NVIDIA WEBINAR
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Facilitate hands-on training in AI and accelerated computing to solve real-world problems. The NVIDIA Deep Learning Institute (DLI) University Ambassador Program enables qualified educators to teach DLI workshops, at no cost, across campuses and academic conferences to faculty, students, and researchers.
Join NVIDIA’s higher education leadership and academic partners to learn how to get involved in the program.
- Obtain an overview of the NVIDIA DLI and University Ambassador Program.
- Learn how the Ambassador Program fits into larger programs that support teaching.
- Hear real examples of how leading academics are involved with the Ambassador Program.
ON-DEMAND WEBINAR REGISTRATION
THANK YOU FOR REGISTERING FOR THE WEBINAR
You will receive an email with instructions on how to join the webinar shortly.Main Content
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DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speaker
Joe Bungo
Deep Learning Institute (DLI) Program Manager, NVIDIAJoe Bungo is the Deep Learning Institute (DLI) Program Manager at NVIDIA where he enables the use of deep learning and GPU accelerated computing technologies in universities, including curriculum and teaching material development, DLI University Ambassador/Instructor Certification, facilitation of academic ecosystems, and hands-on workshops. Previously, he managed university programs at ARM Inc. and worked as an applications engineer. Joe received his degree in Computer Science from the University of Texas at Austin.
Raymond Ptucha
Assistant Professor, Rochester Institute of Technology (RIT)Raymond Ptucha is an Assistant Professor in Computer Engineering and Director of the Machine Intelligence Laboratory at Rochester Institute of Technology. His research includes machine learning, computer vision, and robotics, with a specialization in deep learning. Ray was a research scientist with Eastman Kodak Company where he worked on computational imaging algorithms and was awarded 31 U.S. patents with another 19 applications on file. He graduated from SUNY/Buffalo with a B.S. in Computer Science and a B.S. in Electrical Engineering and earned a M.S. in Image Science and his Ph.D. in Computer Science from RIT in 2013.
Gregory Gutmann
Associate Professor, Tokyo Institute of Technology (Titech)Gregory Gutmann is an Assistant Professor of Computer Science at Tokyo Institute of Technology (Titech), Tokyo Japan. He has published papers related to interactive 3D coarse-grained molecular simulations and recently co-authored a paper on Deep Learning by Doing. He is currently a part of Molecular Robotics and Artificial Muscle projects within the Konagaya Laboratory at Titech, and is an NVIDIA DLI University Ambassador.
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