Perception for Autonomous Vehicles

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The DeepScale Team

Forrest Iandola

Forrest Iandola

Forrest started his career in high-performance computing (i.e. writing fast and scalable software), and he has spent the last several years as a PhD student at Berkeley accelerating and rethinking computer vision algorithms. He has published more than twenty papers, and all of his most recent papers are on accelerating and improving deep learning for computer vision. Forrest is also a huge car enthuaiast, and when not stuck in traffic, he enjoys few things more than spending the day driving on a racetrack.

Kurt Keutzer

Kurt Keutzer

After leaving his position as CTO and Senior Vice-President of Research at Synopsys to become Professor of EECS at University of California, Berkeley, Kurt and his students have focused on applying commodity parallelism to accelerate emerging applications. In particular, Kurt's research group has achieved significant speedups in machine learning (SVMs), computer vision, speech recognition, multimedia analytics, computational finance, and, most recently, training and deployment of deep neural networks. As a researcher, Kurt has published six books and over 200 refereed articles. As an entrepreneur, Kurt has been an investor and advisor to thirteen startups and an advisor to seven more.

Don MacMillen

Don MacMillen

Don's career as a technologist and a senior executive spans the semiconductor and EDA (electronic design automation) industries. He has served as the Vice President of Engineering for four startups in the EDA and semiconductor space, including Stretch, where he led the development of hardware and embedded software solutions for video encoding and processing. At Synopsys, he served as VP of Engineering for Mixed Signal Simulation and TCAD as well as VP of the Advanced Technology Group and it was at Synopsys that Don met and worked with Kurt Keutzer. As a technologist, Don has worked on semiconductor microlithography, device, process, and circuit simulation, timing analysis, logic modeling, logic and RTL synthesis, power and signal integrity. At Nimbic, he delivered cloud enabled HPC for electo-magnetic simulation of boards and packages. More recently, he has provided consulting in text mining and real time web infrastructure. Don holds a PhD in Theoretical Chemistry.

Anting Shen

Anting Shen

Anting expertise includes his experience with computer vision and deep learning from his time in Berkeley's Robot Learning Lab & the ASPIRE lab, and experience in training data management and application development through his time at Google and Yelp. After receiving his B.S. in EECS from Berkeley, he entered entrepreneurship by founding a startup. He is now finishing up his M.S. in Computer Science at Berkeley.

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