Dr. Chitsaz received his Ph.D. at California Institute of Technology (Caltech) in Computer Science, with a focus on A.I. and machine learning, and also Molecular Biophysics where he developed massively parallel machine learning tools to solve one of the longest lasting open problems in structural biology, protein folding problem. Upon finishing his Ph.D. at Caltech, he later joined Goldman Sachs machine learning group as a senior strategist. Later he continued his work at J.P. Morgan, where he was leading the research for the US equities and ETF market making trading desk. He developed statistical arbitrage and machine learning based strategies for the US equities and ETFs. Some of the work of linear quantitative research team at J.P. Morgan is highlighted in Financial Times.