Quant Summit USA

Prof. Marcos López de Prado is the CIO of True Positive Technologies (TPT), and Professor of Practice at Cornell University’s School of Engineering. He has over 20 years of experience developing investment strategies with the help of machine learning algorithms and supercomputers. Marcos launched TPT after he sold some of his patents to AQR Capital Management, where he was a principal and AQR’s first head of machine learning. TPT is currently engaged by clients with a combined AUM in excess of $1 trillion. Marcos also founded and led Guggenheim Partners’ Quantitative Investment Strategies business, where he managed up to $13 billion in assets, and delivered an audited risk-adjusted return (information ratio) of 2.3.

Concurrently with the management of investments, since 2011 Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals, is a founding co-editor of The Journal of Financial Data Science, has testified before the U.S. Congress on AI policy, and SSRN ranks him as the most-read author in economics. Marcos is the author of several graduate textbooks, including Advances in Financial Machine Learning (Wiley, 2018) and Machine Learning for Asset Managers (Cambridge University Press, 2020).

Marcos earned a PhD in financial economics (2003), a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he is a faculty member. Marcos has an Erdős #2 according to the American Mathematical Society, and in 2019, he received the ‘Quant of the Year Award’ from The Journal of Portfolio Management.

Fabio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU, and a former CME risk committee member. He has jointly authored the book 'Interest rate models: theory and practice' and published extensively in books and international journals, including 16 cutting-edge articles in Risk Magazine. Fabio holds a BSc in Applied Mathematics from the University of Padua, Italy, and a PhD in Mathematical Finance from the Erasmus University of Rotterdam, The Netherlands

Andrew Dyson is the Chairman and Chief Executive Officer for QMA. Prior to joining QMA, he was an Executive Vice President at Affiliated Managers Group, Inc., responsible for managing central global distribution platform, and Head of BlackRock’s Global Institutional Client Business following the merger of BlackRock and Barclays Global Investors. In prior roles at BlackRock and Merrill Lynch Investment Managers, he held senior distribution positions, including Head of the International Institutional Business and Head of the Institutional Business for Europe, Middle East, Africa and Asia Pacific.

Previously, Andrew was Head of US Multinational Investment Consulting and Head of UK Pension Fund Investment Consulting for William M. Mercer. He earned an MA in mathematics from Cambridge University. Andrew is a Fellow of the Institute of Actuaries.

In his role as Managing Director and Global Head of Data Analytics, Alexei is responsible for providing data analytics services to Corporate, Commercial and Institutional Banking division of Standard Chartered Bank.

He joined Standard Chartered Bank in 2010 from Barclays Capital where he managed a model development team within Credit Risk Analytics. Prior to joining Barclays Capital in 2004, he was a senior quantitative analyst at Dresdner Bank in Frankfurt.

Alexei holds MSc in Theoretical Nuclear Physics from the University of Kiev and PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine.

He was the recipient of the 2019 Quant of the Year award from Risk magazine.