About

Current

Adjunct Associate Professor
School of International & Public Affairs
Columbia University

Contact

Bio (short)

Neal Parikh is a computer scientist who most recently served as the first Director of Artificial Intelligence for New York City and is currently Adjunct Associate Professor at Columbia University’s School of International and Public Affairs, where he teaches a course on AI for policymakers. He co-founded SevenFifty, a technology platform acquired after 10 years in operation; was Inaugural Fellow at the Aspen Tech Policy Hub at the Aspen Institute; and worked as a senior quantitative analyst at Goldman Sachs. He received his Ph.D. from Stanford University in machine learning and convex optimization. His research includes two monographs on large-scale convex optimization that are now standard references in the field, with over 30,000 citations in the academic literature and widespread use in industry. This work also forms the mathematical foundation of SCS, an open-source optimization solver downloaded millions of times per month.

Bio (long)

Neal Parikh is a computer scientist who most recently served as the first Director of Artificial Intelligence for New York City, where he led the development of the city’s AI strategy and advised on AI policy, legislation, ethics, as well as local and international collaborations. He is currently Adjunct Associate Professor at Columbia University’s School of International and Public Affairs, where he teaches a course on AI for policymakers.

Previously, he co-founded SevenFifty, a platform for the wholesale beverage industry used by over 100,000 restaurants, bars, and retailers, which was acquired in 2022; was Inaugural Fellow at the Aspen Tech Policy Hub at the Aspen Institute; and worked as a senior quantitative analyst at Goldman Sachs, where he worked on a portfolio optimization system managing over $100 billion in investments. He received his Ph.D. from Stanford University in machine learning and convex optimization. His research includes two standard-reference monographs on large-scale convex optimization that have received over 30,000 citations in the academic literature; this work also forms the mathematical foundation of SCS, an open-source optimization solver downloaded millions of times per month.

Previously

Director of Artificial Intelligence
New York City

Inaugural Fellow
Aspen Tech Policy Hub
The Aspen Institute

Visiting Lecturer
Cornell Tech · Operations Research and Information Engineering
Cornell University

Co-Founder
SevenFifty

Senior Quantitative Analyst
Quantitative Investment Strategies
Goldman Sachs

Education

Ph.D. in Computer Science
Advisors: Stephen Boyd, Daphne Koller
Department of Computer Science
Stanford University

Places:
Artificial Intelligence Laboratory
Information Systems Laboratory

Support:
DARPA XDATA
NSF Graduate Research Fellowship
Cortlandt & Jean E. Van Rensselaer Engineering Fellowship

B.A.S., summa cum laude
Computer & Information Science · Mathematics
University of Pennsylvania