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DTSTART;TZID=America/Los_Angeles:20260226T120000
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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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DTSTART;TZID=America/Los_Angeles:20260225T173000
DTEND;TZID=America/Los_Angeles:20260225T190000
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CREATED:20260130T054047Z
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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:20260612T173904
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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:20260612T173904
CREATED:20260114T175234Z
LAST-MODIFIED:20260219T193254Z
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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:20260612T173904
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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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260209T160000
DTEND;TZID=America/Los_Angeles:20260209T170000
DTSTAMP:20260612T173904
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:20260612T173904
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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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260202T160000
DTEND;TZID=America/Los_Angeles:20260202T170000
DTSTAMP:20260612T173904
CREATED:20260128T184233Z
LAST-MODIFIED:20260128T184233Z
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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/
CATEGORIES:Lectures & Presentations,Seminars
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260126T160000
DTEND;TZID=America/Los_Angeles:20260126T170000
DTSTAMP:20260612T173904
CREATED:20260120T184336Z
LAST-MODIFIED:20260120T184604Z
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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/
CATEGORIES:Lectures & Presentations,Seminars
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LOCATION: https://ucsc.zoom.us/j/97450297092?pwd=Bp4GIgR8dAuBeCd1Sz9vXo8unkYWQW.1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260121T173000
DTEND;TZID=America/Los_Angeles:20260121T193000
DTSTAMP:20260612T173904
CREATED:20251125T003155Z
LAST-MODIFIED:20251201T220429Z
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SUMMARY:Kraw Lecture: Sensing the Unseen: How Drones and Ground Sensors Reveal the Hidden Air Quality Impact
DESCRIPTION:How can flying robots help us track the air we breathe and the pollutants we can’t see? In this talk\, Assistant Professor Javier González-Rocha  will share how his team uses drones to measure wind patterns and detect airborne pollutants in hard-to-reach places.. \nThese systems help us understand how toxic pollutants and climate emissions move through the atmosphere and affect human health and the environment. From wildfire smoke to methane leaks from dairy farms and oil fields\, these emissions are often poorly monitored—especially in rural or overburdened communities. \nLow-cost\, adaptable drone and ground sensor systems fill this gap. By combining real-time flight data\, environmental measurements\, and advanced modeling\, González-Rocha and his team generate targeted observations that inform air quality assessments and improve emissions tracking. \nThis work sits at the intersection of engineering\, environmental science\, and community collaboration—building tools that empower people and support climate resilience from the ground up. \nIn-Person Reception: 5:30 p.m.\nLecture: 6–7 p.m.\n\nRegister Now
URL:https://events.ucsc.edu/event/kraw-lecture-sensing-the-unseen-how-drones-and-ground-sensors-reveal-the-hidden-air-quality-impact/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Lectures & Presentations
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260112T170000
DTEND;TZID=America/Los_Angeles:20260112T183000
DTSTAMP:20260612T173904
CREATED:20251209T200526Z
LAST-MODIFIED:20251218T001742Z
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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/
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:20260112T160000
DTEND;TZID=America/Los_Angeles:20260112T170000
DTSTAMP:20260612T173904
CREATED:20260112T164010Z
LAST-MODIFIED:20260112T164010Z
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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/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/01/ph.d.-presentation-graphic-option-1.jpg
LOCATION: https://ucsc.zoom.us/j/96136632376?pwd=yb27lop8mnhnsairAPgezmVJZzFb74.1.
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260105T160000
DTEND;TZID=America/Los_Angeles:20260105T170000
DTSTAMP:20260612T173904
CREATED:20251217T182411Z
LAST-MODIFIED:20251218T002005Z
UID:10005858-1767628800-1767632400@events.ucsc.edu
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/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/12/txvu.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251205T100000
DTEND;TZID=America/Los_Angeles:20251205T123000
DTSTAMP:20260612T173904
CREATED:20251125T212206Z
LAST-MODIFIED:20251125T212206Z
UID:10005646-1764928800-1764937800@events.ucsc.edu
SUMMARY:DeGrendele\, C. (AM) - Learning-Augmented and Structure-Preserving Methods for Conservation Law Solvers
DESCRIPTION:In this work\, we develop numerical methods for conservation laws that explore statistical\, structure-preserving\, and machine-learning-based approaches\, each built on top of traditional numerical solvers. First\, we develop a general Gaussian-process-based “recipe’’ for constructing high-order linear operators such as interpolation\, reconstruction\, and derivative approximations. Building on this recipe\, we derive a kernel-agnostic convergence theory for GP-based operators that interprets them as generalized finite-difference schemes\, defines an effective order-of-accuracy proxy that captures non-ideal truncation-error structure\, and uses this metric to select stencil geometries and kernel hyperparameters analytically. We then introduce a new second-order kernel\, Discontinuous Arcsin (DAS)\, that is stationary and prevents oscillations. DAS is integrated into a shock-capturing framework called the Multidimensional Optimal Order Detection (MOOD) method and shows an increase in efficiency by admitting less first order cascades. Next\, we address the long-standing problem of spurious pressure oscillations in compressible multi-component and real-fluid simulations by introducing a fully conservative pressure-equilibrium-preserving scheme and a high-order fully conservative approximate variant that apply to arbitrary equations of state. Unlike existing approaches\, these methods avoid non-conservative updates or EOS-specific constructions\, and on smooth interface advection tests with ideal-gas\, stiffened-gas\, and van der Waals fluids they reduce spurious pressure oscillations by orders of magnitude relative to current schemes. We then propose a hybrid numerical–machine learning framework for mixed hyperbolic–parabolic systems in which only the diffusive contribution is learned while the hyperbolic fluxes are advanced with standard shock-capturing methods\, enabling timesteps at a hyperbolic CFL. Within this framework\, we compare several neural architectures and loss designs on viscous Burgers tests and on the one-dimensional Euler equations with heat conduction\, showing that U-shaped neural operators combined with multi-step and TVD-style regularization improve long-time stability and spectral behavior\, and we analyze the resulting coupled schemes via eigenvalue-based stability diagnostics. Finally\, we apply high-order\, shock-capturing finite-difference methods within NASA’s Launch Ascent and Vehicle Aerodynamics (LAVA) framework to quantify acoustic and pressure loads on the Artemis Mobile Launcher\, including multiphase simulations of water-suppression systems and comparisons to flight data that inform hardware design for future missions. Collectively\, this work offers a set of targeted advances in kernel-based numerical operators\, conservative schemes and learning-augmented solvers each aimed at improving accuracy\, stability\, or efficiency in complex multiphysics flow simulation. \nEvent Host: Chris DeGrendele\, Ph.D. Candidate\, Applied Mathematics \nAdvisor: Dongwook Lee  \nZoom- https://ucsc.zoom.us/j/96308438100?pwd=9El4idgPoaVnAd9m8M6As6uaSbcojp.1 \nPasscode-  123456
URL:https://events.ucsc.edu/event/degrendele-c-am-learning-augmented-and-structure-preserving-methods-for-conservation-law-solvers/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/11/ph.d.-presentation-graphic-option-1-1.jpg
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:20251201T160000
DTEND;TZID=America/Los_Angeles:20251201T170000
DTSTAMP:20260612T173904
CREATED:20251119T172305Z
LAST-MODIFIED:20251119T172305Z
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SUMMARY:AM Seminar: Denoising: A Powerful Building Block for Imaging\, Inverse Problems and Machine Learning
DESCRIPTION:Presenter: Peyman Milanfar\, Distinguished Scientist\, Google \nDescription: Denoising\, the process of reducing random fluctuations in a signal to emphasize essential patterns\, has been a fundamental problem of interest since the dawn of modern scientific inquiry. Recent denoising techniques\, particularly in imaging\, have achieved remarkable success\, nearing theoretical limits by some measures. Yet\, despite tens of thousands of research papers\, the wide-ranging applications of denoising beyond noise removal have not been fully recognized. This is partly due to the vast and diverse literature\, making a clear overview challenging. This article aims to address this gap. We present a clarifying perspective on denoisers\, their structure and their desired properties. We emphasize the increasing importance of denoising and showcase its evolution into an essential building block for complex tasks in imaging\, inverse problems and machine learning. Despite its long history\, the community continues to uncover unexpected and groundbreaking uses for denoising\, further solidifying its place as a cornerstone of scientific and engineering practice. \nBio: Peyman is a Distinguished Scientist at Google\, where he leads the Computational Imaging team. Prior to this\, he was a Professor of Electrical Engineering at UC Santa Cruz for 15 years\, two of those as Associate Dean for Research. From 2012-2014 he was on leave at Google-x\, where he helped develop the imaging pipeline for Google Glass. Over the last decade\, Peyman’s team at Google has developed several core imaging technologies that are used in many products. Among these are the zoom pipeline for the Pixel phones\, which includes the multi-frame super-resolution (Super Res Zoom) pipeline\, and several generations of state of the art digital upscaling algorithms. Most recently\, his team led the development of Pro Res Zoom\, and Unblur\, features launched in Pixel 10 devices and Google Photos. Peyman received his undergraduate education in electrical engineering and mathematics from the UC Berkeley\, and the MS and PhD degrees in electrical engineering from MIT. He holds more than two dozen patents. He founded MotionDSP\, which was acquired by Cubic Inc. Along with his students and colleagues\, his research work has had deep impact in several areas of computational imaging\, and applications of AI thereto – including the introduction of adaptive kernel regression to imaging; pioneering use of learning for fast\, content-adaptive image upscaling (RAISR); Neural Image quality Assessment (NIMA)\, Regularization by Denoising (RED); and most recently (2024) Inversion by Direct Iteration (InDI). All of these works have been recognized with best paper awards. He’s been a Distinguished Lecturer of the IEEE Signal Processing Society\, and is a Fellow of the IEEE “for contributions to inverse problems and super-resolution in imaging” \nHosted by: Professor Julie Simons\, Applied Mathematics \nZoom link: https://ucsc.zoom.us/j/93681175800?pwd=bgfPLQpTzs5PG4z3Qo2zbvMMScMAwn.1 \nMeeting ID: 936 8117 5800\nPasscode: 609643
URL:https://events.ucsc.edu/event/am-seminar-denoising-a-powerful-building-block-for-imaging-inverse-problems-and-machine-learning/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/11/ph.d.-presentation-graphic-option-1-1.jpg
LOCATION:https://ucsc.zoom.us/j/93681175800?pwd=bgfPLQpTzs5PG4z3Qo2zbvMMScMAwn.1
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251124T160000
DTEND;TZID=America/Los_Angeles:20251124T170000
DTSTAMP:20260612T173904
CREATED:20251105T172921Z
LAST-MODIFIED:20251105T172921Z
UID:10005096-1764000000-1764003600@events.ucsc.edu
SUMMARY:AM Seminar: Linear Stochastic Emulators of the Ocean Circulation based on Balanced Truncation: A Caution\, perhaps\, for Machine Learning?
DESCRIPTION:Presenter: Professor Andy Moore\, UCSC Ocean Sciences \nDescription: Linear inverse models have enjoyed considerable popularity in the geosciences\, particularly in the arena of climate research and climate prediction\, for several decades as a straightforward approach to dimension reduction and streamlining computational efficiency. The most common approach is to truncate the system by retaining the leading Empirical Orthogonal Functions (EOFs) which represent the left singular vectors of the transition matrix. While singular value decomposition is the best low rank approximation of the transition matrix\, ignoring information contained in the right singular vectors\, as is commonly done in linear inverse models\, has consequences for the dynamics that approximate the system. Dimension reduction based on balanced truncation simultaneously preserves information from the right and left singular vectors. This talk will review some of these ideas and present examples from the ocean. Since EOF decomposition is quite commonly used for dimension reduction in some machine learning approaches\, there may be some lessons here for the machine learning community to consider. \nBio: Professor at UCSC since 2016. \nHosted by: Professor Julie Simons
URL:https://events.ucsc.edu/event/am-seminar-linear-stochastic-emulators-of-the-ocean-circulation-based-on-balanced-truncation-a-caution-perhaps-for-machine-learning/
CATEGORIES:Lectures & Presentations,Seminars
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/11/ph.d.-presentation-graphic-option-1.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251117T160000
DTEND;TZID=America/Los_Angeles:20251117T170000
DTSTAMP:20260612T173904
CREATED:20251006T191530Z
LAST-MODIFIED:20251022T182419Z
UID:10003979-1763395200-1763398800@events.ucsc.edu
SUMMARY:AM Seminar: Dynamo Action Inside the Giant Planets
DESCRIPTION:Presenter: Dr. Paula Wulff\, UCLA \nDescription: Our solar system hosts six unique planetary magnetic fields. Intrinsic magnetic fields are generated deep inside planets by dynamo action. This process requires regions of electrically conducting material and energy sources to maintain the dynamo. Thus\, we can learn about the deep interiors of planets\, including their structures and dynamics\, by investigating their magnetic fields. In this talk\, I’ll explore some of the interesting questions and possible answers about planetary interiors that have come from studies of planetary magnetism\, in particular through 3-dimensional magnetohydrodynamic simulations. \nBio: Paula Wulff completed her PhD with Uli Christensen at the Max-Planck-Institute for Solar System Science\, in Goettingen\, Germany\, after her undergrad at Cambridge (UK). While working with Uli\, she studied zonal flows on Gas Giants\, in particular on Jupiter. She used the gravity measurements made by Juno to infer their depth\, and numerical modelling to investigate their truncation mechanism at depth. After her PhD\, she moved to California to work with Hao Cao and Jon Aurnou at UCLA’s EPSS department. During the postdoc she has continued to work on 3-D MHD modelling to study the dynamo mechanisms in the interiors of various planets in our solar system. \nHosted by: Professor Julie Simons
URL:https://events.ucsc.edu/event/am-seminar-dynamo-action-inside-the-giant-planets/
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/10/ph.d.-presentation-graphic-option2.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251110T160000
DTEND;TZID=America/Los_Angeles:20251110T170000
DTSTAMP:20260612T173904
CREATED:20251003T195525Z
LAST-MODIFIED:20251022T182510Z
UID:10003145-1762790400-1762794000@events.ucsc.edu
SUMMARY:AM Seminar: Structure-Preserving Discretizations and their Applications
DESCRIPTION:Presenter: Andy Wan\, Assistant Professor\, University of California\, Merced \n  \nDescription: Many models from science and engineering possess fundamental structures which are important to preserve in order for accurate and stable long-term predictions. For instance\, preserving conserved quantities\, such as energy\, mass and momentum\, are fundamental in many physical systems. Moreover\, preserving dissipative quantities\, such as entropy or Lyapunov functions\, are also essential for predicting correct asymptotic limits. In this talk\, we will survey a recent new class of conservative and dissipation-preserving integrators\, called the Discrete Multiplier Method (DMM). We will discuss various applications to many-body systems\, geodesic flow\, and particle methods in fluids and kinetic models. Moreover\, we will introduce Conservative Hamiltonian Monte Carlo\, which utilizes DMM to improve sampling efficacy of Hamiltonian Monte Carlo for high dimensional target distributions. If time permits\, we will also discuss how structure-preservation in scientific machine learning can improve long-term predictions and be amenable to error analysis on accuracy bounds. \n  \nBio: Andy Wan is an Assistant Professor in the Department of Applied Mathematics at the University of California\, Merced (UC Merced). Prior to joining UC Merced in 2024\, he received his Ph.D. from Polytechnique Montreal\, and was a postdoctoral fellow at McGill University and later an assistant professor at the University of Northern British Columbia. His research interests are in numerical analysis\, scientific computing\, and scientific machine learning. He focuses on structure-preserving discretizations\, specifically in the theory and development of conservative and dissipation-preserving integrators\, as well as their applications to mathematical sciences\, computational statistics and scientific machine learning. He is currently a co-investigator of the 2024-2027 Collaborative Research Group on “Structure-Preserving Discretizations and their Applications”\, supported by the Pacific Institute for the Mathematical Sciences (PIMS). He has also recently co-organized a summer school and hackathon event on “Structure-Preserving Scientific Computing and Machine Learning”\, supported by NSF and PIMS. \n  \nHosted by: Professor Julie Simons \n 
URL:https://events.ucsc.edu/event/am-seminar-structure-preserving-discretizations-and-their-applications/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations
GEO:37.000369;-122.0632371
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251107T000000
DTEND;TZID=America/Los_Angeles:20251108T235959
DTSTAMP:20260612T173904
CREATED:20251013T212720Z
LAST-MODIFIED:20251023T232623Z
UID:10004811-1762473600-1762646399@events.ucsc.edu
SUMMARY:United Nations Reboot the Earth Hackathon
DESCRIPTION:The United Nations (UN) and the Baskin School of Engineering at the University of California\, Santa Cruz\, are collaborating to bring the “Reboot the Earth” hackathon to the West Coast for the first time. \nThis is a social event bringing together aspiring developers to create open source software solutions that address the climate crisis\, including wildfire response. It’s a chance to collaborate with peers\, use open data\, and apply your coding skills to real-world climate challenges! \n\n\n\nDate: November 7-8\, 2025\nLocation: UC Santa Cruz Silicon Valley Center.\nRegister here for the event. \n\nOrganized by the UN Office of Information and Communications Technology (OICT)\, the 2025  Reboot the Earth hackathons are focused on agriculture and artificial intelligence (AI). The California event will focus on the locally relevant challenges of wildfire detection\, response\, and impact. Participants can leverage open source\, AI\, and open data sets\, along with local expertise on the environment and emergency preparedness and response. The goal is to build solutions that can become a digital public good\, serving local community needs. \nUC Santa Cruz students interested in attending the event can take advantage of the Silicon Valley Connector shuttle\, which will be running on Saturday\, November 8\, in addition to the regular Friday schedule. \nTo learn more about the Reboot the Earth initiative\, visit: https://unite.un.org/en/reboot-earth.
URL:https://events.ucsc.edu/event/un-reboot-the-earth-hackathon/
LOCATION:Silicon Valley Campus\, 3175 Bowers Avenue\, Santa Clara\, CA\, 95054\, United States
CATEGORIES:Meetings & Conferences,Social Gathering
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/10/Reboot-the-earth-1.png
GEO:37.3796975;-121.9765484
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Silicon Valley Campus 3175 Bowers Avenue Santa Clara CA 95054 United States;X-APPLE-RADIUS=500;X-TITLE=3175 Bowers Avenue:geo:-121.9765484,37.3796975
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251103T160000
DTEND;TZID=America/Los_Angeles:20251103T170000
DTSTAMP:20260612T173904
CREATED:20251020T180018Z
LAST-MODIFIED:20251023T222025Z
UID:10004950-1762185600-1762189200@events.ucsc.edu
SUMMARY:AM Seminar: In Search of Stratified Turbulence
DESCRIPTION:Presenter: Colm-cille Patrick Caulfield\, Professor\, DAMTP\, University of Cambridge \nDescription: Statically stable density stratification is ubiquitous in geophysical flows\, with the atmosphere\, lakes and oceans all typically having an average density distribution that decreases upwards in a gravitational field. Due to the associated stabilising effect of the buoyancy force\, it would seem intuitive that such statically stable density distributions should suppress vertical motions\, relative to horizontal motions. Such inevitable anisotropy complicates even further developing an understanding of turbulence in density-stratified fluids. Stratified turbulence is not just a fascinating (and inherently complicated) research challenge in classical physics\, but also a key component of the global climate system\, as stratified turbulence has a leading order effect on the transport of heat and other scalars such as carbon dioxide\, pollutants etc in the world’s oceans and atmosphere. Indeed\, how stratified turbulence can actually be `born’ and then `survive’ for a significant period\, hence irreversibly mixing significant scalar quantities\, are open questions\, associated with ongoing controversy in the global research community. In this talk\, I will review some recent studies by my collaborators that have advanced our understanding of various key properties of stratified turbulence and mixing\, while also demonstrating that there is still much more to learn about this fascinating and vitally important class of fluid flows. \n\n\n\n\n\nBio: Colm-cille P. Caulfield is Professor of Environmental and Industrial Fluid Dynamics in the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge\, and a faculty member of the Institute for Energy and Environmental Flows (IEEF). He is also a Professorial Fellow in Mathematics at Churchill College\, Cambridge\, and the Co-Director (Science) of the University’s Institute of Computing for Climate Science (ICCS)\, which studies and supports the role of software engineering\, computer science\, AI and data science within climate science. Prof. Caulfield’s personal research interests include instability\, turbulence transition and turbulent mixing processes in stratified flows\, with particular focus on understanding and improving the modelling of heat transport in the world’s oceans. His undergraduate studies were at the University of Ulster at Coleraine\, graduating with a BSc in Mathematics in 1987. He then studied for his Masters and PhD in Fluid Mechanics at DAMTP under the supervision of Prof Paul Linden FRS\, defending his thesis on stratified shear instabilities in 1991. Following postdoctoral training in the Department of Physics at the University of Toronto and the Department of Engineering Science at Hokkaido University\, he was a lecturer in the School of Mathematics at the University of Bristol from January 1995 to June 1999. Prof. Caulfield subsequently joined the faculty of the Department of Mechanical and Aerospace Engineering at the University of California\, San Diego for the period July 1999 to June 2005. Following tenure at UCSD\, Prof. Caulfield joined the BP Institute (now IEEF) and DAMTP in July 2005. Prof. Caulfield is the Editor-in-Chief of the Journal of Fluid Mechanics\, the Chair of the European Mechanics Society (Euromech) Turbulence Conference Committee\, and served as the Head (ie Dept Chair) of DAMTP January 2020-September 2025. He was elected a Fellow of the American Physical Society (Division of Fluid Dynamics) in 2014.\n\n\n\n\n\nHosted by: Professor Julie Simons
URL:https://events.ucsc.edu/event/am-seminar-in-search-of-stratified-turbulence/
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/10/Colm-cille.png
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251027T160000
DTEND;TZID=America/Los_Angeles:20251027T170000
DTSTAMP:20260612T173904
CREATED:20251006T190306Z
LAST-MODIFIED:20251022T182854Z
UID:10003978-1761580800-1761584400@events.ucsc.edu
SUMMARY:AM Seminar: Why do we care about inertial waves on the Sun?
DESCRIPTION:Presenter: Ms. Catherine Blume\, University of Colorado-Boulder \nDescription: Recent observations of Rossby waves and other inertial oscillations in the Sun’s convection zone have kindled the hope that such waves might be used as a seismic probe of the Sun’s interior. Here\, we present a 3D numerical simulation in spherical geometry that models the Sun’s convection zone and upper radiative interior. This model features a wide variety of inertial oscillations\, including both sectoral and tesseral Rossby waves\, retrograde mixed inertial modes\, prograde thermal Rossby waves\, and the recently observed high-frequency retrograde (HFR) vorticity modes. In this talk\, we’ll explore these different waves\, their physical impact\, and their potential helioseismic utility. \nBio: Catherine Blume is an astrophysics PhD student at the University of Colorado Boulder\, where she works with Brad Hindman studying solar inertial waves. \nHosted by: Professor Julie Simons
URL:https://events.ucsc.edu/event/am-seminar-why-do-we-care-about-inertial-waves-on-the-sun/
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/10/ph.d.-presentation-graphic-option2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251021T120000
DTEND;TZID=America/Los_Angeles:20251021T130000
DTSTAMP:20260612T173904
CREATED:20251013T151834Z
LAST-MODIFIED:20251014T141340Z
UID:10004809-1761048000-1761051600@events.ucsc.edu
SUMMARY:CITRIS Aviation Prize Information Session
DESCRIPTION:Join us for this virtual info session on the 2025–26 CITRIS Aviation Prize\, an exciting multi-campus student competition inviting teams to design innovative solutions for the future of air mobility across the University of California. \nThe session will cover this year’s competition guidelines\, key dates and requirements\, and available resources. Attendees will also have the opportunity for Q&A with members of the CITRIS Aviation Leadership Committee\, composed of aviation research faculty from UC Berkeley\, UC Davis\, UC Merced\, and UC Santa Cruz. \nRegister here to attend. \nFor any questions\, contact aviationprize@citris-uc.org. \n  \nDate: Tuesday\, October 21 \nTime: 12:00 pm – 1:00 pm \nLocation: Zoom (register to attend).
URL:https://events.ucsc.edu/event/citris-aviation-prize-info/
CATEGORIES:Meetings & Conferences
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2025/10/2025-Aviation-Prize-graphic.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251015T110000
DTEND;TZID=America/Los_Angeles:20251015T110000
DTSTAMP:20260612T173904
CREATED:20250924T212046Z
LAST-MODIFIED:20250924T212046Z
UID:10000051-1760526000-1760526000@events.ucsc.edu
SUMMARY:2025 Fall STEM Career & Internship Fair
DESCRIPTION:Here is a chance to meet tech recruiters in person! \nIf you are interested in pursuing a career in science\, technology\, engineering\, mathematics or research\, then take advantage of this opportunity to meet recruiters from companies looking to fill various positions (both technical and non-technical). Learn more about internships and full-time career opportunities. Undergraduate students\, graduate students\, and recent alumni are all welcome to attend! \nPLEASE NOTE: You are encouraged to check in at the student registration table in order to participate in the career fair. Bring your student ID. \nWant more support? \n\nVisit a peer coach during drop-in hours\nSchedule a career coaching appointment with a Career Engagement Specialist\nFor PhD students looking to pursue careers in industry\, explore Beyond the Professoriate\n	(Scroll over "Login to Platform" at the top navigation bar and click "Through your institution")\nGet career tips on demand from our Career Success YouTube video library\nStay in the loop by following Career Success on Instagram\n\nYou will receive registration and additional information in your email from Career Success via Handshake. Please make sure to check your junk/spam folder if you are not receiving any communication.\n  \nYou Belong Here: The programs and services described here 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. \nTo learn more\, please visit UC Nondiscrimination Statement or Nondiscrimination Policy for UC Publications. \nQuestions? Send to csuccess@ucsc.edu or visit Career Success at Hahn 125 East Entrance\nNeed accessibility support? Let us know at slugtalent@ucsc.edu at least two weeks prior to the fair date.
URL:https://events.ucsc.edu/event/2025-fall-stem-career-internship-fair/
LOCATION:Stevenson Event Center\, Stevenson Service Road\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
GEO:36.996897;-122.0512963
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251013T160000
DTEND;TZID=America/Los_Angeles:20251013T170000
DTSTAMP:20260612T173904
CREATED:20251010T173651Z
LAST-MODIFIED:20251010T173651Z
UID:10004556-1760371200-1760374800@events.ucsc.edu
SUMMARY:AM Seminar: Faculty Lightning Talk
DESCRIPTION:Join us for a fast-paced showcase of applied mathematics faculty research in this week’s AM Seminar\, featuring lightning talks that spotlight the department’s wide-ranging interests—from [astro and geo]-fluid dynamics and numerical methods to environmental sensing\, machine learning\, genetics\, and mathematical biology. Discover the innovative projects driving our community and learn about potential hands-on student research project opportunities that bridge theory\, computation\, and real-world impact.\n\n\nSpeakers include: Marcella Gomez\, Ashesh Chattopadhyay\, Pascale Garaud\, Dongwook Lee\, Nilah Ioannidis\, Nic Brummell\, Hongyun Wang\, Julie Simons\, Javier González-Rocha
URL:https://events.ucsc.edu/event/am-seminar-faculty-lightning-talk/
CATEGORIES:Lectures & Presentations
ATTACH;FMTTYPE=image/png:https://events.ucsc.edu/wp-content/uploads/2025/10/option-3.png
END:VEVENT
END:VCALENDAR