Name Bio Presentation
eric brinkman

Erik Brinkman

Ph.D.  University of Michigan

Erik Brinkman received his Ph.D. in Computer Science at the University of Michigan studying the behavior of financial markets using empirical game-theoretic analysis.  
 Peter Carr

Peter Carr

Finance and Risk Engineering Department Chair; Professor

NYU Tandon 

Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. He has headed various quant groups in the financial industry for the last twenty years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his Ph.D. from UCLA in 1989. He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and Financial Engineer of the Year by IAQF/Sungard in 2010. From 2011 to 2014, Dr. Carr was included in Institutional Investor's Tech 50, an annual listing of the 50 most influential people in financial technology.



German Creamer

German Creamer

Associate Professor, Stevens Institute of Technology

 Germán G. Creamer is an Associate Professor of quantitative finance and business analytics at Stevens Institute of Technology and an adjunct associate professor at Columbia University. Dr. Creamer has been a senior manager in the Risk, Information and Banking Division in American Express where he worked in the enterprise-wide risk management and the information management groups. He has been an economic advisor to the president of Ecuador and the government of Equatorial Guinnea, and has consulted for several hedge funds, fintech companies, and international organizations such as United Nations, World Bank, and US Agency for International Development. He has a Ph.D. in Computer Science (specialized in computational finance), an MSc in Financial Engineering, both from Columbia University and a Ph.D. in Economics from the University of Notre Dame. His articles have appeared in leading journals including Quantitative Finance, Computational Economics, Data Mining and Knowledge Discovery, IEEE Systems Journal, and Decision Support Systems. His research interests include portfolio optimization, algorithmic trading, risk management, and machine learning on finance. He is also a Chartered Financial Analyst (CFA).




Raphael Douadi

University of Paris I: Pantheon-Sorbonne

Raphael Douady is a French mathematician and economist specializing in data science, financial mathematics and chaos theory at the University of Paris I-Panthéon-Sorbonne. He formerly held the Frey Chair of quantitative finance at Stony Brook University and was academic director of the French Laboratory of Excellence on Financial Regulation. He earned his PhD in Hamiltonian dynamics and has more than 20 years of experience in the financial industry. He has particular interest in researching portfolio risks, for which he has developed especially suited powerful nonlinear statistical and data science models, as well as macroeconomics and systemic risk. He founded fin tech firms Riskdata (risk management for the buyside) and Datacore (quantitative portfolio of ETFs) and is Chief Science Officer of Matrics (AI for the buy-side). Douady is a member of the Praxis Club, a New York-based think tank advising the French government on its economic policy and sits on the board and the investment committee of Friends of IHES, a foundation supporting the Institut des Hautes Etudes Scientifiques (the French brother of Princeton IAS). He is an alumni of Ecole Normale Supérieure in Paris and was awarded a gold medal at the International Mathematical Olympiads.


Mohammad Fesanghary

Google Scholar link



Mohammad Fesanghary is a quant researcher with Bloomberg. He received his PhD in Mechanical Engineering from Louisiana State University. His current research interests include machine learning methods for investing using alternative & traditional data sources, and optimization.  

Paul Glasserman

Jack R. Anderson Professor of Business
Decision, Risk, and Operations

Research Director
Program for Financial Studies

Columbia University

Professor Glasserman's research and teaching address risk management, derivative securities, Monte Carlo simulation, statistics and operations. Prior to joining Columbia, Glasserman was with Bell Laboratories; he has also held visiting positions at Princeton University, NYU, and the Federal Reserve Bank of New York. In 2011-2012, he was on leave from Columbia and working at the Office of Financial Research in the U.S. Treasury Department, where he continues to serve as a part-time consultant.

Glasserman's publications include the book Monte Carlo Methods in Financial Engineering (Springer, 2004), which received the 2006 Lanchester Prize and the 2005 I-Sim Outstanding Publication Award. Glasserman is a past recipient of the National Young Investigator Award from the National Science Foundation (1994 - 99), IBM University Partnership Awards (1998 - 2001), the TIMS Outstanding Simulation Publication Award (1992), the Erlang Prize (1996), the IMS Medallion from the Institute of Mathematical Statistics (2006), and a fellowship from the FDIC Center for Financial Research (2004). He received the 2004 Wilmott Award for Cutting-Edge Research in Quantitative Finance and Risk Magazine's 2007 Quant of the Year Award, and he received a U.S. patent for an option pricing method. He was named an INFORMS Fellow in 2008. He is also a two-time recipient of the Dean's Award for Teaching Excellence (1994, 2000). Glasserman serves on the editorial boards of Finance & Stochastics, Mathematical Finance, the Journal of Derivatives, and Stochastic Systems.

Glasserman was senior vice dean of Columbia Business School in 2004-2008 and served as interim director of the Sanford C. Bernstein & Co. Center for Leadership and Ethics in 2005-2007. He currently serves as research director of the Program for Financial Studies.


Derek Hansen

University of Michigan

Derek Hansen is currently a Ph.D. student in Statistics at the University of Michigan, Ann Arbor supported by an NSF Graduate Research Fellowship (GRFP). He previously worked as a Senior Research Assistant in the Risk Analysis section at the Federal Reserve Board in Washington, DC, where he contributed to both research and policy work on systemic risk measures of the U.S. financial system, trading book stress testing, and bond-CDS liquidity co-movement. He also engaged with developing robust filtering techniques for improved stochastic volatility modeling, return density forecasting and extraction of inflation trends. His current research is focused on developing robust parametric and semi-parametric inference and prediction methods, particularly in time-series applications, while his other areas of interest include Bayesian model selection and averaging and extreme-value theory. He will be presenting the paper A Randomized Missing Data Approach to Robust Filtering with Applications to Economics and Finance.




Dror Kenett

Economist at Financial Industry Regulatory Authority (FINRA)

Washington, District Of Columbia

 Dror Y. Kennett (Financial Industry Regulatory Authority, USA) is currently an economist at  FINRA’s Office of the Chief Economist. For over a decade he has been performing data-driven quantitative research on financial economics, uncovering patterns, structure, dynamics, and sources of risk within and between different markets and sectors. He has been developing econometric and network-based models to quantify and monitor changes, threats, and vulnerabilities to the financial system. He has been studying cross border spillovers and vulnerabilities and has developed new models to account for spillover and contagion channels. Some of the projects he has worked on include developing models and tools to understand patterns of comovement in financial markets, model interconnectedness and transmission channels for cross-asset classes and cross border spillover and contagion effects, develop new stress test models, and new measures of liquidity in equity markets.  

Sebastian Jaimungal

Professor, University of Toronto

Prof. Jaimungal is the current director of the professional Masters of Financial Insurance Program and teaches in the Mathematical Finance Program and the PhD and MSc programs in the Department of Statistical Sciences. He is the current chair (former vice chair; former program director) for the SIAM activity group in Financial Mathematics and Engineering (SIAG/FM&E), a managing editor of quantitative finance, and an associate editor for the SIAM Journal on Financial Mathematics (SIFIN), among others. He is also a lab leader at Fields-CQAM and a founding board member of the Commodities and Energy Markets Association, currently serving on its advisory board.

His research interests lie in mathematical finance and ranges over a variety of topics in mean field games, algorithmic trading, machine learning, and commodities markets.


Baron Law

Agam Capital

Dr. Law is currently working for Agam Capital, responsible for the research and development of pricing and hedging models. Prior to Agam, he was a consultant in Deloitte Advisory engaging projects in market, credit, and operational risks with banking clients. Before that, Dr. Law was a vice president in the Quantitative and Derivative Strategies (QDS) of Morgan Stanley designing quantitative equity trading algorithms. While he was a member of Credit Suisse HOLT, he participated in the quantitative research of equity valuation methodologies. Dr. Law received his PhD from Purdue University and his research was focused on algorithmic market making. In addition, he is a CFA charterholder and certified Financial Risk Manager (FRM).  Download



Roger Lee

Associate Professor, University of Chicago

Roger Lee is Associate Professor of Mathematics at the University of Chicago. He also serves as an Associate Editor of Mathematical Finance and an Associate Editor of the SIAM Journal on Financial Mathematics. His research interests include robust pricing and hedging, implied volatility asymptotics, and volatility contracts. He has a Ph.D. from Stanford and a B.A. from Harvard.  

Vladimir Markov


Vladimir Markov

Quantitative Research, Bloomberg LP


Jerzy Pawlowski 2007 small

Jerzy Pawlowski

GitHub: Link

Jerzy Pawlowski is an adjunct professor in the Department of Finance and Risk Engineering at the NYU Tandon School of Engineering, where he teaches graduate courses in Applications of R in Finance, and Algorithmic Portfolio Management Using R.
Previously he was a portfolio manager at several hedge funds, including Millennium, Diamond Notch, and Mariner-Tricadia. He has a Ph.D. in physics from SUNY Buffalo.

Philip Protter

Professor, Columbia University

Professor Protter's primary research interests include mathematical finance (capital asset pricing theory, the pricing and hedging of derivatives, liquidity issues, financial bubbles, insider trading, high frequency trading, and credit risk), stochastic integration theory, stochastic differential equation theory, numerical solutions of stochastic differential equations, discretization of stochastic processes (as a branch of mathematical statistics), backward and forward-backwards stochastic differential equations, Markov process theory, and filtering theory. He has authored or co-authored two textbooks and two research books.

Professor Protter is a Fellow of the I.M.S., the Associate Editor of nine research journals and is on two editorial boards, and is the former editor-in-chief of Stochastic Processes and their Applications. In 2007 he was a Fulbright Distinguished Chair at the University of Paris (Dauphine), and he has given many invited special lectures, including the R. Von Mises Lecture, Humboldt University, Germany (Inaugural Lecture), June 7, 2007; the Bullitt Lecture, University of Louisville, KY, April 3, 2008; and Lundis de la Connaissance, Nice, France, July 6, 2009. He has been a visiting member of the Institute for Advanced Study, and he has been an invited visitor at many universities in the US and abroad. He has won two best teacher awards.

Professor Protter was an Assistant Professor at Duke University, a visiting member of the IAS in Princeton, a Professor at Purdue University, and a Professor at Cornell University before moving to Columbia University in 2011. He has been an invited short term visitor at the University of Wisconsin, the University of Paris, INRIA, and the Universities of Nice, Provence, Rennes, Rouen, Strasbourg, Marne-la-Valle, and Nancy in France; Perugia, Rome, and l'Aquila in Italy; the University of Bonn and Humboldt University in Germany, ETH in Zurich, the University of Warwick in England, and the University of Tokyo. He has also given short courses in Chile, Finland, Milan, New York, and Istanbul.


Shivaji Rao

Fair Value Partners

Shivaji Rao is the Founder and Chief Operating Officer of FVP Inc, he alongside Dr. Raphael Douady directed a team of quant developers from Stevens Institute of Technology/Stony Brook University to implement a trading application prototype for the family office of Bruce Flatt. The mathematical models were co-written by the co-CEOs’ (Dr. Raphael Douady and Dr. Shivaji Rao) while the trading application prototype was written by Mr. Saleem Huda of Brookfield Asset Management. In addition, Dr. Shivaji Rao's Quantitative Trading experience includes risk management, quantitative modeling, structuring and trading. Relationships include analyst community, public sector organizations, bank proprietary trading desks, and hedge fund managers. Products include cash, futures, derivatives, Fixed Income, Foreign Exchange, Algorithmic Trading & e-commerce. Previously responsible for the Valuation and the Disposition of Fixed Income instruments for MF Global and the Wells Fargo / Wachovia Asset Distribution.  Download
JSR Photo

John Roberts

Office of the Chief Economist

U.S. Commodity Futures Trading Commission

John S. Roberts received his Ph.D. at the University of Maryland, College Park and is researcher in the Office of the Chief Economist at the U.S. Commodity Futures Trading Commission. His research focuses on automated trading, the role of market makers and liquidity provision, and the dynamics of the electronic limit order book using market depth data.  Download

 Jack Sarkissian

Managing Director, Algostox Trading

Dr. Jack Sarkissian is the Managing Director of Algostox Trading overseeing quantitative trading and analytics. He was the Chief Investment Officer for EG Capital Partners and Sever Asset Management managing $3 bln. in assets. Prior to asset management career he held senior banking roles in risk management and quantitative analytics.

Jack holds a Ph.D. in Physics and promotes the application of theoretical physics to reveal fundamental properties of financial markets. His research focuses on practical aspects of trading and includes order book dynamics, pricing, and execution of large orders, risk assessment of illiquid securities, OTC derivatives pricing, ergodic properties of financial markets, transitional effects and stabilization in financial markets. Jack is the author of the quantum theory of price formation, which describes price dynamics as a quantum-chaotic process.


Alexander Shklyarevsky

Solutions Architect/Evaluserve Consultant, Mizuho

 Alexander Shklyarevsky is a Solutions Architect / Consultant from Evalueserve in Risk Analytics and Model Risk at Mizuho Bank in New York. He specializes in quantitative pricing and risk models and other methodologies and processes for Capital, Credit Risk. Collateral Modeling, Insurance Products, Derivative Securities and their portfolios across asset classes. Prior to starting at Mizuho, Alexander worked at State Street, AIG, Bank of America, KBC Financial Products, Commerzbank, Merrill Lynch, ING Barings, Deutsche Bank, Bank of Tokyo and Chase Manhattan Bank where he specialized in quantitative pricing, trading and risk models for derivative securities and their portfolios, as well as Risk Management and Risk Analytics. Mr. Shklyarevsky has been published in financial magazines and has been a speaker at multiple industry and academic conferences. Prior to working in an Insurance Industry and a Financial Industry, he worked in Construction Research, Market Research and Academia where he conducted Mathematical Research and taught courses in Mathematics. Mr. Shklyarevsky holds a B.S. / M.S. Degree in Mathematics from Kiev State University (Department of Mathematics) and M.S. Degree with all Ph.D. credits in Mathematics from New York University (Courant Institute of Mathematical Sciences, Department of Mathematics).  
Majeed Simaan

Majeed Simaan

Asistant Professor 

Stevens Institute of Technology

 Majeed Simaan is a tenure-track assistant professor of Finance at Stevens Institute of Technology (SIT). He holds a Ph.D. in Finance from Rensselaer Polytechnic Institute (RPI). His research interests revolve around Banking and Risk Management, with emphasis on asset allocation and pricing. He is well versed in quantitative and computational finance-related research areas, such as financial networks (interconnectedness), machine learning, and textual analysis. He is an active member of the R in Finance community, and his research has been published in Quantitative Finance (2019), International Review of Economics and Finance (2018), and the Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence. Before his Ph.D., Majeed pursued graduate training in the area of Mathematical Finance at the London School of Economics (LSE) for one year and worked as a part-time Quantitative Analyst for Pantheon Ventures. He holds both BA and MA in Statistics from the University of Haifa with specialization in actuarial science.  Download

Martin Smid

Czech Academy of Sciences

Martin Šmíd is a researcher, working in the Czech Academy of Sciences. He holds a Ph.D. in Econometrics and Operations Research. Besides Financial Econometrics, his research interests include Decision Theory and Stochastic Programming.   
 Sasha F. Stoikov pic; select for larger image

Sasha Stoikov

Cornell Financial Engineering Manhattan

Sasha's research is in market microstructure, market incompleteness and their impact on the optimal strategies of stock and options traders. In particular, his quantitative finance research focuses on models of volatility, dynamics of limit order books and market-making techniques.

Sasha Stoikov is a senior research associate at Cornell Financial Engineering Manhattan. Stoikov, who is the son of a former professor of Industrial and Labor Relations at Cornell, holds a B.S. from MIT and an M.S. in mathematics from the University of Wisconsin, Madison in addition to his Ph.D. from the University of Texas. He has worked in the financial services industry as a consultant for the Galleon Group and Morgan Stanley and as a VP in the High-Frequency Trading group at Cantor Fitzgerald. Stoikov was also an instructor at the Courant Institute of New York University and a lecturer at Columbia's IEOR department.

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Maria Pia Beccar Varela, Ph.D.

Department of Mathematical Sciences

Maria Pia Beccar Varela has earned a Master degree in Physics from the University of Buenos Aires, a Master degree in Statistics from the University of Texas at El Paso and a Master and Ph.D. in Mathematics from New Mexico State University, her advisor was Dr. Ernest Barany. Her research interests include applied math and modeling, and statistical methods applied to Geophysics and Finance. She is at present a full-time faculty at the University of Texas at El Paso.  


Student speakers:


  Name Bio

Md Al Masum Bhuiyan

University of Texas at El Paso

 Md Al Masum Bhuiyan is currently a Ph.D. candidate in Computational Science Program at The University of Texas at El Paso (UTEP). He obtained a Masters degree in Mathematical Sciences from UTEP. He earned another Masters degree in Applied Mathematics and, prior to that, a Bachelor degree in Mathematics, both from the University of Dhaka, Bangladesh. He has been working on data analytics applications in Mathematical Finance & Geophysics, his areas of interest being statistical methods or, more precisely, stochastic differential equation, stochastic volatility model, deterministic volatility model, dynamical Fourier and Wavelet analysis, and machine learning techniques.

Osei Kofi Tweneboah

University of Texas at El Paso

I am currently a Ph.D. Candidate in Computational Science Program at The University of Texas at El Paso. In August 2015, I completed my MS in Mathematics from The University of Texas at El Paso under the guidance of Prof. Maria C. Mariani. My research interest are as follows: Data science: data mining, machine learning, big data analytics, etc.; Stochastic analysis: stochastic differential equations, stochastic processes, stochastic volatility etc.; Scientific computing: high performance computing, computational mathematics, etc.; Fourier and Wavelets analysis: modeling and analysis of data arising in data science and statistics, finance, geophysics, etc.



Michael Roberts

North Dakota State University

Michael is working toward a Ph. D. in mathematics focusing in finance at North Dakota State University. Previously, he earned a M.S. at University of Tennessee, Knoxville. His research interests include Lévy processes, stochastic differential equations, partial differential equations, and machine learning

shantanu phd student


Awasti Shantanu

North Dakota State University

I grew up in the Kanpur city of India. I received a bachelor's degree in Electronics Engineering. I am interested in Machine Learning, Actuarial Sciences. In spare time I prefer to watch documentaries.

Dan Wang

Stevens Institute of Technology

Dan Wang is currently a Ph.D. student in Financial Engineering program at Stevens Institute of Technology. Previously, he has earned a Bachelor degree in Beihang University and a Master degree in Stevens Institute of Technology. His research interests include Machine Learning in finance,  NLP and Volatility Spillover.

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Ziwen Ye

Stevens Institute of Technology

Ziwen Ye is a Ph.D. candidate in Financial Engineering, Stevens Institute of Technology. His research topic focuses on analyzing high-frequency data in financial markets, which includes rare events detection in the equity market, and the short-term option pricing in high-frequency trading.  His research interests include statistical models, time-series models, deterministic regimes models, machine learning techniques, and behavioral finance.