Ciamac C Moallemi

Senior Consultant

Ciamac C. Moallemi is a Senior Consultant with Compass Lexecon. Professor Moallemi is the William von Mueffling Professor of Business in the Graduate School of Business at Columbia University. His research interests are in the development of mathematical and computational tools for optimal decision making under uncertainty, with a focus on applications to areas including market microstructure, quantitative and algorithmic trading, cryptocurrencies, and blockchain technology. His expertise blends theory and practice — aside from his academic work, he also develops quantitative trading strategies at Bourbaki LLC, a quantitative investment advisor. He has been invited to present his research to numerous banks, hedge funds, and regulatory agencies. Professor Moallemi is the recipient of a number of awards, including the British Marshall Scholarship, the Benchmark Stanford Graduate Fellowship, first place in the INFORMS Junior Faculty Paper Competition, and the Best Simulation Publication Award of the INFORMS Simulation Society. Professor Maollemi has been presenter at multiple conferences and published in top academic journals including Management Science, Operations Research, The Review of Economic Studies, NeurIPS, and the American Economic Association. He holds editorial positions at the journals Management Science and Operations Research.

A high school dropout, Professor Moallemi received S.B. degrees in Mathematics and Electrical Engineering from M.I.T., a Master’s degree in Mathematics with distinction from the University of Cambridge, and a Ph.D. in Electrical Engineering from Stanford University. Prior to his doctoral studies, he developed quantitative methods in several entrepreneurial ventures: as a partner in a $200 million fixed-income arbitrage hedge fund and as the director of scientific computing at an early-stage drug discovery start-up.

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    • PhD in Electrical Engineering, Stanford University
    • Master of Advanced Study in Mathematics, University of Cambridge
    • SB in Mathematics and Electrical Engineering & Computer Science, Massachusetts Institute of Technology

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