PERSON
Vasant Dhar
NYU Stern professor of information systems and machine learning whose 2024 construction of DBOT — an AI trained on Damodaran's complete output — produced the empirical experiment that crystallized Damodaran's thinking on AI moats.
Vasant Dhar is the Howard J. Heyman Professor at NYU's Stern School of Business and a faculty member at the Center for Data Science. His research spans machine learning, predictive analytics, and the design of AI systems for decision-making in financial markets. Across three decades of work, Dhar has built a research program around the question of where machine intelligence augments human judgment and where it must defer to it. In 2024, Dhar and his team built DBOT — a large language model fine-tuned on every blog post, lecture, valuation, and book Aswath Damodaran had published — and tested whether the bot could replicate Damodaran's valuation work. The experiment's result became the founding empirical case for Damodaran's "Beat Your Bot" framework: DBOT successfully imitated Damodaran's prose but systematically failed at the framing decisions that produce credible valuations.
In The You On AI Field Guide
Dhar is one of a small number of academics whose career has straddled finance and machine learning long enough