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.
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.
Anting's expertise spans computer vision, deep learning, training data management, and front-end development. In the past, Anting scaled search and machine learning over enormous datasets while working at Yelp. Anting earned a BS in Computer Science at UC Berkeley, and he is currently wrapping up his MS in CS.