MSCF alumni regard our professors as the number one strength of the MSCF program and the primary reason for its success. From senior faculty with superior achievements to younger academics with new perspectives, MSCF professors are highly respected and knowledgeable in their fields. They are also praised by our students, with an average rating of 4.7 out of 5 stars on RateMyProfessors.com.
While industry practitioners are valuable in the classroom as knowledgeable guest lecturers, we developed our curriculum to be primarily taught by full-time, tenure-track faculty whose research interests are in the areas in which they teach. Whether it’s hosting additional office hours, responding to last-minute questions, offering extra review sessions before exams or creating additional practice materials, professors in the MSCF program are keenly interested in your success.
Learn more about the importance of tenured faculty when evaluating your options for a quant finance program.
Assistant Professor of Statistics, received his Ph.D. in statistics from Stanford University in 2014. Dr. G'Sell's research interests involve a variety of theoretical and applied questions in high dimensional statistics and machine learning.
Assistant Professor in the Department of Statistics and Data Science, graduated from the Wharton School of the University of Pennsylvania. Kuchibhotla research interests include post-selection inference, large sample theory, robust statistics, semi-parametric statistics, non-parametric statistics, concentration inequalities, high-dimensional CLT, and dependent data.
Thomas Lord University Professor of Statistics and Mathematical Sciences received his Ph.D. in statistics from Stanford University in 1969. Dr. Lehoczky’s main teaching and research interest involve the theory and application of stochastic processes. His current focus is on two broad application areas: financial markets and real-time computer and communication systems. In finance, he has been involved in the development of new simulation methodologies to price and hedge complex securities, the estimation of parameters of stochastic differential equations and its application to term structure or asset pricing models, and the behavior of limit-order books. His research in real-time computer systems involves collaboration with researchers at the CMU School of Computer Science, Electrical and Computer Engineering Departments and the Department of Mathematical Sciences. He developed, jointly with Professor Steve Shreve, a new analytic methodology called real-time queueing theory. He has published extensively in journals including the Annals of Applied Probability, Management Science and Real-Time Systems. He has served on the editorial staff of Management Science, IEEE Transactions on Computers, and Real Time Systems. Dr. Lehoczky is a fellow of the American Statistical Association, Institute of Mathematical Statistics, INFORMS, AAAS, is an elected member of the International Statistics Institute, and was co-recipient of the 2016 IEEE Simon Ramo medal.
Assistant Teaching Professor of Statistics & Data Science, received his Ph.D. in statistics from Carnegie Mellon University in 2018. Dr. Reinhart's research includes the use of spatiotemporal point processes to solve interesting applied problems, such as the modeling and prediction of crime. He also conducts research in statistical education and pedagogy, studying the ways students understand statistical concepts, and is the author of the popular book Statistics Done Wrong, on common statistical mistakes made by scientists.
Professor of Statistics, received his Ph.D. in statistics from the University of California, Berkeley in 2004. His primary research interests focus on addressing inference problems in the physical sciences using novel, often computationally- intensive, statistical methods. He is a part of the McWilliams Center for Cosmology at CMU and actively collaborates with researchers in astronomy, particle physics, and risk assessment. He has published in the Journal of the American Statistical Association and the Astrophysical Journal, among others.
John K. Ostlund, Clinical Professor of Information Systems at the Heinz College, currently works as a consultant in the financial industry, developing option pricing software in C++. Formerly, John was Principal Research Programmer at the Auton Lab, a Machine Learning research group at Carnegie Mellon University, for over eight years. In that position, he worked in C and C++ on machine learning algorithms, and the application of these algorithms to large data sets from U.S. government agencies involved in intelligence, health monitoring and fleet maintenance. Prior to the Auton Lab, John was a leadingcourse author and instructor for Learning Tree International, a top-ranked technology and management training company. He developed and taught courses in C++, C, Unix, Linux and Solaris. John holds an MS in Computational Finance from Carnegie Mellon University and a BA in Physics and Mathematics from St. Olaf College.
Professor of Mathematical Sciences, Dr. Hrusa earned his Ph.D. from Brown University. His main areas of research are in partial differential equations, integral equations, and calculus of variations with particular emphasis on problems that arise in continuum mechanics. Current research is focused on Lavrentiev’s phenomenon in the calculus variations, i.e. with situations in which the infimum for a given variational problem is sensitive to the precise degree of regularity that is assumed for the competing functions. A major goal is to understand if this phenomenon can occur for realistic problems in nonlinear elasticity.
Associate Professor of Mathematical Sciences, Professor Iyer earned his Ph.D. from the University of Chicago in 2006. He was a Szegö Assistant Professor at Stanford University from 2006 to 2009 and joined Carnegie Mellon in 2009. His current research is mainly focused on the theoretical study of problems arising in applied mathematics using tools from partial differential equations and probability. Professor Iyer has won prestigious research awards, including an Alfred P. Sloan fellowship, a National Science Foundation CAREER Grant, and a Simons fellowship. The latter is funded by the Simons Foundation created by James Simons, the founder of the hedge fund Renaissance Technologies.
Mellon College of Science Professor of Mathematical Finance, Professor Kramkov earned his Ph.D. from the Steklov Mathematical Institute in Moscow in 1991. His current research is mainly focused on topics in mathematical finance such as equilibrium, dynamic game theory, option pricing theory, and optimal investment. In 1996 he received a prize of the Second European Congress of Mathematics in Budapest for his research on statistics and mathematical finance. From 1997 to 2000 Dr. Kramkov worked for Tokyo-Mitsubishi International in London, where he was the Acting Head of Research and Product Development. His main responsibility was the evaluation of complex derivative contracts. Dr. Kramkov currently serves as an Associate Editor of the journal of Finance and Stochastics. He has an affiliation with the University of Oxford, where he is a member of Man-Oxford Institute for Quantitative Finance.
Associate Professor of Mathematical Sciences, Professor Larsson earned his Ph.D. from Cornell University in 2012. Before joining Carnegie Mellon in 2019, he was an Assistant Professor of Mathematical Finance at the Swiss Federal Institute of Technology (ETH) in Zurich. Professor Larsson's research touches on a number of areas in mathematical finance, probability, and stochastic analysis, with applications to term structure modeling, stochastic portfolio theory, and equilibrium analysis. Recent research interests also include the mathematics of deep learning and the application of tools from mathematical finance to problems in statistics.
Orion Hoch and University Professor of Mathematical Sciences and member of the MSCF Steering Committee. Professor Shreve earned his Ph.D. in 1977 from the University of Illinois. His research and teaching interests range from capital asset pricing models to various aspects of mathematical finance, including the effect of transaction costs and unknown volatility on option prices and diffusion models of limit-order books.Dr. Shreve is past-President of the Bachelier Finance Society. In 1994, Dr. Shreve was one of the founders of the Carnegie Mellon Master's program in Computational Finance. Dr. Shreve serves as Advisory Editor of the journal, "Finance and Stochastics." He has co-authored a number of books, including "Brownian Motion and Stochastic Calculus" and "Methods of Mathematical Finance." He has written a two-volume work based on his teaching in the MSCF program, "Stochastic Calculus for Finance."
Zeigham joins us from Tulane University, where he was an Assistant Professor of Finance. His research focuses on energy finance, specifically using data prediction on potential mispricing of oil. His career began with modeling and estimation, and has evolved to focus on machine learning, specifically in computation and statistics in the asset management domain. He will teach Data Science in Finance and Asset Management starting in spring 2021. Zeigham received his Ph.D. from the University of Texas at Austin, McCombs School of Business.
Javier Pena is the Bajaj Family Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University. He earned his Ph.D. in Applied Mathematics from Cornell University in 1998. His teaching and research interests include financial optimization, machine learning, and convex optimization. Dr Pena's publications have appeared in journals such as Quantitative Finance, Journal of Risk, Mathematics of Operations Research, and the SIAM Journal on Optimization. Dr. Pena has consulted with Axioma Inc. in the development and implementation of algorithmic tools for portfolio management. Dr. Pena was the recipient of the 2005 George Leland Bach MBA Teaching Award for excellence in the classroom.
Teaching Professor of Business Management Communication with the Tepper School of Business for 23 years, Prof. Pierce's research and consulting focuses on the development and implementation of executive problem-solving skills in communications, corporate leadership and communication strategies, cross-team collaboration, and team building. She was honored with the Sustained Excellence in Teaching Award in 2004 as well as the Undergraduate Teaching Award in 1996. She has coached award-winning case competition teams and has mentored students in their new business development plans and presentations. In 2009, she founded what is now called the Communications Studio, a critical mentoring center that is a part of the Accelerate Leadership Center at Tepper. She has consulted with numerous corporations that include PNC Bank, Alcoa, and Bayer, Inc. She also has taught in Carnegie Mellon's Masters of Robotics Systems Development program since its inception in 2011.
Ron Placone is Associate Teaching Professor of Business Management Communication and the Faculty Lead for the Accelerate Leadership Center at the Tepper School of Business. He received his Ph.D. in Rhetoric-English from Carnegie Mellon University in 2009. Ron teaches a range of communication courses and leadership programs for graduate and undergraduate students and oversees a communication studio. Ron has served as a consultant and coach for numerous executives and to corporate and not-for-profit organizations. His engagements have focused on leadership and organizational development, strategic planning, and change management. Ron has delivered presentations on individual and organizational effectiveness at regional and national conferences and has published articles in banking, health care, human resources, legal and quality improvement journals.
Duane Seppi is the BNY Mellon Professor of Finance at the Tepper School of Business. He received his Ph.D. from the University of Chicago in 1988. Duane’s teaching and research interests include energy and commodity derivatives, stochastic volatility modeling, market microstructure, limit orders, and liquidity. His research has been published in the Review of Financial Studies, Journal of Finance, Journal of Financial Economics and other leading finance and economics journals. His research has been recognized by awards from the the Q-Institute, the Western Finance Association, and the Journal of Asset Pricing Studies. He has been on the editorial boards of the Journal of Finance, the Review of Financial Studies, the Journal of Financial Markets, and the Review of Finance. He was a visiting scholar at the US Securities and Exchange Commission and at Nanyang Business School.
Leif B. G. Andersen is the Global Head of the Quantitative Strategies Group at Bank of America Merrill Lynch. He holds MCs in Electrical and Mechanical Engineering from the Technical University of Denmark, an MBA from University of California at Berkeley, and a Ph.D. in Finance from Aarhus Business School. He was a co-recipient of Risk Magazine's Quant of the Year Award in 2001 and again in 2017. He has worked for more than 20 years as a quantitative researcher in the derivatives pricing and risk management areas.
Ed Barr received his master’s degree from Indiana University of Pennsylvania in 1976. He served as Chief Marketing Officer at Carnegie Mellon’s subsidiary, iCarnegie, from 2010 to 2012, as well as associate teaching professor at CMU’s Heinz College from 2000 to 2010. He has served as Vice President of Marketing for Allegheny University Medical Practices and has held other marketing, teaching and executive education roles. Barr is certified as a teacher of English as a Second Language and has taught in China, India, Mexico, South America and Europe. Barr is the author of several books, including “Seven Secrets to Successful Business Writing,” “Seven Secrets to Successful Business Presentations” (both in English and Spanish) and “Ask the Right Questions; Get the Right Job.”
Professor Bryant, Adjunct Professor of Industrial Administration, received his BA from Denison University in 1975 and MBA from Carnegie Mellon in 1980. Following six years with H.J. Heinz Company in their Corporate M&A and Treasury areas, Bryant became Reebok International's Treasurer in 1988 and in 1993, Chief Financial Officer of Hefren-Tillotson, a broker/dealer and investment advisor. Professor Bryant joined the Tepper School in 1999 as the Executive Director of Carnegie Mellon's Computational Finance Program and over the years has taught both in Tepper's undergraduate finance program and in the MSCF program.
Jeff Greco is a Principal & Senior Director – Head of Strategy Research with Milliman Financial Risk Management, LLC. He holds a BS & MS in Mathematics from Carnegie Mellon University, and an MS in Applied Mathematics from the University of Chicago. He has worked in the finance industry since 1995 in the areas of quantitative research, capital markets valuation, risk management, and trading strategy development. Jeff has taught graduate level financial mathematics since 2002.
Peter started his career in 1994 as a quantitative developer for O’Connor & Associates which was owned by Swiss Bank. In 1997 he was hired by Susquehanna International Group, at the time the largest proprietary derivatives trading firm in the US. Peter started in the FX derivatives team and then migrated into equities whereby he focused on index and ETF arbitrage, dispersion and other volatility trading strategies. In 2005 Peter joined Deutsch Bank’s equity exotics desk where he was responsible for franchise equity correlation trading. Peter held various roles within the equities platform including building and running a global proprietary portfolio with a concentration on equity volatility and dispersion trading. In 2011 Peter joined Citi as America’s head of equity derivatives trading, 2015 was promoted to head of America’s equity trading and in 2018 Peter’s responsibilities expanded and he currently oversees equity cash globally.
Nick Psaris is a Managing Director in Bank of America's Data & Innovation Group. He is a CFA charterholder and holds a Masters in Computational Finance from the Tepper School of Business at Carnegie Mellon University. Nick wrote "Q Tips: Fast, Scalable and Maintainable Kdb+" based on his years of practical experience developing production trading systems in q. In 2020, he released "Fun Q: A Functional Introduction to Machine Learning in Q" which uses the expressive q language to guide readers through implementing twelve machine learning algorithms from scratch. Between New York and Hong Kong, Nick has worked for more than 20 years as a trading strategist.