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Marcos López de Prado is a Senior Managing Director at Guggenheim Partners, where he manages several multibillion-dollar internal funds. Over the past 19 years, his work has combined advanced mathematics with supercomputing technologies to deliver billions of dollars in net profits for investors and firms. A proponent of research by collaboration, Marcos has published with over 30 leading academics, resulting in some of the most read papers in Finance (SSRN), 7 international patent applications on Algorithmic Trading, 4 textbooks, numerous articles in the top Mathematical Finance journals, etc. He serves on the editorial board of 5 academic journals, including the Journal of Portfolio Management (IIJ). In 2017 he was elected to the board of directors of the IAQF.

Since the year 2010, Marcos has also been a Research Fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy’s Office of Science), where he conducts research in the mathematics of large-scale financial problems and HPC at the Computational Research Department. For the past 7 years he has lectured at Cornell University, where he currently teaches a graduate course in Financial Big Data and Machine Learning at the Operations Research Department.

Marcos is a recipient of the 1999 National Award for Academic Excellence, which the Government of Spain bestows once a year to the best graduate student nationally. He earned a Ph.D. in Financial Economics (2003), and a second Ph.D. in Mathematical Finance (2011) from Universidad Complutense de Madrid (est. 1293). Between his two doctorates, Marcos was a Postdoctoral Research Fellow of RCC at Harvard University for 3 years, during which he published over a dozen articles in JCR-indexed scientific journals. Marcos has an Erdös #2 and an Einstein #4 according to the American Mathematical Society.


For Finance to serve society, it needs to evolve beyond guesswork and toy models. Just as modern Physics cannot advance without facilities like the Large Hadron Collider (LHC), modern Finance needs machinery up to the complex task at hand. Above, a presentation on Quantum Computing technologies at Exponential Finance 2016.