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Vasant Dhar

Vasant Dhar

Joined Stern 1983

Leonard N. Stern School of Business
Kaufman Management Center
44 West Fourth Street, 8-92
New York, NY 10012

E-mail vd1@stern.nyu.edu
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Biography

Vasant Dhar is an Artificial Intelligence researcher and data scientist and host of the podcast, "Brave New World," which explores how technology and virtualization in the post-COVID era is transforming humanity. He brought Machine Learning to Wall Street in the 90s, and subsequently founded the Machine-Learning-Based hedge-fund SCT Capital Management.

Dhar’s research focuses on how risk influences our trust in AI systems. It shows the existence of an “automation frontier” that expresses a tradeoff between how often the machine will be wrong and the consequences of its errors. Trust, and hence our willingness to cede control of decision making to the machine, rises with decreasing error rates and lower error costs. The automation frontier provides a natural way to think about the division of responsibility between humans and machines and future of work.

More broadly, Dhar’s research examines how innovations such as Artificial Intelligence impact our lives, and how we can create technology and policy for a better future in a world of increasingly intelligent machines.

Dhar writes regularly in the media on Artificial Intelligence, societal risks of AI platforms, data governance, privacy, ethics, and trust. He is a frequent speaker in academic and industrial forums.

Professor Dhar teaches courses on Systematic Investing, Data Science, Prediction, and Tech Innovation.

He has written over 100 research articles, funded by grants from industry and government agencies such as the National Science Foundation.

Professor Dhar received his Bachelor of Technology from the Indian Institute of Technology in Delhi, and his Master of Philosophy and Doctor of Philosophy from the University of Pittsburgh.

Research Interests

  • Data Science
  • Predictive Analytics
  • Artificial Intelligence
  • Machine Learning
  • Data Governance

Courses Taught

  • Foundations of FinTech
  • Introduction to Data Science
  • Robo Advisors and Systematic Investing

Academic Background

Ph.D., Artificial Intelligence, 1984
University of Pittsburgh

M.Phil., 1982
University of Pittsburgh

B.Tech., Chemical Engineering, 1978
Indian Institute of Technology, Delhi

Awards & Appointments

 
Editor-in-Chief Big Data 2014
Principal Investigator Mining Online Delegate Data for 2012 US Presidential Elections, July 2011 2011
Co-Principal Investigator Interdisciplinary Studies in Security and Privacy, NYU Abu Dhabi 2011
Principal Investigator Risk-Driven Catastrophes in Global 1000 Companies, funded by Deloitte & Touche 2010
Principal Investigator News as a Risk Factor in Predictive Modeling, supported by Thomson Reuters ('10-present) 2010
Daniel P. Paduano Fellow ('09-'11) NYU Stern 2009
Co-Director Center for Business Analytics 2006