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SpeakerTopicsTitleFaculty hostSpeaker Webpage
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Fall, 2019
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September 4Barbara Thompson, NASA Goddard
Application of AI/Machine learning in astrophysics
Sylvina
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9/18/2019Jean Camp, Indiana Universitysecurity and privacyWhat's the Problem: Reasons for InsecurityBei Xiao
https://sice.indiana.edu/contact/profile/?profile_id=178
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September 25
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10/9/2019
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10/16/2019
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10/23/2019Bert Huang, Virginia TechMachine LearningBei Xiao http://people.cs.vt.edu/~bhuang/
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November 6Roberto Corizzo, AU
Forecasting, Time Series, Sensor Data, Spatio-Temporal Autocorrelation
Nathalie
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November 13Robert Rand, UMDverification, quantum computingMark Nelson
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November 20Lap-Fai (Craig) Yu, George Mason University HCI, Graphics, VR/ARBei Xiaohttps://craigyuyu.github.io/home/
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December 4Max Leiserson, UMD (to be confirmed)
Machien learning, Computational Biology, Theory
Bei Xiao
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Spring 2019
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Feb 4Soheil Feizi/UMDMachine learning
GANs meet VAEs: Towards a Comprehensive Understanding of Generative Models
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Feb 11
Perry Zurn(AU) and David Lydon-Staley (UPenn)
Curiosity
Hunters, busybodies, and the role of deprivation-type curiosity in knowledge network building
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Feb 25 Braxton Boren (AU) Auditory scene analysisComputer Simulation of Past Soundscapes
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March 25Jason Fischer (John Hopkins) Computational neuroscience, fMRI Intuitive physics: building a mental model of how the world behaves
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April 15Thomas Goldstein/UMDMachine learning/Computer Vision
A theoretical look at adversarial example: a perspective from high-dimensional geometry
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April 22Huaishu Peng /UMDHCI/Robotics/3D printingTBA
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Fall 2018
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Nov 1Nathalie Japkowicz/AUMachine learningToward a Lifelong Self-Adaptive Monitoring System
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Nov 5Ting Hua/John Hopkins NLP/Social networks/Machine learningTake Bayesian probability into Deep Learning
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Nov 8John Dickerson/UMDAI/Machine Learning/Data Science
Using Optimization to Balance Fairness and Efficiency in Kidney Exchange
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Nov 12Simon Leonard/John HopkinsRoboticsFrom Teleoperation to Automation: Improving Surgical Outcomes
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Nov 19Mike Trenor/AUGame/AI
Computer Science and Games: How Computational Models Help Us Understand and Create Meaningful Game
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Nov 26Hamed Pirsiavash/UMBCComputer Vision Self-supervised learning for visual recognition
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