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NVIDIA AI Day @ Georgia Tech

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Georgia Institute of Technology

Atlanta, GA 30332

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Georgia Tech, come join us for NVIDIA AI Day on Thursday, October 18th!

Explore the future of AI computing and robotics in engaging talks by Nathan Ratliff (NVIDIA Distinguished Research Scientist on the Robotics Research Team) and Byron Boots (Assistant Professor for the College of Computing and Visiting Faculty for NVIDIA Research).

Come and learn how they are creating new realities with AI.

*We will be raffling a GeForce GTX1080 Ti!


When: Thursday, October 18th, 2018
Who it’s for: All Georgia Tech students, professors, and faculty

See agenda below and register for the events you would like to attend.

*Space is limited.




SCHEDULE OF EVENTS:

11:00 AM – 3:00 PM | NVIDIA Recruiting
Location: College of Computing Commons

  • Come pick up swag and meet with engineers from our hardware, software, and deep learning teams!
  • Lunch will be provided


6:30 PM – 8:00 PM | NVIDIA Robotics Tech Talks

Location: Klaus Advanced Computing Building, Rm 1116 (East/West)

  • Nathan Ratliff, NVIDIA Distinguished Research Scientist
  • Byron Boots, Assistant Professor for the CoC and Visiting Faculty for NVIDIA Research
  • Food and drinks will be provided

Stay after the Tech Talks for dessert and networking!




Nathan Ratliff, NVIDIA Distinguished Research Scientist

Title: Toward Effective Collaborative Manipulation

Abstract: Effective unstructured collaborative manipulation will unlock a new wave of commercial applications and vault us into the future. Anything from aiding staff in a hospital and caring for elderly residents at nursing homes, to high-stress cooking for michelin restaurants and meticulous collaborative assembly requires a level of perception and dexterity inaccessible by modern technologies despite decades of important advances from research institutes around the world. Nvidia wants this problem solved. To aid efforts and catalyze new directions, Nvidia has established a new hub for collaborative manipulation research in Seattle near the University of Washington, directed by Prof. Dieter Fox. Nvidia’s Seattle Robotics Lab (SRL) is actively forming a multidisciplinary team with expertise from a breadth of areas such as deep learning, perception, motion generation, control, task planning, HRI, and even neuroscience tasked with collaborating toward the discovery of new approaches to manipulation and build tools to facilitate research and benchmarking across the broader community. In this talk, I’ll overview some of these efforts, including recent research exploiting known algorithmic structure in deep learning tools for perception and control, and our long-term effort to develop systems and benchmarks to streamline research in real-world unstructured manipulation.

Bio: Nathan Ratliff has been working in manipulation for over a decade studying machine learning and control approaches with a focus on reactive motion optimization and structured learning. He received his PhD on Imitation Learning from Carnegie Mellon University (CMU) in 2009 under Prof. J. Andrew Bagnell working closely with Dr. Siddhartha Srinivasa.

After continuing his work for a while at the Toyota Technological Institute in Chicago (TTI-C) and Intel Labs and brief hiatus as a software engineer at Google developing large-scale machine learning systems, he spent two years in Germany jointly with the Max Planck Institute for Intelligent Systems and the University of Stuttgart working closely with Profs. Stefan Schaal and Marc Toussaint.

In 2015, Nathan co-founded Lula Robotics in Seattle to productionize advanced perception and continuous motion generation technologies, and in 2017 he moved that effort into Nvidia to catalyze the formation of the Seattle Robotics Lab and utilize Nvidia’s resources to expand the work into areas addressing fundamental problems in manipulation research.


Byron Boots, Assistant Professor for the College of Computing and Visiting Faculty at NVIDIA Research

Title: TBA

Bio: Byron Boots is an Assistant Professor in the School of Interactive Computing within the College of Computing at Georgia Tech. Byron directs the Georgia Tech Robot Learning Lab, which is affiliated with both the Center for Machine Learning and the Institute for Robotics and Intelligent Machines. He also holds an adjunct appointment in the School of Electrical and Computer Engineering within the College of Engineering. Byron is a Visiting Faculty position in the Seattle Robotics Lab at NVIDIA Research.

Byron's group performs fundamental and applied research in machine learning, artificial intelligence, and robotics with a focus on developing theory and systems that tightly integrate perception, learning, and control. Their work touches on a range of problems including computer vision, system identification, time-series forecasting, state estimation, localization and mapping, motion planning, and high-speed navigation. The algorithms that they develop use and extend theory from graphical models, nonparametric statistics, neural networks, non-convex optimization, online learning, reinforcement learning, and optimal control.

Prior to joining Georgia Tech, Byron was a post-doc in the Robotics and State Estimation Lab directed by Dieter Fox in the Computer Science and Engineering Department at the University of Washington. Byron received his Ph.D. from the Machine Learning Department at Carnegie Mellon University where he was a member of Sense, Learn, Act (SELECT) Lab co-directed by Carlos Guestrin and his advisor Geoff Gordon.

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Georgia Institute of Technology

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