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Calendar

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UT Dallas CS Colloquium Series Presents: Dr. Ryan McMahan 11:00 am
UT Dallas CS Colloquium Series Presents: Dr. Ryan McMahan
Feb 2 @ 11:00 am – 12:00 pm
UT Dallas Computer Science Colloquium Series Presents Dr. Ryan McMahan UT Dallas Professor of Computer Science “Virtual Reality Training Solutions for Robotic Operating-Room Staff”   Abstract: Robotic operating-room (OR) surgeons have many opportunities for training[...]
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UT Dallas CS Colloquium Series Presents: Dr. Sergey Bereg 11:00 am
UT Dallas CS Colloquium Series Presents: Dr. Sergey Bereg
Feb 9 @ 11:00 am – 12:00 pm
UT Dallas Computer Science Colloquium Series Presents Dr. Sergey Bereg UT Dallas Professor of Computer Science “Topological Methods in Computational Geometry”   Abstract: Computational Topology is a branch of topology overlapping with computer science, in[...]
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UT Dallas CS Colloquium Series Presents: Dr. Kyle Fox 10:00 am
UT Dallas CS Colloquium Series Presents: Dr. Kyle Fox
Feb 16 @ 10:00 am – 11:00 am
UT Dallas Computer Science Colloquium Series Presents Dr. Kyle Fox UT Dallas Professor of Computer Science “Surface Embedded Graphs, Shortest Homology Bases, and Holiest Paths” Abstract: Several problems from graphics and other application areas ask[...]
UT Dallas CS Colloquium Series Presents: Dr. Christopher D. Gill From Washington University in St. Louis 2:00 pm
UT Dallas CS Colloquium Series Presents: Dr. Christopher D. Gill From Washington University in St. Louis
Feb 16 @ 2:00 pm – 3:00 pm
UT Dallas Computer Science Colloquium Series Presents Dr. Christopher D. Gill Professor of Computer Science and Engineering School of Engineering and Applied Science Washington University in St. Louis “Advances in Parallel Real-Time Cyber-Physical Systems” Abstract:[...]
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UT Dallas CS Colloquium Series Presents Dr. Vibhav Gogate 10:00 am
UT Dallas CS Colloquium Series Presents Dr. Vibhav Gogate
Feb 23 @ 10:00 am – 11:00 am
UT Dallas Computer Science Colloquium Series Presents Dr. Vibhav Gogate UT Dallas Professor of Computer Science “Efficient Inference and Learning in Markov Logic Networks”   Abstract: Markov logic networks (MLNs) use weighted first-order logic formulas[...]
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