Marcos López de Prado

Dr. Marcos López de Prado OMC is a computational scientist, hedge fund manager and professor known for pioneering machine learning and statistical inference methods that are now widely adopted at some of the largest investment corporations. He is currently Global Head of Quantitative R&D at the Abu Dhabi Investment Authority (ADIA), one of the largest sovereign wealth funds, and is a founding board member of ADIA Lab, Abu Dhabi's center for research in data and computational sciences. The U.S. Congress has invited him to testify on AI policy, he is the named inventor on 15 patents, and the Social Science Research Network (SSRN) ranks him among the 10 most-read authors in Economics. He has published over 100 scientific journal articles in collaboration with over 50 researchers, including several Nobel laureates. These contributions have earned him prestigious scientific, state, and industry awards. In 2024, His Majesty King Felipe VI and the Government of Spain appointed him Knight Officer of the Royal Order of Civil Merit (OMC), "for distinguished services to science and the global investment industry." Before ADIA, Prof. López de Prado founded True Positive Technologies LP (TPT), a firm that researches and develops investment IP. TPT has advised clients with a combined AUM in excess of $1 trillion, and has licensed and sold several patents to some of the largest investment funds in eight-figure dollar deals. Before TPT, he was a Partner and the first Head of Machine Learning at AQR Capital Management. As a Senior Managing Director at Guggenheim Partners, he also founded and led its Quantitative Investment Strategies business, where he managed $13 billion in assets, and delivered an audited risk-adjusted return (information ratio) of 2.3. Since 2011, concurrently with the management of multibillion-dollar funds, Prof. López de Prado has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He is a founding co-editor of The Journal of Financial Data Science, and the author of several influential graduate textbooks, including Advances in Financial Machine Learning (Wiley, 2018), Machine Learning for Asset Managers (Cambridge University Press, 2020), and Causal Factor Investing (Cambridge University Press, 2023). He earned a PhD in financial econometrics (2003), and a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid. He completed his post-doctoral research at Harvard University and Cornell University, where he has been Professor of Practice at the College of Engineering since 2015. He has an Erdős #2 (via Neil Calkin) and an Einstein #4 according to the American Mathematical Society.

Affiliation on publications · Environment Agency Abu Dhabi