MAFN Faculty
MBA, Analytic Finance, University of Chicago, 1998
Multi-Asset Portfolio Management
Irina Bogacheva is Director of Research at Millburn Ridgefield and Adjunct Professor within the Department of Mathematics.
Previously, she held senior research positions with Goldman Sachs, Deutsche Asset Management, QS Investors, and Franklin Templeton. Irina’s 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’s 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.
Adjunct Professor, Department of Mathematics
MS, Columbia University
Quantitative Methods in Investment Management
Alberto Botter is a Managing Director within the Portfolio Management department at AQR Capital Management. In this role, he oversees the construction, optimization, and management of AQR’s Equities Long-Short and Tax-Managed portfolios. Prior to AQR, Mr. Botter was a quant in the Wealth Strategies Group at Morgan Stanley. Alberto earned a B.S. and an M.S. in economics from the University of Bologna and an M.A. in Mathematics of Finance from Columbia University.
Adjunct Professor, Department of Mathematics
Ph.D., International School for Advanced Studies
Credit Models, Computational Finance, and Machine Learning
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.
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).
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.
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.
PhD, Princeton University, 1995
Statistical and High-Frequency Trading, Drawdown Risk Measures, Portfolio Optimization
Alexei Chekhlov is an Adjunct Assistant Professor within the Department of Mathematics. He has previously taught graduate courses such as “Mathematical Methods in Financial Price Analysis” and “Capital Markets and Investments.” 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.
Assistant Professor, Department of Statistics
PhD, Princeton University
Statistical Inference / Time-Series Modelling
Gökçe Dayanıklı is an assistant professor in the Department of Statistics. Her research interests include mean field game and control applications, contract theory, and innovative machine learning approaches to solve these problems. She earned her Ph.D. in Operations Research & Financial Engineering from Princeton University where she was given the School of Engineering and Applied Science Award for Excellence.
gd2640@columbia.edu
Adjunct Professor, Department of Mathematics
PhD, Columbia University, 1996
Numerical Methods in Finance and Risk Model Methodologies
Tat Sang Fung is an Adjunct Professor at Columbia University, and he currently teaches “Numerical Methods in Finances,” 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.
fts@math.columbia.edu | 212-854-5880 | Website
PhD, Columbia University, 1980
Probability, Stochastic Control, Mathematical Economics, and Finance
Ioannis Karatzas is the Eugene Higgins Professor of Applied Probability in Columbia’s 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 “Applied Mathematics & Optimization,” “Stochastics,” the “SIAM Journal on Mathematical Analysis,” and the “SIAM Journal on Control & Optimization.” 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’s program.
Adjunct Professor, Department of Mathematics
PhD, University of Waterloo, 1995
Credit analytics, Risk Management, FinTech
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.
David has a PhD degree in statistics from the University of Waterloo, Master’s degrees in economics, finance and actuarial science, and a bachelor’s 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.
Adjunct Professor, Department of Mathematics
PhD, Columbia University, 2011
Equity Derivatives Trading
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.
Amal has a Ph.D. in Statistics, obtained with distinction, from Columbia University. Her thesis “Contagion and Systemic Risk in Financial Networks” 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 Télécom Paris.
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.
Adjunct Assistant Professor, Department of Mathematics
PhD, Columbia University, 1996
Derivatives and Structured Products Development
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.
Director of the Mathematics of Finance MA program
PhD, Harvard University, 1985
Lars Tyge Nielsen is the Director of the Mathematics of Finance MA (MAFN) program. He was a Chaired Professor, Associate Dean, and Director of the PhD program at INSEAD, the international business school in Fontainebleau, France and Singapore and now Abu Dhabi. He has held academic appointments at Nankai University, China (Chair Professor), NYU, UT Austin, Copenhagen Business School and the University of Copenhagen. Dr. Nielsen spent 13 years on Wall Street as an executive at various institutions including Morgan Stanley and Goldman Sachs.
ltn@math.columbia.edu | 212-854-4306 | Website
Adjunct Professor, Department of Mathematics
PhD, University of Kentucky, 1983
Multi-Asset Portfolio Management
Colm O’Cinneide 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.
MBA, Finance, University of Chicago, 1999
Multi-Asset Portfolio Management
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).
PhD, University of Brescia, 2000
Fixed Income Portfolio Management
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’s Mathematics of Finance program in 1998 as one of the program’s first classes.
Adjunct Assistant Professor, Department of Statistics
PhD, University of Oxford, 2016
Applied Probability Theory & Statistics
fhr2111@columbia.edu
PhD, Harvard University
Machine Learning for Finance
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’ 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 @ Université Paris Dauphine – 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.
wgr2107@columbia.edu
Adjunct Assistant Professor, Department of Mathematics
MBA, Columbia Business School
Machine Learning for Finance
Renzo Silva is an Adjunct Assistant Professor in the Department of Mathematics. In addition to his teaching position, Mr. Silva has extensive professional experience in the Financial Technology industry, and he currently serves as a Software Engineering Manager at Google. Previous experiences include Software Development Manager at Amazon, CTO at P1 Capital, and Managing Director at the New York Stock Exchange. Mr. Silva is a graduate of Columbia University’s Mathematics of Finance MA program, and he also holds an MBA in Finance and Economics from Columbia Business School. His research interests include Artificial Intelligence and Machine Learning, Optimization, Simulation, and Quantum Computing.
PhD, Princeton University, 1995
Quantitative Portfolio Management, Quantitative Investment Strategies, Risk Measurement, and Management
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.
smirnov@math.columbia.edu | 212-854-6955 | Website
PhD, University of California, Berkeley, 1991
Quantitative Modeling, Risk Analytics, Derivatives Pricing, Stochastic Processes, Numerical Methods
Dr. Harvey J. Stein left Bloomberg in March 2022 after a distinguished 28 3/4 year career where he built quant and engineering teams and introduced a variety of innovations in option pricing, computation and risk analysis. Dr. Stein 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 an organizer of the IAQF/Thalesians financial seminar series. He’s also worked as a quant researcher on the Bloomberg for President campaign. He received his BA in mathematics from WPI in 1982 and his PhD in mathematics from UC Berkeley in 1991. He recently started a new position as Senior VP, Quant Research at Two Sigma.
PhD, Princeton University
Price Impact Models and Applications to Quantitative Trading
Kevin Webster graduated with a Ph.D. from Princeton University Operations Research and Financial Engineering Department (ORFE). At ORFE, he studied mathematical models applied to high-frequency trading, emphasizing price impact and market making. He previously worked at Deutsche Bank and Citadel.
Kevin Webster created and taught a course, ORF 474 High-Frequency Markets: Models and Data Analysis, as a visiting lecturer at Princeton in the 2015 school year. His publications include “The self-financing equation in high frequency markets,” “Information and inventories in high frequency trading,” “A portfolio manager’s guidebook to trade execution,” and “High frequency market making.”
PhD, Oxford University, 2020
Robust approach to quantitative finance, optimal transport of stochastic processes, (robust) statistics, machine learning
Johannes Wiesel is an Assistant Professor in the Department of Statistics with affiliation with the Data Science Institute. Wiesel’s research interests include mathematical statistics, specializing in statistical optimal transport, and the robust approach to quantitative finance. Additionally, he serves as an editorial advisory board member for “Dependence Modeling,” an academic journal on multivariate dependence modeling. Wiesel earned his Ph.D. in Mathematics from the University of Oxford.
Adjunct Professor, Department of Mathematics
AB/SM, Harvard University, 1998
Quantitative Investment Strategies
Eric Yeh is an Adjunct Professor in the Department of Mathematics, specializing in Quantitative Investment Strategies. Yeh’s 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.