural networks (DNNs)\, FML facilitates long-term system modeling and prediction even when governing equations are unavailable. FML is particularly powerful in the context of Digital Twins\, an emerging concept in digital transformation. With sufficient offline learning\, FML enables the construction of simulation models for key quantities of interest (QoIs) in complex Digital Twins\, when direct mathematical modeling of the QoIs is infeasible. During the online execution of a Digital Twin\, the learned FML model can simulate the QoIs without reverting to the computationally intensive Digital Twin simulation model. As a result\, FML serves as an enabling methodology for real-time control and optimization for complex systems. \nBio: Dongbin Xiu received his Ph.D degree from the Division of Applied Mathematics of Brown University in 2004. He joined the Department of Mathematics of Purdue University in 2005 and moved to the University of Utah in 2013. In 2016\, He joined The Ohio State University as Professor of Mathematics and Ohio Eminent Scholar. He received NSF CAREER award in 2007 and was elected to SIAM Fellow in 2023. He is currently the Editor-in-Chief of the Journal of Computational Physics and the founding Editor-in-Chief of Journal of Machine Learning for Modeling and Computing (JMLMC). His current research focuses on developing efficient numerical methods for scientific machine learning\, data driven discovery and digital twins. \nHosted by: Daniele Venturi\, Applied Mathematics
URL:https://events.ucsc.edu/event/am-seminar-data-driven-modeling-for-scientific-discovery-and-digital-twins/
CATEGORIES:Lectures & Presentations,Seminars
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260206T110000
DTEND;TZID=America/Los_Angeles:20260206T120000
DTSTAMP:20260127T193801Z
CREATED:20260127T193801Z
LAST-MODIFIED:20260127T193801Z
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SUMMARY:Johnstone\, J. (AM) - The Effects of Asymmetry on Overshooting and Magnetic Pumping from Compressible Convection Zones
DESCRIPTION:We present a comprehensive numerical investigation examining how vertical asymmetry in compressible convection affects overshooting and the transport of large-scale magnetic fields from convective to stably stratified regions. Using three-dimensional direct numerical simulations\, we systematically vary the superadiabaticity and stratification of a convective layer to control the vertical asymmetry of the flow and analyze its influence on overshooting depth and magnetic pumping efficiency. We extend previous work by Tobias et al. (2001) and draw guidance from the asymmetry regimes identified by John & Schumacher (2023)\, investigating whether similar asymmetric convecting regimes emerge in our overshooting model that incorporates a stably stratified region below. We find that vertical asymmetry increases significantly with stratification at a moderate\, fixed Rayleigh number\, while superadiabaticity contributes primarily through enhanced downflow velocities\, with both combined leading to increasing overshooting depths reaching approximately 0.46 − 0.7 pressure scale heights. Magnetic pumping efficiency initially increases with stratification but unexpectedly decreases at higher stratification\, despite increasing overshooting depths. We find that this behavior arises from the increasing thermal and magnetic diffusivities that result from increasing stratification at fixed Ra. When instead either holding these diffusivities constant or increasing Ra sufficiently\, we find that then both overshooting and magnetic pumping depths both decrease with increasing stratification. This behavior is explained by a change of dynamical state from one of laminar downflows to one of turbulent downflowing plumes leading to a high degree of turbulent mixing and entrainment. We thus find two distinct regimes that might be described as a microscopically diffusive regime and a turbulently diffusive one. These results suggest that\, in the highly turbulent regime expected in the Sun\, magnetic pumping efficiency may decrease with increasing stratification due to enhanced turbulent entrainment\, with important implications for solar dynamo theory and the transport of large-scale magnetic fields in the solar interior. \n  \nEvent Host: Jason Johnstone\, Ph.D. Student\, Applied Mathematics \nAdvisor: Nic Brummell \nZoom- https://ucsc.zoom.us/j/5428987373?pwd=JSmNz3ZZby5ZnVBYbSoakjjQb2qQj6.1&omn=98571815542 \nPasscode- 778899
URL:https://events.ucsc.edu/event/johnstone-j-am-the-effects-of-asymmetry-on-overshooting-and-magnetic-pumping-from-compressible-convection-zones/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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