Ashwin Rao Stanford University Adjunct Professor : UC Berkeley Haas Speaker Profile
UC Berkeley’s Financial Innovation Conference
Ashwin Rao has more than two decades of experience as a leader in the Finance and Retail industries, with a consistent focus on creating outsized business value through technological innovations. Specifically, he has led science and engineering teams building products for Trading, Risk-Management, Pricing, Forecasting, Supply-Chain, Personalized Customer Experience. He brings unique skills in translating challenging business problems into technical specifications, solving them by blending traditional mathematical/algorithmic methods with modern machine learning methods, and articulating commercial value of complex technology in simple and intuitive ways across the enterprise.
Ashwin has spent the past 6 years in the Retail industry where he and his teams have been designing and engineering mathematical models and algorithms to create operational efficiencies and enable customers to find and acquire the right products in a seamless manner. Ashwin is also an Adjunct Professor at Stanford University where he serves as the Director of the Mathematical & Computational Finance program, and focuses his research and teaching on AI for Sequential Optimal Decisioning under Uncertainty, particularly Reinforcement Learning algorithms and particularly applied to financial trading problems.
He is the author of a book on Reinforcement Learning for Trading (https://www.amazon.com/Foundations-Reinforcement-Learning-Applications-Finance/dp/1032124121), and has developed extensive open-source code for models and algorithms on this topic.
AshwinRao_Bio.docx (stanford.edu)
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