Big data and AI are joined at the hip: the best AI applications require massive amounts of constantly updated training data to build state-of-the-art models AI has always been one of the most exciting applications of big data and Apache Spark. Increasingly Spark users want to integrate Spark with distributed deep learning and machine learning frameworks built for state-of-the-art training.
Ion Stocia is the Executive Chairman and co-founder of Databricks. Ion also serves as a professor in the EECS Department at UC Berkeley, and as a co-director of the AMPLab. At AMPLab Ion has been leading the software systems effort, which included the development of Apache Spark, as well as two other high profile open source projects: Apache Mesos and Tachyon. In 2006, he co-founded Conviva, a startup to commercialize technologies for large scale video distribution, where he is serving as a CTO. Ion is an ACM Fellow and has received numerous awards, including the SIGCOMM Test of Time Award (2011), and the ACM doctoral dissertation award (2001). Ion holds a Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University and an M.S. in Computer Science and Control Engineering from Polytechnic University Bucharest.
Frank is the Technical Director for the Healthcare and Life Sciences vertical at Databricks. Prior to joining Databricks, Frank was a lead developer on the Big Data Genomics/ADAM and Toil projects at UC Berkeley, and worked at Broadcom Corporation on design automation techniques for industrial scale wireless communication chips. Frank holds a PhD and Masters of Science in Computer Science from UC Berkeley, and a Bachelor’s of Science with Honors in Electrical Engineering from Stanford University.