Jay is a scientist who enjoys thinking out of the box to untangle challenges in machine intelligence and reasoning. He has a Ph.D. and more than 8 years of experience in applied AI / Machine Learning. He leads the AI team at Autodesk and is an adjunct faculty of Columbia University. Jay has authored more than 15 patents and 20 publications on AI applications.
His main areas of specialties are: Distributed Intelligence and Decision Making, Machine Learning, Knowledge Representation and Reasoning, Time_Series Analysis, Anomaly Detection, Dialogue Management (ChatBots), Graph Theory, Bayesian Networks and Rule Engines.
On his free time, Jay loves to run, play soccer, and card games.
In this part-time course, students learn to build robust predictive models, test their validity, and clearly communicate resulting insights.