George Lentzas
George Lentzas Professor

George is a statistics expert with a decade of experience in applying quantitative models in the real world. He has worked in various capacities at leading financial institutions, such as Morgan Stanley, BNP Paribas, Citigroup, and Hutchin Hill Capital. He has also held faculty positions at Columbia University and NYU, where he has taught courses in machine learning and applied statistics and econometrics. His professional expertise includes the application of statistics, machine learning, and AI to finance and economics. He is currently the chief data scientist and manager of Springfield Capital Management. He holds a PhD, MPhil, and BA from Oxford University and an MPhil from Cambridge University.

Igor Halperin
Igor Halperin Professor

Igor Halperin is Research Professor of Financial Machine Learning at NYU Tandon School of Engineering. Prevously, he was an Executive Director of Quantitative Research at JPMorgan, and before that he worked as a quantitative researcher at Bloomberg LP. Igor has published articles in finance and physics journals, is a speaker at financial conferences and has co-authored the book “Credit Risk Frontiers.”  Igor has a Ph.D. in theoretical high energy physics from Tel Aviv University, and a M.Sc. in nuclear physics from St. Petersburg State Technical University. He also advises fintech and data science start-ups and risk management firms.

Joshua Joseph
Joshua Joseph Professor

Josh Joseph is the Chief Intelligence Architect of the Bridge, the application arm of MIT's Quest for Intelligence Initiative. Previously, Josh was the Chief Science Officer of Alpha Features, an alternative data distribution platform, and co-founded a proprietary trading company based on machine learning driven strategy discovery and fully autonomous trading. Additionally, he has done a variety of consulting work across finance, life sciences, and robotics. He has a Ph.D. in Aeronautics and Astronautics from MIT where his research focused on methods for learning models of complex systems for decision making. 

Mickey Atwal
Mickey Atwal Professor

Mickey Atwal is an associate professor at Cold Spring Harbor Laboratory where he undertakes machine learning research and builds tools to analyze vast datasets in cancer genomics and immunology. He was awarded the Winship Herr Award for Excellence in Teaching a record three times, developing courses at the interface of machine learning, molecular biology, and neuroscience. He has trained in theoretical physics from the University of Cambridge, Cornell University, and Princeton University.

Larry Rudolph
Larry Rudolph Researcher

Larry Rudolph is a researcher at the MIT Computer Science and Artificial Intelligence Laboratory. He received his PhD in Computer Science in 1981 from the Courant Institute at NYU. Larry was on the faculty at University of Toronto, Carnegie-Mellon University, and The Hebrew University, before joining MIT as a principal research scientist, in 1995. In 1978, he helped start the Ultracomputer, a high performance parallel computer architecture, many ideas of which can be found in current multi-core computer chips.  Larry is currently a Vice President (Member of Labs) at Two Sigma Investments.

Michael Oliver Weinberg
Michael Oliver Weinberg Co - Founder and Chief Executive Officer

Michael has 25 years of experience investing directly at the security level and indirectly as an asset allocator in traditional and alternative assets.   He is the Chief Investment Officer, and a Senior Managing Director of MOV37 and Protégé Partners.  His portfolio management experience includes Soros Fund Management LLC, Credit Suisse First Boston, and Financial Risk Management (FRM).

Michael is a published author and keynote speaker at conferences and universities.  He received an M.B.A. from Columbia Business School, where he is now also an Adjunct Professor of Finance and Economics, and a B.S. in Economics from New York University.

Miquel Noguer i Alonso
Miquel Noguer i Alonso Co - Founder and Chief Science Officer

Miquel Noguer is a financial markets practitioner with more than 20 years of experience in asset management, he is currently Head of Development at Global AI ( Big Data Artificial Intelligence in Finance company ) and Head on Innovation and Technology at IEF.

He worked for UBS AG (Switzerland) as Executive Director.for the last 10 years. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006.

He is professor of Big Data in Finance at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain).

Scientific advisors

Gordon Ritter
Gordon Ritter Scientific Advisor

Gordon Ritter completed his Ph.D. in mathematical physics at Harvard University in 2007, where he published in top international journals.  Prior to that he earned his Bachelor's degree from the University of Chicago. Gordon is currently a senior portfolio manager at GSA.  Prior to joining GSA, Gordon was a Vice President of Highbridge Capital Management and a core member of the firm's statistical arbitrage group.  Concurrently with his positions in industry, Gordon teaches at three of the nation's leading MFE programs, including Baruch College and NYU.  He has published articles, and is a speaker at the top industry conferences.

Petter Kolm
Petter Kolm Scientific advisor and Professor

Petter Kolm is a Clinical Professor and the Director of the Mathematics in Finance Master’s Program at Courant Institute of Mathematical Sciences, NYU. Previously, Petter worked in the Quantitative Strategies Group at Goldman Sachs Asset Management.  Petter has coauthored numerous academic articles and four books. He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich.  Petter is also on various Board of Directors, editorial and advisory boards.