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DTSTART;TZID=America/Los_Angeles:20261019T160000
DTEND;TZID=America/Los_Angeles:20261019T170000
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SUMMARY:AM Seminar: Analysis of Flagellar Gait Changes Across Fluid Viscosities
DESCRIPTION:Presenter: Dr. Kelli Gutierrez\, CSU Monterey Bay \nDescription: Many microswimmers propel themselves using flagella\, which are thin\, threadlike filaments that beat in a periodic wavelike motion. The flagellar beat emerges from the coupled interactions between the surrounding fluid and the active and passive responses of the flagellum. Previous studies have observed the qualitative shape of the flagellar waveform and the swimming speed to change with fluid viscosity. We quantify changes in the flagellar waveforms of \textit{Chlamydomonas reinhardtii} in response to changes in fluid viscosity using (i) shape mode analysis and (ii) a full swimmer simulation to analyze how shape changes affect the swimming speed. By decomposing the gait into the time‑independent mean shape and the time‑varying stroke\, we find that the time-independent mean shape changes substantially in response to viscosity\, while the changes in the time-varying stroke are more subtle. \nAbout the speaker: Dr. Gutierrez received her Ph.D. in Applied Mathematics from UC Davis. She joined the Department of Mathematics and Statistics Department at Cal State Monterey Bay in 2026. Her research interests include mathematical biology\, fluid dynamics\, and applied mathematics. \nThis seminar is hosted by Applied Mathematics.
URL:https://live-events-ucsc.pantheonsite.io/event/am-seminar-analysis-of-flagellar-gait-changes-across-fluid-viscosities/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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DTSTART;TZID=America/Los_Angeles:20261102T160000
DTEND;TZID=America/Los_Angeles:20261102T170000
DTSTAMP:20261001T175836Z
CREATED:20261001T175836Z
LAST-MODIFIED:20261001T175836Z
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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://live-events-ucsc.pantheonsite.io/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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DTSTART;TZID=America/Los_Angeles:20261109T160000
DTEND;TZID=America/Los_Angeles:20261109T170000
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SUMMARY:AM Seminar: Enhanced Resolution Imaging in Strongly Scattering Media
DESCRIPTION:Presenter: Chrysoula Tsogka\, Professor\, Applied Mathematics\, UC Merced \nDescription: In a strongly scattering medium\, waves undergo multiple scattering that is usually seen as an obstacle to imaging. Time-reversal experiments show the opposite: waves re-emitted into the medium refocus on their source more sharply than in a homogeneous medium\, because scattering makes the array appear larger than it is. This effect\, known as super-resolution\, is not available to conventional imaging. Since the medium through which the waves travelled is unknown\, conventional methods back-propagate the data in an approximation of the true background. In this talk I will show how super-resolution can be achieved in imaging when abundant array data are available. The key idea is to learn the Green’s functions of the unknown random medium directly from the data using sparse dictionary learning. The Green’s functions are recovered as unordered columns of the sensing matrix. To associate each column with its location in the imaging window\, we build a graph from cross-correlations of the recovered columns and apply multidimensional scaling to the resulting proxy distances. The learned Green’s functions are then used to form images by back-propagation or by $\ell_2$ and $\ell_1$ methods\, with resolution beyond the homogeneous medium limit. I will also discuss recent extensions: a new dictionary learning algorithm that starts from a random initialization\, imaging on unstructured grids\, and imaging through changing random media. Joint work with M. Moscoso\, A. Novikov\, G. Papanicolaou\, A. Christie\, M. Leibovich and J. Zheng. \nAbout the speaker: Chrysoula Tsogka is a Professor of Applied Mathematics at the University of California\, Merced\, where she also serves as Chair of the Applied Mathematics Graduate Group. She received her Ph.D. in Applied Mathematics from the University Paris IX Dauphine and was a Postdoctoral Fellow at Stanford University. Before joining UC Merced in 2019\, she was a tenured CNRS researcher at LMA in Marseille\, an Assistant Professor at the University of Chicago\, and a Professor at the University of Crete. Her research focuses on numerical methods for direct and inverse wave propagation problems and on imaging in complex media. Her recent work includes quantitative synthetic aperture radar (SAR) imaging for the detection and classification of buried landmines\, and data-driven methods\, such as dictionary learning\, for super-resolution imaging in strongly scattering media. She serves on the editorial boards of Inverse Problems\, the Journal of Computational Physics and the Journal of Mathematical Imaging and Vision.
URL:https://live-events-ucsc.pantheonsite.io/event/am-seminar-enhanced-resolution-imaging-in-strongly-scattering-media/
LOCATION:Jack Baskin Engineering\, Baskin Engineering 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Lectures & Presentations,Seminars
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