{"id":7093,"date":"2022-03-02T11:56:13","date_gmt":"2022-03-02T15:56:13","guid":{"rendered":"https:\/\/www.math.columbia.edu\/mafn\/dev\/?page_id=7093"},"modified":"2026-01-30T16:08:43","modified_gmt":"2026-01-30T20:08:43","slug":"mafn-faculty","status":"publish","type":"page","link":"https:\/\/www.math.columbia.edu\/mafn\/mafn-faculty\/","title":{"rendered":"MAFN Faculty"},"content":{"rendered":"

MAFN Faculty
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<\/i><\/i><\/span>Graeme S. Baker<\/span><\/a><\/h4><\/div>
Assistant Professor, Department of Statistics<\/span>
Ph.D., Princeton University, 2023
Stochastic Processes – Applications I<\/p>\n
Graeme Baker is an Assistant Professor with the Department of Statistics, and his research interests are in probability theory, partial differential equations, and applications of these fields. His recent work focuses on interacting particle systems which arise when modelling systemic risk in the context of interconnected financial networks. He completed his Ph. D. in Applied and Computational Mathematics at Princeton University in 2023.<\/p>\n<\/div>\n
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g.baker@columbia.edu<\/a> |<\/span> Website
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<\/i><\/i><\/span>Irina Bogacheva<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department of Mathematics<\/span>
\nMBA, Analytic Finance, University of Chicago, 1998
\nMulti-Asset Portfolio Management<\/p>\n

Irina Bogacheva is Director of Research at Millburn Ridgefield and Adjunct Professor within the Department of Mathematics.<\/p>\n

Previously, she held senior research positions with Goldman Sachs, Deutsche Asset Management, QS Investors, and Franklin Templeton. Irina\u2019s professional experience includes research and implementation of systematic global macro strategies, strategic and dynamic asset allocation, and active factor equity strategies. She holds Diploma in Mathematics from Moscow State University, Master\u2019s in Economics from New Economic School (Moscow), and an MBA in Analytic Finance from the University of Chicago Booth School of Business, where she also completed Ph.D. coursework in Finance.<\/p>\n

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<\/i><\/i><\/span>GREG BOROVYKH<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department of Mathematics<\/span>
MA, Mathematics of Finance, Columbia University, 2012
\nIntroduction to Quantitative Balance Sheet Strategy (QBSS) for Commercial Banks<\/p>\n

Greg Borovykh is a Managing Director at JPMorganChase’s Treasury and Chief Investment Office (TCIO). In this role, he leads a research team responsible for quantitative risk and resource allocation which includes investment portfolio strategy, balance sheet optimization and banking industry surveillance. <\/p>\n

Greg is CFA charterholder; he earned BBA in Accounting and Economics from Baruch College and MA in Mathematics of Finance from Columbia University.<\/p>\n

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<\/i><\/i><\/span>Alberto Botter<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
MS, Columbia University
Quantitative Methods in Investment Management<\/p>\n

Alberto Botter is a Partner at AQR Capital Management. In this role, Alberto is responsible for overseeing the daily management of equity long-short and tax-aware products, with a particular focus on portfolio management, portfolio construction and risk management. Furthermore, as a leader of the portfolio implementation department, he is responsible for driving initiatives to continuously enhance the firm\u2019s investment process and analytical capabilities. In addition to his work at AQR, Alberto serves as an Adjust Professor at Columbia University where he teaches quantitative methods in investment management. He has also previously taught at New York University and delivered guest lectures and seminars at numerous academic institutions. Before joining AQR, Alberto was a quant associate in the Wealth Strategies Group at Morgan Stanley. He holds a B.S. and M.S. in Economics from the University of Bologna and an M.A. in Mathematics of Finance from Columbia University.<\/p>\n

alberto.botter@columbia.edu <\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Luca Capriotti<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
Ph.D., International School for Advanced Studies
Credit Models, Computational Finance, and Machine Learning<\/p>\n

Luca is the Global Head of Quantitative Strategies (QS) Credit at Credit Suisse, where he has worked since 2004. Previous to this role, he was the global head of QS for Credit and Structured Notes; he was the EMEA head and the US head of QS Global Credit Products; he worked in Commodities in New York and London, and he was part of the cross-asset modeling R&D group of QS in the London office.<\/p>\n

Luca is also Visiting Professor at the Department of Mathematics at University College London, and an Adjunct Professor at Columbia University. His current research interests are in Credit Models, Computational Finance, and Machine Learning, with a focus on efficient numerical techniques for Derivatives Pricing and Risk Management, and applications of Adjoint Algorithmic Differentiation (AAD), which he has pioneered in Finance and Physics, and for which he holds a US Patent. Luca has published over 70 scientific papers, with the top 3 papers collecting to date over 1000 citations (h factor 27, i10 factor 49).<\/p>\n

Prior to working in Finance, Luca was a researcher at the Kavli Institute for Theoretical Physics, Santa Barbara, California, working in High-Temperature Superconductivity and Quantum Monte Carlo methods for Condensed Matter systems. He has been awarded the Director’s fellowship at Los Alamos National Laboratory, and the Wigner Fellowship at Oak Ridge National Laboratory.<\/p>\n

Luca holds an M.S. cum laude in Physics from the University of Florence, and an M.Phil. and a Ph.D. cum laude in Condensed Matter Theory, from the International School for Advanced Studies, Trieste.<\/p>\n

lc3635@columbia.edu<\/a><\/p>\n<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Alexei Chekhlov<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department of Mathematics<\/span>
\nPhD, Princeton University, 1995<\/p>\n

Capital Markets and Investments, Math Methods in Financial Price Analysis<\/p>\n<\/p>\n

Alexei Chekhlov is an Adjunct Assistant Professor within the Department of Mathematics. He has previously taught graduate courses such as \u201cMathematical Methods in Financial Price Analysis\u201d and \u201cCapital Markets and Investments.\u201d Additionally, Chekhlov serves as the Head of Research and Partner at Systematic Alpha Management, LLC, and he previously worked as a research associate at Princeton University, where he conducted research on the theory of fluid turbulence. He has published repeatedly on fluid mechanics, the kinetic theory of gases, turbulence, and within the fields of applied mathematics and quantitative finance. Chekhlov earned his Ph.D. in Applied and Computational Mathematics from Princeton University.<\/p>\n

ac3085@columbia.edu<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Jaehyuk Choi<\/span><\/a><\/h4><\/div>
MAFN Program Director, Department of Mathematics<\/span>
\nPhD, Massachusetts Institute of Technology<\/p>\n

Math Finance Practitioners Seminar<\/p>\n<\/p>\n

Jaehyuk Choi is the MAFN program director. He was an Associate Professor at Peking University HSBC Business School before joining Columbia in 2025. Prior to his academic career, he spent nine years as a fixed-income quant at Goldman Sachs in New York and Hong Kong. Jaehyuk is also a co-founder and academic advisor to quants.net, a financial technology company. His research interests encompass mathematical finance, machine learning, and numerical methods. He holds a Ph.D. in Applied Mathematics from the Massachusetts Institute of Technology.<\/p>\n

jc6569<\/span>@columbia.edu<\/span><\/font><\/a><\/font><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Alberto Gonzalez Sanz<\/span><\/a><\/h4><\/div>
Assistant Professor, Department of Statistics<\/span>
\nPhD, University of Valladolid (Spain) and the University of Toulouse III (France), 2023<\/p>\n

Statistical Inference \/ Time-Series Modelling<\/p>\n<\/p>\n

Alberto Gonz\u00e1lez Sanz is an Assistant Professor in the Department of Statistics, with research interests in optimal transport, statistics, artificial intelligence, probability theory, and partial differential equations. He completed his PhD through a cotutelle program between the University of Valladolid (Spain) and the University of Toulouse III (France) in 2023.<\/p>\n

ag4855@columbia.edu<\/span><\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Paul-Guillaume Fourni\u00e9<\/span><\/a><\/h4><\/div>
Adjunct Assistant Professor<\/span>, Department of Mathematics<\/span><\/p>\n

MSc, Ecole Polytechnique, 2015
MSc, Corps des Mines, 2018<\/p>\n

Interest Rates Models<\/p>\n<\/p>\n

Paul-Guillaume Fourni\u00e9 has been working as an Options Rates Quant at BNP Paribas\u2019 New York office since 2019, heading the team locally since 2022. Covering both Vanilla and Exotic options, his most recent focus has been on the creation and adaptation of interest rates models to SOFR. He holds MSc in Mathematics and Physics from Ecole Polytechnique and MSc in Economics and Public Policy from Corps des Mines. Before switching to finance he occupied several positions in leading French industrial and telecommunications companies and served in France\u2019s Ministry of the Economy. <\/p>\n

pf2474@columbia.edu<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Tat Sang Fung<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
PhD, Columbia University, 1996
Numerical Methods in Finance and Risk Model Methodologies<\/p>\n

Tat Sang Fung is an Adjunct Professor at Columbia University, and he currently teaches \u201cNumerical Methods in Finances,\u201d a graduate course required for students in the Mathematics of Finance program. His areas of expertise include Quantitative Finance and Risk Management Methodology, and Mathematics. Additionally, Fung serves as the Global Head of Risk Model Methodology at Jefferies and has held other senior positions in the finance industry at Finch Lead Inc. and Finastra. Fung earned his Ph.D. in Mathematics from Columbia University.<\/p>\n

fts@math.columbia.edu<\/span> <\/a>| 212-854-5880 | <\/span>Website<\/a><\/span><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Julien guyon<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics
<\/span>PhD, \u00c9cole des ponts ParisTech, 2006
Nonlinear Option Pricing<\/p>\n

Julien Guyon is a professor of Applied Mathematics at Ecole des Ponts ParisTech, one of the oldest and one of the most prestigious French Grandes Ecoles, where he holds the BNP Paribas Chair Futures of Quantitative Finance. Before joining Ecole des Ponts, Julien worked in the financial industry for 16 years, first in the Global Markets Quantitative Research team at Societe Generale in Paris (2006-2012), then as a senior quantitative analyst in the Quantitative Research group at Bloomberg L.P., New York (2012-2022). Julien was also an adjunct professor in the Department of Mathematics at Columbia University and at the Courant Institute of Mathematical Sciences, NYU, from 2015 to 2022; and previously at Universite Paris Diderot and Ecole des Ponts ParisTech. Julien serves as an Associate Editor of Finance & Stochastics, SIAM Journal on Financial Mathematics, Quantitative Finance, and Journal of Dynamics and Games. He is also a Louis Bachelier Fellow.<\/p>\n

Julien co-authored the book Nonlinear Option Pricing (Chapman & Hall, 2014) with Pierre Henry-Labordere. He has published more than 20 articles in peer-reviewed journals (including Finance and Stochastics, SIAM Journal on Financial Mathematics, Quantitative Finance, Risk, Journal of Computational Finance, Annals of Applied Probability, Stochastic Processes and their Applications) and is a regular speaker at international conferences, both academic and professional. His main research interests include volatility and correlation modeling, option pricing, optimal transport, and numerical probabilistic methods.<\/p>\n

A big soccer fan, Julien has also published articles on fairness in sports both in academic journals and in top-tier newspapers including The New York Times, The Times, Le Monde, and El Pais. Some of his suggestions for draws and tournament design have been adopted by FIFA and UEFA, including a new, fairer draw method for the FIFA World Cup; a fairer format for the 2026 FIFA World Cup (in progress); a new knockout bracket for the UEFA Euro; and an optimized schedule of the UEFA Champions League. His paper “Risk of collusion: Will groups of 3 ruin the FIFA World Cup?” won the 2nd prize at the 2021 MIT Sloan Sports Analytics Conference, the biggest sports analytics event in the world.<\/p>\n<\/p>\n

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<\/i><\/i><\/span>Ioannis Karatzas<\/span><\/a><\/h4><\/div>
Eugene Higgins Professor of Applied Probability, Department of Mathematics<\/span>
\nPhD, Columbia University, 1980
\nProbability, Stochastic Control, Mathematical Economics, and Finance<\/p>\n

Ioannis Karatzas is the Eugene Higgins Professor of Applied Probability in Columbia\u2019s Department of Mathematics, whose research interests include Probability and Mathematical Statistics, Random Processes, Stochastic Analysis, Optimization, and Mathematical Economics and Finance. He has served as the managing editor for the book series Applications of Mathematics and on numerous editorial boards such as \u201cApplied Mathematics & Optimization,\u201d \u201cStochastics,\u201d the \u201cSIAM Journal on Mathematical Analysis,\u201d and the \u201cSIAM Journal on Control & Optimization.\u201d His book with Steven Shreve, Brownian Motion and Stochastic Calculus, first published in 1987, is the standard reference within the field of Stochastic Analysis. Karatzas earned his Ph.D. from Columbia University and helped build and establish this Mathematics of Finance Master\u2019s program.<\/p>\n

ik1@columbia.edu<\/a> | <\/span>Website<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Laura Leal<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department of Mathematics<\/span>
\nPhD, Princeton University
A Mathematical Approach to Generative AI<\/p>\n

Dr. Laura Leal is Vice President at Goldman Sachs, on the AI Strats team. Prior to that, she was on GSAM's Quantitative Investment Strategies team, working on Systematic Trading. In addition to her industry work, Laura is an Adjunct Professor at Columbia University, where she teaches the Mathematics of Generative AI. <\/p>\n

Laura has a PhD in Operations Research and Financial Engineering from Princeton University. During her time in Princeton, Laura was awarded the School of Engineering and Applied Science Award for Excellence, the Princeton Teaching Award, and the prestigious Gordon Wu Fellowship. At Goldman Sachs, she won the extremely competitive GS Global Engineering Hackathon. <\/p>\n

ls4329@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>David X. Li<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
PhD, University of Waterloo, 1995
Credit analytics, Risk Management, FinTech <\/p>\n

David X. Li currently teaches at Shanghai Advanced Institute of Finance, Shanghai Jiaotong University. Previously, he held senior positions at various leading financial institutions for more than two decades in the areas of new product development, risk management, asset\/liability management and investment analytics. <\/p>\n

David has a PhD degree in statistics from the University of Waterloo, Master\u2019s degrees in economics, finance and actuarial science, and a bachelor\u2019s degree in mathematics. Dr. Li was one of the early practitioners in credit derivatives. His work of using copula functions for credit portfolio modeling has been widely cited by academic researchers, broadly used by practitioners for credit portfolio trading, credit risk management and credit rating, and well covered by media such as Wall Street Journal, Financial Times, Nikkei, CBC News.<\/p>\n

dl3054@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Bryan Liang<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
PhD, University of Michigan, 2002
Non-Linear Option Pricing <\/p>\n

Bryan Liang is an Adjunct Assistant Professor in the Department of Mathematics, specializing in Derivatives Modelling. Additionally, Liang has extensive experience as a quantitative analyst in the finance industry, currently working as a Quantitative Researcher in the Quantitative Financial Research Group for Bloomberg. Liang earned his Ph.D. in Mathematics from the University of Michigan.<\/p>\n

jl4916@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Amal Moussa<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
PhD, Columbia University, 2011
Modeling and Trading Derivatives<\/p>\n

Dr. Amal Moussa is a Managing Director at Goldman Sachs, where she leads the Single Stocks Exotic Derivatives Trading desk. Prior to that, Amal held senior-level positions in equity derivatives trading at other leading financial institutions such as J.P. Morgan, UBS, and Citigroup. In addition to her work in Markets, Amal is an Adjunct Professor at Columbia University, where she teaches a graduate course on Modeling and Trading Derivatives in the Mathematics of Finance Masters program.<\/p>\n

Amal has a Ph.D. in Statistics, obtained with distinction, from Columbia University. Her thesis \u201cContagion and Systemic Risk in Financial Networks\u201d shed light on the importance of the network structure in identifying systemic financial institutions and formulating regulatory policies and has been cited by several scholars and industry professionals, including former Federal Reserve president Janet Yellen. She was also awarded the Minghui Yu Teaching Award at Columbia University. Prior to her Ph.D., Amal graduated with a Masters in Mathematical Finance from Sorbonne University (former Paris VI) and a Grande Ecole engineering degree from T\u00e9l\u00e9com Paris.<\/p>\n

Amal is a board member of Teach for Lebanon, an NGO working to ensure that all children in Lebanon have access to education regardless of socioeconomic background, and she is an active member of the Women in Trading network at Goldman Sachs.<\/p>\n

am2810@columbia.edu<\/span><\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Ka Yi Ng<\/span><\/a><\/h4><\/div>
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Adjunct Assistant Professor, Department of Mathematics<\/span>
PhD, Columbia University, 1996
Programming for Quantitative & Computational Finance<\/p>\n

Ka Yi Ng is an Adjunct Assistant Professor in the Department of Mathematics with extensive quantitative experience in FinTech. Currently, Ng works at Calypso Technology Inc. and serves as an advisor at Finch Lead Inc. Ng previously worked at Wall Street Systems and ION. At Columbia, her interests include Derivatives and Structured Products Development, and Machine Learning. Ng earned her Ph.D. in Mathematics from Columbia University.<\/p>\n

kyn@math.columbia.edu<\/a> | <\/span>Website<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Colm O\u2019Cinneide<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span>
PhD, University of Kentucky, 1983
Multi-Asset Portfolio Management<\/p>\n

Colm O\u2019Cinneide is an adjunct professor in the Department of Mathematics. He has worked in quantitative asset allocation and portfolio construction roles for the past 20 years at Deutsche Asset Management, QS Investors, and Franklin Templeton Investments, where he is currently an SVP. He was a partner at QS investors. Prior to this, he worked in academia from 1982 to 2000 and held tenured positions in Mathematical Sciences (Statistics) at the University of Arkansas and Industrial Engineering (Operations Research) at Purdue University. He has 40+ refereed publications related to probability, statistics, numerical analysis, and finance, with 1300+ citations and a track record of National Science Foundation funding. He has a PhD in Statistics from the University of Kentucky.<\/p>\n

cao2107@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Inna Okounkova<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department of Mathematics<\/span>
\nMBA, Finance, University of Chicago, 1999
\nMulti-Asset Portfolio Management<\/p>\n

Editor-in-Chief of the Journal of Investment Consulting, Wealth Management eJournal, and Wealth Management Editor's Choice eJournal; formerly Director of Investment Strategy at AB Bernstein; prior to that head of Strategic Asset Allocation Portfolio Management and partner at QS Investors, LLC and head of Strategic Asset Allocation Portfolio Management at Deutsche Asset Management; Past President and Director of the Honorary Board of the Society of Quantitative Analysts; MS in Mathematical Economics and ABD from Moscow State University; MBA from the University of Chicago (1999).<\/p>\n

io2173@columbia.edu<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Rosanna Pezzo-Brizio<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department<\/span> of Mathematics<\/span>
\nPhD, University of Brescia, 2000
\nFixed Income Portfolio Management<\/p>\n

Rosanna Pezzo-Brizio is an Adjunct Professor in the Department of Mathematics, specializing in Fixed Income Portfolio Management. Pezzo-Brizio has a vast array of professional, senior experience, working at Goldman Sachs, Greenwich Capital Markets, Intesa Sanpaolo. Currently, she is the Director of the Investment Consulting Group at New York Life Investments. Pezzo-Brizio holds a Ph.D. in Mathematics of Finance from the University of Brescia. Additionally, she graduated from Columbia University\u2019s Mathematics of Finance program in 1998 as one of the program\u2019s first classes.<\/p>\n

rp279@columbia.edu<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Franz Rembart<\/span><\/a><\/h4><\/div>
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Adjunct Assistant Professor, Department of Statistics<\/span>
PhD, University of Oxford, 2016
Statistical Inference \/ Time-Series Modelling<\/p>\n<\/p>\n

Franz Rembart is a Principal at Boston Consulting Group (BCG), where he focuses on digitization and data science topics in Financial Services & Insurance, and the Public\/Social Impact Sector. His academic research interests include random tree growth processes, operations on continuum random trees and related fields. An illustrative example of his work would be \u201cRecursive construction of continuum random trees,\u201d with Matthias Winkel, The Annals of Probability 2018\/19. Professor Rembart received his PhD in Applied Probability Theory & Statistics from the University of Oxford in 2016. During his studies, he was a Stipendiary Lecturer at the renowned Christ Church, Oxford. He holds a Masters\u2019 degree in Mathematical Finance and Actuarial Science and a Bachelor\u2019s degree in Mathematics (both with a minor in Economics) from the Technical University Munich. <\/div>\n
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fhr2111@columbia.edu<\/p>\n<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Gordon Ritter<\/span><\/a><\/h4><\/div>
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Adjunct Professor, Department of Mathematics<\/span><\/div>\n
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PhD, Harvard University<\/span>
Machine Learning for Finance <\/span>
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Professor Ritter is founder and CIO of Ritter Alpha LP, a registered investment adviser running systematic absolute-return trading strategies across multiple asset classes and geographical regions. Before Ritter Alpha, he was a senior portfolio manager at GSA Capital and a Vice President in the Statistical Arbitrage Group at Highbridge Capital Management (HCM). Gordon completed his PhD in mathematical physics at Harvard University and his Bachelors\u2019 degree with honors in Mathematics from the University of Chicago. While at Harvard, he published several papers in the areas of quantum field theory, differential geometry, quantum computation and abstract algebra. His current research is on portfolio optimization and statistical machine learning. Notable publications include \"Optimal turnover, liquidity, and autocorrelation,\" with @Bastien Baldacci of @ Universit\u00e9 Paris Dauphine \u2013 PSL and @Jerome Benveniste of @New York University, Risk, 2022, and \"Machine learning for trading,\" Risk, 2017. In recognition of the latter publication, Professor Ritter was named Buy-Side Quant of the Year in 2019.<\/span><\/p>\n

wgr2107@columbia.edu<\/span><\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Renzo Silva<\/span><\/a><\/h4><\/div>
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Adjunct Assistant Professor, Department of Mathematics<\/span>
MBA, Columbia Business School
Machine Learning for Finance<\/p>\n

Renzo Silva is an Adjunct Assistant Professor in the Department of Mathematics. In addition to his teaching experience, Mr. Silva has extensive professional experience in the Technology and Financial industries, including technical leadership positions at Google, Amazon, P1 Capital, and the New York Stock Exchange. Mr. Silva is a graduate of Columbia University\u2019s Mathematics of Finance MA program, and he also holds an MBA in Finance & Economics from Columbia Business School, and an SM in Computational Science & Engineering from Harvard University. His research interests include mathematical and theoretical physics, and mathematical and AI methods for the sciences.<\/p>\n

rs333@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Iordan Slavov
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Adjunct Associate Professor, Department of Mathematics<\/span>
PhD, Sofia University
Stochastic Processes \u2013 Applications I<\/p>\n

Iordan Slavov is AI\/ML Technical Lead at JPMorgan Chase. Previously he has held analytical positions at Thomson Reuters, UnitedHealth Group and a few start-ups where he applied his expertise in Data Science, Machine Learning and Statistics. He has a PhD in Mathematics from Sofia University, Bulgaria and MA degrees in Statistics and Mathematics of Finance from Columbia University. He is also an Adjunct Associate Professor at CUNY where he teaches graduate classes in Statistics.<\/p>\n<\/p>\n

is385@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Mikhail Smirnov<\/span><\/a><\/h4><\/div>
Senior Lecturer in Discipline, Department of Mathematics<\/span>
\nPhD, Princeton University, 1995
Introduction to the Mathematics of Finance <\/p>\n

Mikhail Smirnov is a Senior Lecturer in Discipline in the Department of Mathematics and was Director of the Mathematics of Finance program in 1998-2012. His research interests include Quantitative Portfolio Management, Quantitative Investment Strategies, and Risk Measurement. He holds a Ph.D. from Princeton University.<\/p>\n

smirnov@math.columbia.edu<\/a> | 212-854-6955 | <\/span>Website<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

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<\/i><\/i><\/span>Harvey J. Stein<\/span><\/a><\/h4><\/div>
Adjunct Professor, Department of Mathematics<\/span>
\nPhD, University of California, Berkeley, 1991
Financial Risk Management and Regulation<\/p>\n

Harvey Stein is a senior VP in the Labs group in Two Sigma where he works on various research projects around the firm. From 1993 to 2022, Dr. Stein was at Bloomberg, where he served as the head of several departments including Quantitative Risk Analytics, Counterparty and Credit Risk, Interest Rates Derivatives, and Quantitative Finance R&D. Harvey is well known in the industry, having published and lectured on credit risk modeling, financial regulation, interest rate and FX modeling, CVA calculations, mortgage backed security valuation, COVID-19 data analysis, and other subjects. Dr. Stein is on the board of directors of the IAQF, a board member of the Rutgers University Mathematical Finance program, an adjunct professor at Columbia University, and organizer of the IAQF\/Thalesians financial seminar series. He's also worked as a quant researcher on the Bloomberg for President campaign. Harvey holds a Ph.D. in Mathematics from the University of California, Berkeley (1991) and a B.S. in Mathematics from Worcester Polytechnic Institute (1982).<\/p>\n

hjstein@columbia.edu<\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

<\/span><\/div><\/div><\/div>

<\/i><\/i><\/span>Yisha Yao<\/span><\/a><\/h4><\/div>
Assistant Professor, Department of Statistics<\/span><\/p>\n
\nPhD, Rutgers University, 2021<\/div>\n
\n

Statistical Interference\/ Time-Series Modeling<\/p>\n

Yisha Yao is an Assistant Professor with the Department of Statistics. Her research interests span a wide range of modern high-dimensional statistics, including but not limited to nonparametric methods, statistical inferences, mixture models, FDR control, iterative algorithms, tensor analysis, and applications in biomedical sciences. She obtained her PhD in statistics from Rutgers University (New Brunswick) in 2021, and then spent two years at Yale University as a postdoctoral researcher in biostatistics. <\/p>\n<\/div>\n

yy3381@columbia.edu <\/a>\n\t<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

<\/span><\/div><\/div><\/div>

<\/i><\/i><\/span>Eric Yeh<\/span><\/a><\/h4><\/div>
\n

Adjunct Professor, Department of Mathematics<\/span>
AB\/SM, Harvard University, 1998
Hedge Funds Strategies and Risk<\/p>\n

Eric Yeh is an Adjunct Professor in the Department of Mathematics, specializing in Quantitative Investment Strategies. Yeh\u2019s vast professional experience in the Finance industry includes senior positions at Morgan Stanley, Deutsche Bank, Tower Research Capital, and AllianceBernstein. Currently, he is President of Vermillion Leaf Capital LLC and an advisor to multiple investment managers, including the $100M hedge fund he previously co-founded. Yeh holds an AB in Mathematics and an SM in Computer Science from Harvard University.<\/p>\n

ey2237@columbia.edu<\/a><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"100-width.php","meta":{"footnotes":""},"class_list":["post-7093","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/pages\/7093","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/comments?post=7093"}],"version-history":[{"count":180,"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/pages\/7093\/revisions"}],"predecessor-version":[{"id":9510,"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/pages\/7093\/revisions\/9510"}],"wp:attachment":[{"href":"https:\/\/www.math.columbia.edu\/mafn\/wp-json\/wp\/v2\/media?parent=7093"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}