Tag: Baskin Engineering
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Semiconductor Career Summit – From Campus to Silicon Valley
A SEMI Professional Development Seminar organized by the SEMI Silicon Valley Chapter – Connecting College Students to the Semiconductor Industry. Learn about career opportunities in high tech and acquire valuable, practical information that will help you choose career directions and plan for your success.
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Statistics Seminar: Rotated Mean-Field Variational Inference and Iterative Gaussianization
Presenter: Sifan Liu, Assistant Professor, Department of Statistical Science, Duke University Description:Mean-field variational inference (MFVI) approximates a target distribution with a product distribution in the standard coordinate system, offering a […]
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Statistics Seminar: Mathematical Foundations for Machine Learning from a Nonlinear Time Series Perspective
Presenter: Jiaqi Li, William H. Kruskal Instructor, University of Chicago Description:Modern machine learning (ML) algorithms achieve remarkable empirical success, yet providing rigorous statistical guarantees remains a major challenge, particularly in […]
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Statistics Seminar: Inferring Unobserved Trajectories from Multiple Temporal Snapshots
Presenter: Yunyi Shen, Ph.D. Candidate, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology Description: Practitioners often aim to infer an unobserved population trajectory using sample snapshots at […]
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Statistics Seminar: Boosting Biomedical Imaging Analysis via Distributed Functional Regression and Synthetic Surrogates
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 […]
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Statistics Seminar: Heterogeneous Statistical Transfer Learning
Presenter: Subhadeep Paul, Associate Professor, Ohio State University Description: In the first part of the talk, we consider the problem of Transfer Learning (TL) under heterogeneity from a source 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
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 […]
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AM Seminar: Data Driven Modeling for Scientific Discovery and Digital Twins
Presenter: Dongbin Xiu, Professor, Ohio State University Description:We present a data-driven modeling framework for scientific discovery, termed Flow Map Learning (FML). This framework enables the construction of accurate predictive models […]
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AM Seminar: Multiscale Modeling of Cellular Membranes and Oncogenic Proteins
Presenter: Liam Stanton, Professor, San Jose State University Description: In this talk, I will present a multiscale model for cellular membranes, which is trained on molecular dynamics simulations. The model […]
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AM Seminar: Science in the Age of Foundation Models
Presenter: Dr. Danielle Robinson, AWS AI Description: In this talk, I will discuss the large impact of foundation models within the sciences with a particular focus on the importance of […]