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 4.6 out of 5 on the University’s Faculty Course Evaluations.
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 “day job” is teaching our students. 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 academic and professional success!
Learn more about the importance of tenured faculty when evaluating your options for a quant finance program.
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.
Assistant Teaching Professor of Statistics & Data Science, received his Ph.D. in statistics from Carnegie Mellon University in 2022. Dr. Yurko's research focuses on developing methods at the interface of inference and machine learning, oriented towards problems in statistical genetics. He also actively publishes sports analytics research and has work featured in popular media outlets such as FiveThirtyEight and The Wall Street Journal, among others. He previously worked in finance modeling risk and in the professional sports industry.
Michael McCarthy is an Associate Teaching Professor of Information Systems at Carnegie Mellon University's Heinz College of Information Systems and Public Policy. He has taught graduate courses in Applied Cryptography, Distributed Systems, Internet of Things, and Data Structures and Algorithms. Professor McCarthy’s degrees include a BA in Philosophy and an MS in Information Science (Systems Track), both from the University of Pittsburgh. He is a member of the Association for Computing Machinery (ACM) and has over twenty years of university-level teaching experience. Mr. McCarthy has also worked as a software consultant to several engineering firms. Mr. McCarthy is primarily interested in standard data representation and data processing methods for the World Wide Web, the Web of Things, Web Services and the Semantic Web.
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 Carnegieie 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 Computationall Finance from Carnegie Mellon University and a BA in Physics and Mathematics from St. Olaf College.
Dr. Raja Sooriamurthi is a Teaching Professor in the Information Systems Program at Carnegie Mellon University's Heinz College of Information Systems and Public Policy. Research interests include Artificial intelligence and cognitive science with an emphasis on case-based reasoning, knowledge-management, distributed reasoning and machine learning. Other interests include higher order programming languages, software development, computer science / information systems pedagogy.
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.
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.
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. He is also interested in sequential statistics, where finance-inspired trading analogies lead to novel approaches to valid statistical testing and inference in online settings.
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."
Assistant professor of Mathematical Sciences, Johannes Wiesel earned his Ph.D. from Oxford University in 2020. Before joining Carnegie Mellon in 2023, he was an Assistant Professor of Statistics at Columbia University. Professor Wiesel's research is primarily focused on the robust approach to mathematical finance, which does not start with an a priori model but rather with information available in the markets. He has established new connections to the theory of optimal transportation of stochastic processes on the one hand and statistics as well as machine learning on the other. His theory provides a universal toolbox for the implementation of robust and time-consistent trading strategies and risk assessment.
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.
Lars-Alexander Kuehn is an Associate Professor of Finance at the Tepper School of Business of Carnegie Mellon University. He received his Ph.D. in Finance from the Sauder School of Business at the University of British Columbia (Vancouver, Canada). His research and teaching focuses on the valuation of equity and corporate debt. More specifically, he has done research on risk factors in equity market, credit risk modeling, and risk management. An underlying theme of his research is to connect valuations to variation in macroeconomic sources of risk. His work has been published in leading journals in finance and economics.
Professor Kuehn has won multiple awards for his research as well as the Gerald Thompson Teaching Award for Excellence in the Classroom for undergraduate business education and the George Leland Bach Excellence in Teaching Award for MBA education at CMU.
Currently, he serves as an associate editor at the Journal of Finance.
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.
Joseph Rudman, Adjunct Professor of Business Communication, has been teaching oral business communications at Tepper since 1993. He holds a Doctor of Arts degree from Carnegie Mellon University. He has studied Speech and Classical Rhetoric. Rudman has been a consultant with Solutions 21, the Canadian Government, the Australian Government, the City of Pittsburgh, several banks, the American Institutes for Research, and others. He has given over 300 presentations in 15 foreign countries and 124 U.S. cities to statisticians, computer scientists, digital humanists, literary scholars, bibliographers, business groups, and others.
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.”
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.
Nick Psaris is a Managing Director in Bank of America's Central Risk Book desk. 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.
Nick graduated from Tepper with a PhD in Economics in May of 2020. He is currently a postdoctoral scholar in the Laboratory for Aggregate Economics and Finance at the University of California, Santa Barbara. His research focusses on household finance, specifically how behavioral phenomena determine agent-level consumption and savings decisions as well as macroeconomic outcomes. His work has been funded by the NSF and CMU’s PNC Center for Financial Services Innovation, among other institutions.
Jon Kinol was Managing Director at Credit Suisse and Deutsche Bank. As Global Head of Rates at Credit Suisse, Jon was responsible for all aspects of trading and sales of Interest Rate Derivatives, Government Bonds, and Agency products in the United States, Europe and Asia. At Deutsche Bank, Jon was Head of North America Rate Trading, Global Head of Rate Proprietary Trading, and Global Head of Credit Correlation Trading. Jon is currently involved in several trading ventures applying analytics to trading decisions in the macro and derivative markets. He is also an Executive in Residence at Duquesne University supporting Student Managed Investment Funds. He is a member of the Board of Directors at Duquesne University and the Board of Business Advisors at the Tepper School of Business at Carnegie Mellon. Previously, Jon was a member of the Treasury Borrowing Advisory Committee which advises the United States Treasury on economic and technical debt management issues.
Dr. Lisa Larsson is a Managing Director, Portfolio Management, at StepStone. Prior to StepStone, Dr. Larsson was an assistant vice president on the credit economic risk capital team at Credit Suisse. Before that she was an assistant professor at the Courant Institute of Mathematics at NYU. Dr. Larsson received her PhD in mathematics from McGill University, her MS from the Swiss Federal Institute of Technology (ETH), and her BS from Michigan Tech University.
John Mackey is a teaching professor, jointly appointed in mathematics and computer science. For research, I like to hunt for elusive mathematical objects having special properties. For example, assuming that every pair of people are either acquaintances or strangers, it is not known whether it is possible to have a party of 43 people at which no five people are mutual acquaintances and no five people are mutual strangers. Such questions test the boundary of mathematics and computation.
My primary activities in the departments are teaching, serving on curriculum and education committees, mentoring various clubs and campus groups, and hosting prospective students and their parents. I was a co-PI on the recent NSF Debt-M grant to help Pittsburgh Public School Students close the opportunity gap faced in their pursuit of mathematics.
Dr. Amal Moussa is a Managing Director at Goldman Sachs where she leads the Single Stocks Exotic Derivatives Trading team. 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. Amal has a Ph.D. in Statistics, obtained with distinction, from Columbia University. Prior to her Ph.D., Amal graduated with a Masters in Mathematical Finance from Sorbonne Université (former Paris VI) and a Grande Ecole engineering degree from Télécom Paris.
Tim Weithers was born in Chicago, the worldwide headquarters for options. He received a Ph.D. in Mathematical Economics from The University of Chicago. After teaching in The Department of Economics at Fordham University in New York, Tim joined O'Connor and Associates, the world's premiere proprietary option trading and marketmaking firm. O'Connor was bought by Swiss Bank Corporation (SBC) which acquired S.G. Warburg, Brinson Partners, Dillon Read, Paine Webber, and eventually merged with Union Bank of Switzerland to form the new UBS. Tim was a Managing Director at UBS. Tim was also a faculty member (and Associate Director) for The University of Chicago's Graduate Program in Financial Mathematics, from its inception in 1996 through 2010. Tim finished his full-time professional career as an Executive Director at Chicago Trading Company (or CTC) -- which was founded by former O'Connor option traders/colleagues; CTC is also one of the world's premier option trading and marketmaking institutions. Now retired, Tim is often engaged as an expert witness (in Federal Court and Federal Tax Court), serves as a consultant (mainly on derivatives) for regulatory actions, settlements, arbitrations, and he still occasionally teaches and does work for the option exchanges, banks, regulators, and trading firms. Tim wrote a (woefully out-of-date) book entitled "Foreign Exchange: A Practical Guide to the FX Markets" published by John Wiley & Sons in 2006.