NVIDIA GPU Deep Learning Symposium

Jeffrey Young

Please join us for an NVIDIA-organized symposium to learn more about exciting research and tools for using deep learning with GPU platforms. Topics will include discussions of NVIDIA research using deep learning in the automotive, robotic, health sciences, and defense areas as well as cutting-edge talks from Georgia Tech and GTRI scientists who have combined GPU acceleration with deep learning to solve problems in the areas of robotics and computer vision, health care, and online recommendation systems. In addition, learn more about available NVIDIA resources and upcoming seminars that you can use to accelerate your own deep learning applications. 
Update: We are unfortunately sold out of tickets for this event! However, we are planning to try and record and post sessions and slides here after the event.
 
Presenters and Schedule:
<UL>
<LI>Craig Tierney - NVIDIA Solutions Architect</LI>
<LI>Zsolt Kira - GTRI scientist working on computer vision and robotics applications. </LI>
<LI>Oded Green - GT scientist who is creating new CUDA-based data structures to support graphs and deep learning.</LI>
<LI>Le Song - GT scientist investigating uses of deep learning for graph analytics.</LI>
<LI>Jimeng Sun - GT scientist using deep learning to help solve challenging problems in the medical arena.</LI>
</UL>
10-11:30:         Craig Tierney - Overview of NVIDIA research into deep learning 11:30-12:00:    Le Song - Deep Learning for dynamic graphs and data structures 12:00-12:20:    Lunch/break  12:20-1:00:      Craig - Generative Adversarial Networks (GANs) 1:00-1:30:        Zsolt Kira - Robotic Perception and Learning 1:30-1:45:        Break 1:45-2:15:        Jimeng Sun - Deep Learning for Improved Healthcare Outcomes 2:15-2:45:        Oded Green - cuSTINGER: GPU-focused data structures for deep learning and dynamic graphs 2:45-3:00:        Wrap-up 
Logistics:
<UL>
<LI>April 18th, 10 AM - 3 PM.</LI>
<LI>This symposium will be held in the Bill Moore Student Success Center, Press Room B (west end of the football stadium). When you go in, please go to the right and take the elevator to the 2nd floor.</LI>
<LI>RSVP required as space is limited! Please only RSVP if you are able to attend most of the session. </LI>
<LI>Box lunch will be served.</LI>
<LI>Please direct any questions to the event organizer, Jeff Young.</LI>
</UL>
Directions to the Student Success Center:
For GPS, please use:
Alumni House, 190 North Ave. NW Atlanta, GA 30313
Because the Bill Moore Student Success Center has a campus address (rather than a street address), please use the GPS address for the Georgia Tech Alumni House, listed above. The Alumni House is located across the street from our building, just west of Interstate 75/85 on North Avenue NW. Paid parking is available in Area 1, located just past the 3-tier parking deck next to the Alumni House. Once parked, cross the street using the designated crosswalk or the sky bridge which crosses the street. Once you cross North Avenue, you’ll find our building just down the path on the right-hand side, built into the west side of the football stadium, facing Tech Tower.
*Please note that this event is in Press Room B on the 2nd floor. To get to this location please take a right as you enter and take the elevator to the 2nd floor. From the elevator go left and down the hall.

Bill Moore Student Success Center

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NVIDIA GPU Deep Learning Symposium

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NVIDIA GPU Deep Learning Symposium

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