Applied Microeconomics and Trade Seminar Series Presents: Guo Xu
Engineering 2 Engineering 2 1156 High Street, Santa Cruz, CAApplied Microeconomics and Trade Seminar: Guo Xu
7 events found.
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Statistics Seminar: Heterogeneous Statistical Transfer Learning
Engineering 2, 499Hybrid EventPresenter: 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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Statistics Seminar: Boosting Biomedical Imaging Analysis via Distributed Functional Regression and Synthetic Surrogates
Engineering 2, 599Virtual EventPresenter: 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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AM Seminar: Probing Forced Responses and Causality in Data-Driven Climate Emulators: Conceptual Limitations and the Role of Reduced-Order Models
Virtual EventPresenter: 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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Statistics Seminar: Inferring Unobserved Trajectories from Multiple Temporal Snapshots
Engineering 2, 599Virtual EventPresenter: 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 multiple time points. E.g. given single-cell sequencing data, scientists would like to learn how gene expression changes over a cell’s life cycle. But sequencing any […]
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AM Seminar: Data Driven Modeling for Scientific Discovery and Digital Twins
Jack Baskin Engineering, 372Presenter: 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 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 […]
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AM Seminar: Multiscale Modeling of Cellular Membranes and Oncogenic Proteins
Jack Baskin Engineering, 372Presenter: 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 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 […]