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Vice President and Applied Deep Learning Researchat NVIDIA
Bryan Catanzaro's profile covers his NVIDIA career, deep learning research, and work in speech recognition.
Bryan Catanzaro is Vice President, Applied Deep Learning Research at NVIDIA, where he focuses on applying deep learning to problems ranging from video games to chip design. His work spans deep neural networks, machine learning, computer architecture, and AI research. Before taking his current leadership role, he worked as a research scientist at NVIDIA and as a senior researcher at Baidu, where he managed a team researching methods for training and deploying deep neural networks, with a focus on speech recognition. Catanzaro also has academic research experience from the University of California, Berkeley, and has contributed to work in areas including end-to-end speech recognition and deep learning.
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Field |
Details |
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Full Name |
Bryan Catanzaro |
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Current Position |
Vice President, Applied Deep Learning Research |
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Current Company |
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Location |
Santa Clara, California, United States |
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Previous Leadership Experience |
Managed a 15-person research team at Baidu |
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Previous Companies |
Baidu, NVIDIA |
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Academic Institution |
University of California, Berkeley |
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Education |
PhD in Electrical Engineering and Computer Sciences; MS in Electrical Engineering |
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Languages |
English, Russian |
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Technical Skills Listed |
Computer Architecture, Verilog |
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Publication |
DeepSpeech: Scaling up end-to-end speech recognition |
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Research Area |
Deep neural networks and end-to-end speech recognition |
Catanzaro began his professional research career at NVIDIA, where he also completed an internship focused on the Copperhead language and compiler. He later became a Research Scientist at the company before joining Baidu as a Senior Researcher in 2014. At Baidu, he managed a 15-person research team focused on deep neural network training and deployment, particularly for speech recognition. He returned to NVIDIA in 2016 as Vice President of Applied Deep Learning Research. His academic background includes graduate research in Electrical Engineering and Computer Science at UC Berkeley.
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Year |
Career Development |
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2004–2005 |
MS, Electrical Engineering, Brigham Young University: Completed a master's degree in Electrical Engineering. |
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2005–2011 |
Graduate Student Researcher, University of California, Berkeley: Conducted graduate research while pursuing a PhD in Electrical Engineering and Computer Sciences. |
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May 2009–Aug 2009 |
Intern, NVIDIA: Worked on the Copperhead language and compiler during an NVIDIA internship. |
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2005–2011 |
PhD, Electrical Engineering and Computer Sciences, University of California, Berkeley: Completed doctoral studies in Electrical Engineering and Computer Sciences. |
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May 2011–Jun 2014 |
Research Scientist, NVIDIA: Worked on research involving deep learning and related computing technologies. |
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Jun 2014–Aug 2016 |
Senior Researcher, Baidu: Managed a team of 15 researchers working on tools and methodologies for training and deploying deep neural networks, with a focus on speech recognition. |
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Sep 2016–Present |
Vice President, Applied Deep Learning Research, NVIDIA: Leads applied deep learning research focused on using deep learning to address problems ranging from video games to chip design. |
Company Name | Investor Category | Invested Date | Funding Round | Invested Fund |
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Result Not FoundNo Records Found | ||||
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