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SUMMARY:PyTorch Santa Cruz Meetup
DESCRIPTION:Food\, Socializing\, and Excellent talks from the PyTorch Ecosystem\n\n​5:30 – 6:30 Food and Socializing\n​6:30 – 7:00 Rob Timpe – Using and Debugging Torch.compile\n​7:00 – 7:30 Roy Shadmon – EdgeFL and Federated Learning\n​7:30 – 8:00 Talk 3\n\n​Talk 1: \n​Using and Debugging Torch.compile\n​Torch.compile promises great speedups with a one line change\, but can give cryptic error messages when it fails.  We’ll describe some common failures and how to fix them\, as well as recent efforts to both reduce failures and make the remaining ones easier to debug. \nRob Timpe is a software engineer at OpenTeams where he works on the front end of torch.compile (Dynamo).  Previously he was an ML engineer working on autonomous aircraft at Xwing\, and computer vision at Microsoft. \n​Talk 2: \n​EdgeFL and Federated Learning\n​EdgeLake coordinates federated learning across distributed sites without moving raw training data to a central location. Each site trains locally\, EdgeLake handles the distributed data and coordination layer\, and the resulting models are shared across the network and deployed for inference at the edge — creating a continuous path from managing distributed data to training models to running inference\, all at the edge. \n​Roy Shadmon is a System Architect at AnyLog\, where he works on EdgeLake and its applications in federated learning and distributed edge intelligence. He holds a PhD from UC Santa Cruz. \n​Other speaker(s) announced soon
URL:https://events.ucsc.edu/event/pytorch-santa-cruz-meetup/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
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SUMMARY:2026 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! \nCurious about how to best prepare for the fair? \n1. Research the organization \nIdentify the top 3-5 companies you are interested in\, but remember to be open to different companies you may not have heard of because they may be a startup or business-to-business organization that doesn’t directly serve consumers. \nDo your research by reviewing company websites. Look for their mission\, values\, location\, and the type of available opportunities (e.g.\, internships\, full-time positions\, etc.). Company representatives are impressed by potential candidates who take the time to do this! \n2. Prepare your introduction and questions \nReflect on what it is about each company that resonates with you. Perhaps it’s the specific technology they’re developing\, the research they’re leading\, or the world problem they’re trying to solve. What relevant experiences do you have? How can you be of service to that organization? Exercise critical thinking skills to develop questions to ask recruiters and hiring managers. \n3. Dress with confidence \nEach industry and each company has different work attire expectations and organizational culture. Do your research\, ask mentors in advance for advice\, and dress to impress! \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. \nCareer fair registrations are made without endorsement\, direct or implied\, by Career Success or UCSC. Career Success educates students about various opportunities and ensures equity of access to campus recruiting activities for all employers who abide by our Employer Policies. Individual students are encouraged to determine which employers align with their diverse talents\, values\, and interests.
URL:https://events.ucsc.edu/event/2026-fall-stem-career-internship-fair/
LOCATION:Stevenson Event Center\, Stevenson Service Road\, Santa Cruz\, CA\, 95064
CATEGORIES:Meetings & Conferences
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SUMMARY:AM Seminar: Sliced Optimal Transport: From Acceleration to Bayesian Modeling
DESCRIPTION:Presenter: Enter the speaker’s name\, title\, and institution at the top of the event \nDescription: Optimal transport (OT) provides a principled way to match\, compare\, and interpolate distributions\, but its computational cost limits its use at realistic scales. I will present our recent work on reducing that cost and on using OT for statistical modeling and inference. In the first part of the talk\, I will briefly introduce optimal transport and sliced optimal transport (SOT). I will then present sliced-regularized OT\, which uses a cheap sliced plan as an informative prior for approximating the full plan\, yielding an efficient approximate OT solver. In the second part\, I will show how SOT enables new applications in statistical inference. In particular\, I will introduce distributional determinantal point processes\, which use SOT geometry to place repulsive priors on distributions\, giving a Bayesian model for clustering distributional data. Applications include image processing and the clustering of single-cell and epilepsy data. \nAbout the speaker: Dr. Khai Nguyen is an Assistant Professor in the Department of Statistics and Data Science at Texas A&M University. He received his Ph.D. in Statistics from the University of Texas at Austin and his B.Sc. in Computer Science from Hanoi University of Science and Technology. His research develops computational optimal transport\, particularly sliced methods that make large-scale transport tractable. He brings these tools to problems in machine learning and geometric data processing\, as well as to Bayesian approximate inference and nonparametric models for distributional data. \nThis seminar is hosted by Professor Yunyi Shen.
URL:https://events.ucsc.edu/event/am-seminar-sliced-optimal-transport-from-acceleration-to-bayesian-modeling/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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SUMMARY:AM Seminar: Data Analysis Workflow from Low-Code Tools to Generative and Agentic AI
DESCRIPTION:Presenter: Reza Fazel-Rezai\, Senior Science and Education Application Engineer\, MathWorks \nDescription: Please join us to learn how to accelerate data analysis using a workflow that spans low-code tools\, Generative AI\, and Agentic AI. Through live demonstrations and practical examples\, you’ll see how to import\, explore\, visualize\, model\, and process data using interactive tools that require minimal coding. The session will demonstrate how these tools can automatically generate reproducible MATLAB code\, how Generative AI can assist with code creation\, explanation\, and troubleshooting\, and how Agentic AI workflows can help plan\, execute code\, validate results\, diagnose issues\, and iteratively refine outcomes. Highlights: – Build a data analysis workflow using low-code and interactive tools. – Use Generative AI to support code generation\, explanation\, and troubleshooting. – Explore how Agentic AI can plan analysis steps\, run code\, test results\, diagnose errors\, and iterate toward reliable outcomes. \nAbout the speaker: Dr. Reza Fazel-Rezai\, with a Ph.D. and MS in Biomedical Engineering and a BS in Electrical Engineering\, brings over two decades of experience in both industry and academia. As a senior research scientist\, research team manager\, and the founding Director and tenured full Professor of Biomedical Engineering\, he has extensive expertise and background in the field. Dr. Fazel-Rezai has authored more than 200 scientific publications\, edited and published seven books\, and pursued diverse research interests in biomedical signal and image processing\, particularly through machine learning and deep learning methods. Passionate about leveraging and sharing his skills to help others achieve their goals\, he currently serves as an ABET PEV for Biomedical Engineering\, works part-time as an instructor at UC San Diego\, and is a full-time Senior Science and Education Application Engineer at MathWorks. \nThis seminar is hosted by Professor Pascale Garaud.
URL:https://events.ucsc.edu/event/am-seminar-data-analysis-workflow-from-low-code-tools-to-generative-and-agentic-ai/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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