CoFES Faculty Advisory Board

The founding Faculty Advisory Board for CoFES, consists of L. Scott Baggett, Bryan W. Brown, Keith Cooper, Katherine B. Ensor (director), Peter R. Hartley, Matthias Heinkenschloss, George Kanatas, Richard J. Stoll, James R. Thompson. A short biography of each faculty member is provided below. Full vitaes are available upon request.

L. Scott Baggett, (Baggett@rice.edu) is Senior Statistician at the Jesse H. Jones Graduate School of Management. He also holds a Lecturer’s position in the Department of Statistics and is Director of the Rice University Statistical Consulting Lab. His research interests include stochastic processes of financial systems and the application of statistics to climatology.

Bryan W. Brown, (bwbwn@rice.edu) Reginald Henry Hargrove Professor of Economics, focuses his research on econometric theory. His articles have appeared in numerous scholarly journals. Much of his early work concentrated on developing methodology for identification, estimation, and prediction in nonlinear systems, models of the type that have been widely used for macroeconomic forecasting. This work was the first to propose the use of simulation techniques for approximating the higher-order integrals involved in prediction in these models under relaxed distributional assumptions. This research led, recently, to a more general interest in simulation-based and semiparametric estimation.

Keith Cooper, (keith@rice.edu) Professor and Chair of Computer Science, has primary research interests in code optimization for modern microprocessors. His recent work has included interprocedural analysis and optimization; code generation issues, such as register allocation and scheduling; and rethinking classical optimizations. His current work is focused on practical and effective techniques for interprocedural optimizations, classical optimization, compiler management of latency, and issues that arise in the design and use of deep memory hierarchies.

Katherine B. Ensor, (ensor@rice.edu) Professor and Chair of Statistics, is an expert in time series and forecasting, stochastic processes, and spatial processes. For the past decade, she has made substantive contributions in the area of inference for stochastic processes. Such models form the basis for financial and econometric modeling. A basic premise of her research is the practical application of complex models. She investigates the use of simulation and computer intensive techniques, which take the modeler directly from model formulation to model implementation, keeping as much of the mathematical complexity in the background as possible. A second theme to Dr. Ensor's research activities is spatial-temporal modeling with specific application to problems in environmental science.

Peter R. Hartley, (hartley@rice.edu) Professor and Chair of Economics, has published articles, books and policy papers on theoretical and applied issues in many areas of economics including money and banking, business cycles, regulation of utilities and airlines, energy economics, environmental economics, international finance, health and labor economics, and the economic analysis of legal issues. His research includes quantitative and methodological papers of direct relevance to the focus of the Center. He also teaches undergraduate courses in corporate finance and economic analysis under uncertainty that would be part of the proposed curriculum in Financial Engineering. Peter has policy experience working as part of a team of economists advocating and advising on reform of the electricity supply industry in Australia throughout the 1980s and early 1990s. He also worked for the Prime Minister’s Department in the Australian Federal Government in 1975 and 1976.

Matthias Heinkenschloss, (heinken@rice.edu) Associate Professor of Computational and Applied Mathematics, specializes in optimal control and computational optimization. His research includes the development and analysis of state-of-the-art computational tools for the solution of complex, large-scale optimization problems in engineering and the social sciences, and the implementation of these tools in high performance computing environments.

George Kanatas (kanatas@rice.edu) is a Professor of Management at the Jesse H. Jones Graduate School of Management. His research interests include Corporate Finance and Financial Intermediation. He is well published and has served on the editorial boards of numerous respected journals in finance.

Barbara Ostdiek, (ostdiek@rice.edu) Associate Professor of Finance at the Jesse H. Jones School of Management and Department of Statistics, currently focuses her research on financial market volatility, information linkages, and cross-market volatility. Complex econometric stochastic volatility models form the foundation for this research. Applications include analyzing the information linkages among the U.S. stock, bond, and money markets; analyzing the impact of derivative introductions on the underlying assets in the energy markets; estimating the economic value of volatility predictability; and characterizing the volume-volatility relation.

Richard J. Stoll, (stoll@rice.edu) Professor of Political Science and Associate Dean of the School of Social Sciences. In addition to being known as one of Rice University’s outstanding teachers, Professor Stoll is an accomplished scholar of international conflict. He has used computer simulation techniques to study such issues as defense spending, arms races, and collective security. A member of the Council of the Correlates of War Project, Dr. Stoll is currently participating in a ten-university effort funded by the National Science Foundation to collect data on militarized interstate disputes. He recently received a grant from the National Science Foundation, joint with Devika Subramanian of Computer Science, to study techniques and methods for early prediction of international conflict based on publicly available data.

James R. Thompson, (thomp@rice.edu) Noah Harding Professor of Statistics, develops models for business and economics. He has taught courses in market models at both the senior undergraduate and graduate levels. He has been the thesis advisor for two doctoral dissertations dealing with derivatives based on mortgages and natural gas. His approach in dealing with market models is computationally intensive. He works with the usual naive stochastic differential equation models that form the basis of efficient market theory, then adds on as "patches" items to bring the naive models closer to economic reality. The creator of SIMEST, a simulation based paradigm for parameter estimation, he builds deep models selected for conformity to data, rather than for mathematical or approximation theoretic tractability. He is the author or co-author of twelve books, four of which are concerned with model-based simulation. His most recent text is Models for Investors in Real World Markets to be published by Wiley this winter.