Similarity Learning For Financial Domain : Dr. Dhagash Mehta, Head of Applied Machine Learning Research, Blackrock

Similarity Learning For Financial Domain : Dr. Dhagash Mehta, Head of Applied Machine Learning Research, Blackrock

MIT Quant & Ai Conference 2022 : Full Agenda

Dr. Mehta is the Head of Applied Machine Learning Research (Investment Management) at Blackrock Inc. and an Editorial Board Member at the Journal of Financial Data Science (

Previously I was a Senior Manager, Investment Strategist (Machine Learning – Asset Allocation) at Investment Strategy Group at The Vanguard Group. Before joining Vanguard, I was a Senior Research Scientist at United Technologies (UTX) Research Center. Prior to that, I was a Research Assistant Professor at Department of Applied and Computational Mathematics and Statistics in conjunction with Department of Chemical and Biomolecular Engineering at University of Notre Dame. I was a Fields Institute Postdoc Fellow for the Thematic Program on Computer Algebra at Fields Institute, Toronto, in Fall 2015 and a Visiting Fellow at Simons Institute for Theory of Computing at Berkeley in Fall 2014. Previously, I have held various research positions at the University of Cambridge (the UK), Imperial College London (the UK), the University of Adelaide (Australia), Syracuse University (USA) and National University of Ireland Maynooth (Ireland).

Dr. Mehta’s research areas are machine/deep learning; quantitative finance, and computational mathematics, science and engineering. In particular, I work on optimization (convex and nonconvex), computational algebraic geometry, numerical analysis, network science and machine learning to solve various problems arising in financial services and wealth/asset management (and in the past, power systems and control theory; and theoretical and computational physics, jet-engines, HVAC and building systems, chemistry and biology).

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