Seminars

Events for January 26, 2026

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ECE Seminar: Tactile sensing: At the boundary between mechanical and computational intelligence in robotic grippers

Engineering 2 Engineering 2 1156 High Street, Santa Cruz

Presenter: Dr. Hannah Stuart, Associate Professor in the Department of Mechanical Engineering, University of California at Berkeley Description: Robot grippers typically include mechanical intelligence (e.g., underactuation, compliance) or computational intelligence (e.g., fully actuated with a wide array of sensors). Next generation grippers and hands will require both intelligences to work in concert across applications with […]

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Statistics Seminar: Boosting Biomedical Imaging Analysis via Distributed Functional Regression and Synthetic Surrogates

Virtual Event

Presenter: Guannan Wang, Associate Professor, The College of William & Mary Description: Generative AI has emerged as a powerful tool for synthesizing biomedical images, offering new solutions to challenges such as data scarcity, privacy constraints, and modality imbalance. However, the reliable use of synthetic images in scientific analysis requires principled statistical frameworks that can assess […]

CM Seminar – “Revealing Hidden Stories: Co-Designing the Thámien Ohlone Augmented Reality Tour”

Engineering 2 Engineering 2 1156 High Street, Santa Cruz

Presented by: Kai Lukoff Description: The Santa Clara University campus is adorned with symbols and monuments, including a Spanish Mission Church, that highlight its Catholic heritage. However, the presence and history of the Ohlone Native Americans, who have inhabited this land for thousands of years and continue to live in the region, receive little to […]

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AM Seminar: Probing Forced Responses and Causality in Data-Driven Climate Emulators: Conceptual Limitations and the Role of Reduced-Order Models

Virtual Event

Presenter: Fabrizio Falasca, New York University Description: 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 […]