报告人：Ming C Lin，美国马里兰大学讲席教授、ACM Fellow、IEEE Fellow
报告时间：2021年6月15日 (星期二) 上午9:00 - 10:00
Meeting ID: 281 001 9605
报告摘要：With increasing availability of data in various forms from images, audio, video, 3D models, motion capture, simulation results, to satellite imagery, representative samples of the various phenomena constituting the world around us bring new opportunities and research challenges. Such availability of data has led to recent advances in data-driven modeling. However, most of the existing example-based synthesis methods offer empirical models and data reconstruction that may not provide an insightful understanding of the underlying process or may be limited to a subset of observations.
In this talk, I present recent advances that integrate classical model-based methods and statistical learning techniques to tackle challenging problems that have not been previously addressed. These include flow reconstruction for traffic visualization, learning heterogeneous crowd behaviors from video, simultaneous estimation of deformation and elasticity parameters from images and video, and example-based multimodal display for VR systems. These approaches offer new insights for understanding complex collective behaviors, developing better models for complex dynamical systems from captured data, delivering more effective medical diagnosis and treatment, as well as cyber-manufacturing of customized apparel. I conclude by discussing some possible future directions and challenges.
报告人简介：Ming C Lin is a Distinguished University Professor, Barry Mersky and Capital One Endowed Professor, and former Elizabeth Stevinson Iribe Chair of Computer Science at the University of Maryland at College Park, as well as John & Louise Parker Distinguished Professor Emerita of Computer Science at the University of North Carolina (UNC) - Chapel Hill. She is also an Amazon Scholar. She received her B.S., M.S., Ph.D. degrees in Electrical Engineering and Computer Science respectively from the University of California, Berkeley. She has received several honors and awards, including the NSF Young Faculty Career Award, UNC Hettleman Award for Scholarly Achievements, Beverly W. Long Distinguished Term Professor, IEEE VGTC VR Technical Achievement Award, Washington Academy of Sciences Distinguished Career Award, and several best paper awards. She is a Fellow of ACM, IEEE, and Eurographics, and a member of ACM SIGGRAPH Academy. She is also a member of CRA-WP Board of Directors, a former Chair of IEEE Computer Society (CS) Computer Pioneer Awards Committee, IEEE CS Fellows Committee, and IEEE CS Transactions Operations Committee, as well as the Founding Chair of ACM SIGGRAPH Outstanding Doctoral Dissertation Award Committee. She is an Editor-in-Chief Emerita of IEEE Transactions on Visualization & Computer Graphics and a former IEEE CS Board of Governors member.
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