Our Distinguished Faculty

Applied Mathematics and Statistics faculty have Ph.D.s in mathematics, applied mathematics, operations research, statistics, physics, biophysics, biostatistics, and chemical engineering. Every faculty member has collaborated on papers or grants with scientists in other disciplines. James Glimm is a member of the National Academy of Sciences, Sheldon Weinig is a member of the National Academy of Engineering, and Ram Srivastav is a member of the Indian National Academy of Sciences. Glimm has received the National Medal of Science , Steele Prize of the American Mathematical Society (for work in nonlinear analysis) and the Heinemann Prize of the American Physical Society (for work in quantum field theory). Alan Tucker won the Mathematical Association of America's National Award for Excellence in University Mathematics Teaching, and David Ferguson won the U.S. President's Award for Excellence in Science/Mathematics/Engineering Mentoring. John Grove and Joe Mitchell were National Science Foundation Presidential Young Investigators. Judy Tanur was runner-up in the latest election for president of the American Statistical Association.

Faculty(in alphabetical order) :

ALAN TUCKER, Distinguished Teaching Professor
Ph.D. 1969, Stanford University

Alan Tucker started his career at Stony Brook doing research and directing doctoral students on problems in graph theory and combinatorial algorithms. Over the past 15 years he has become more and more engaged in projects dealing with collegiate mathematics education. He has been the lead author of four national reports for the Mathematical Association of America, Recommendations for a General Mathematical Sciences Program (1981), Assessing Calculus Reform Efforts (1995), Case Studies in Effective Undergraduate Mathematics Programs (1996), and The Mathematical Education of Teachers (2001). Tucker recently directed the NSF-funded Long Island Consortium for Interconnected Learning, which involved more than 350 faculty at 10 Long Island colleges and universities in an array of innovative efforts to coordinate and enhance instruction in quantitative disciplines. He co-directs a large NSF VIGRE grant jointly with Stony Brook ’s Department of Mathematics, to integrate research and education across the mathematical sciences. This grant includes 16 fellowships for graduate students.
(631) 632-8365, atucker@notes.cc.stonybrook.edu

BRENT LINDQUIST, Professor
Ph.D. 1981, Cornell University

What do we need to accurately compute the movement of water and oil below ground? This question is equally pertinent to oil reservoir production as it is to cleanup of organic contamination in groundwater. Brent Lindquist’s research is focused towards improving our understanding of the fundamental characterization of the properties of porous media and the relation of these properties to fluid motion, and establishing limits on the accuracy of fluid movement prediction given practical limits on our understanding of the medium properties. Lindquist’s research tools involve numerical solution of nonlinear PDEs of mixed type, statistics/probability theory, elements of computational geometry, and image analysis. An additional result has been the unexpected technology transfer of tools developed for the above to the biological sciences, specifically the study of neurons. His research collaborations are with scientists at Brookhaven National Laboratory, Cold Spring Harbor Laboratory, the Australian National University, Mt. Sinai School of Medicine, and the New Mexico Institute of Mining and Technology.
(631) 632-8361, lindquis@ams.sunysb.edu

DAVID F. GREEN, Assistant Professor
Ph.D. 2002, MIT

David Green's research involves computational and theoretical methods to study the specificity of protein-protein interactions. Rather than restricting his studies to biophysical descriptions of protein-protein binding, David is taking an integrated systems biology David's work focuses on the model system of heterotrimeric G-proteins to address a broad range of cellular activities. He is working to identify the interactions which lead to high specificity or promiscuity between families of structurally related proteins, describe the possible modes of evolution of a single binding pair into a family of interacting proteins and develop computation methodologies for the design of specifically interacting proteins. The ramifications of theses molecular-level events on the behavior of the system as a whole is a key area of interest.
(631) 632-9344, dfgreen@ams.sunysb.edu

ESTHER M. ARKIN, Professor
Ph.D. 1986, Stanford University

Esther Arkin’s primary research area is the design and analysis of algorithms that arise in a variety of fields, including network optimization, computational geometry, graph theory, scheduling, robotics, geographic information systems, computer graphics, manufacturing, and computer vision. Algorithms are ubiquitous in modern life and the need to improve their efficiency and effectiveness only increases as the problems that need to be solved get larger. Arkin is interested in theoretical analysis of worst-case complexity of problems, especially those that require optimization. For many of the hardest problems (particularly those that are “provably hard”), the interest is in obtaining provably good approximations to what an optimal algorithm would produce, but doing so in a running time that is provably good (polynomially bounded). Arkin is also interested in the experimental evaluation of efficiently designed heuristic algorithms, especially those that arise in real-world applications.
(631) 632-8363, estie@ams.sunysb.edu

EUGENE FEINBERG, Professor
Ph.D. 1979, Vilnius University, Lithuania

Eugene Feinberg’s broad area of research is stochastic methods of operations research and their industrial applications. His major areas of expertise are operations research; operations management; stochastic optimization with application to telecommunication; and manufacturing, transportation, service, and other manmade systems. Feinberg has held permanent and visiting appointments at the Moscow Institute of Transport Engineering, Yale University, and MIT. Feinberg’s fundamental research focuses on Markov Decision Processes and other methods for optimization and control of stochastic systems and their applications. In addition, he works on several industrial projects. One of his major current projects deals with applications of operations research and statistical methods to electric energy transmission and distribution. Another project deals with applications of operations research and statistics to information technology.
(631) 632-7189, efeinberg@notes.cc.stonybrook.edu

HONGSHIK AHN, Professor
Ph.D. 1992, University of Wisconsin-Madison

Hongshik Ahn’s initial research effort was in the area of tree-structured regression modeling for censored survival data. After graduation, he worked in the Division of Biometry and Risk Assessment at the National Center for Toxicological Research (NCTR). During these four years, he served as the principal investigator for several projects on animal carcinogenicity, developmental toxicology, and drug stability analysis. He also played an important role in the development of the tumor analysis for the NCTR’s Project on Caloric Restriction (PCR) studies. After joining Stony Brook in 1996, Ahn continued this research effort and received a five-year NIH FIRST (National Institutes of Health First Independent Research Support and Transition) Award on analyses of animal carcinogenicity experiments. In this project, Ahn is collaborating with the statisticians and scientists at the NCTR. He is also working on tree-structured generalized linear regression models for counting data and a variable selection problem in regression and experimental design.
(631) 632-8372, hahn@ams.sunysb.edu

JAMES GLIMM, Distinguished Professor
Ph.D. 1959, Columbia University

James Glimm’s research focuses on computational methods theory and applications, numerical algorithms for solution of differential equations, and the analysis and modeling of complex fluid flows. His other research deals with simulation of Maxwell’s equations in complex geometries for study of opto-electronic computing and communication components. A third area of investigation is algorithms for simulation of material deformation and failure. Glimm is also interested in flow in porous media. His theoretical interests include analysis of solutions of nonlinear hyperbolic equations, analytic models of turbulent diffusion and turbulent mixing, and studies of multiphase flow. Glimm is involved in the analysis of errors in numerical solutions, methods of comparing numerical solutions to observational data and the inferences that may be drawn, and the role and quantification of uncertainty in science-based predictions of natural phenomena.
(631) 632-8355, glimm@ams.sunysb.edu

JIAQIAO HU
Ph.D. 2006, University of Maryland, College Park

Jiaqiao Hu's research interests lie in various areas of operations research,including Markov decision processes (MDPs), applied probability, simulation, computational learning theory,and various simulation-based optimization techniques. A significant part of his research is focused on designing and analyzing randomized search methods for solving Markov decision processes and global optimization problems. He has been studying a wide range of theoretical and applied problems of control and decision making using Markov decision process models. Many real-world problems of practical interest are often very large and complex, so that classical solution methods may quickly become computationally intractable, even with significant computing resources. In particular, he has been investigating sampling-, simulation-, and population-based numerical algorithms to overcome the computational difficulties associated with traditional solution techniques, where sampling and simulation techniques are used not only to avoid enumerating the entire solution space but also to resolve the issue of the unavailability of explicit mathematical models of the underlying systems.
Contact - jqhu@ams.sunysb.edu (Math Tower 1-107 ext. 2-8239)
Website - http://www.ams.sunysb.edu/~jqhu/

JOHN REINITZ, Professor
Ph.D. 1988, Yale University

John Reinitz is a biologist who previously worked in departments of Biological Sciences, Molecular Biology and Biochemistry before coming to the Stony Brook Department of Applied Mathematics and Statistics. His research area is in the developmental biology of the fruit fly, Drosophila melanogaster . During the first 90 minutes of life, the cells in the developing fly embryo acquire specific developmental fates in a very precise spatial pattern. This physical organization is the result of differential gene expression among a mutually interacting network of genes. Reinitz's research is focused on characterizing the dynamics of this genetic network. To examine these dynamics, he uses mathematical models, quantitative, gene expression done from his laboratory in the Center for Developmental Genetics and extensive computer simulations that involve state-of-the-art computational science.
(631) 632-8352, reinitz@ams.sunysb.edu

JOSEPH MITCHELL, Professor
Ph.D. 1986, Stanford University

Joe Mitchell’s primary research area is computational geometry, applied to problems in computer graphics, visualization, robotics, manufacturing, geographic information systems, and computer vision. Computational geometry is the study of the design, analysis, and implementation of efficient algorithms to solve geometric problems. Mitchell is interested in both theoretical and applied computational geometry. Theoretical work involves coming up with algorithms that are provably more efficient than their predecessors, and applied work involves modeling real-world problems in a precise framework, designing and implementing algorithms (possibly heuristic), and giving experimental evidence of the efficiency and effectiveness of the algorithms on real data. Mitchell also has interests in the study of algorithms, particularly in optimization problems, approximation algorithms, and networks. Mitchell heads the Computational Geometry Lab at Stony Brook, which is engaged in an active industrial outreach program of collaboration with industry and government labs on various applied projects.
(631) 632-8366, jsbm@ams.sunysb.edu

NANCY ROLE MENDELL, Professor
Ph.D. 1972, University of North Carolina

Nancy Mendell’s major area of interest is statistical genetics and genetic epidemiology. This research area concerns the genetics of complex human traits, including attributes such as schizophrenia and disease susceptibility that are due to the interaction between more than one gene and environmental factors. One aspect of her research is the development of measures for these disorders that are more directly related to the gene action. These include traits which have a different distribution in the individual affected with a disease than unaffected individuals and which have different distribution in the relatives of the affected individuals. A second aspect of Mendell’s research involves developing a methodology for gene mapping that can be applied to traits that result from two or more genes. These methodologies are currently being applied to the analysis of family data on schizophrenia, glaucoma, and malaria. Additionally, Mendell participates in the Genetic Analysis Workshop, a group which meets in alternate years after having analyzed a common simulated data set with the objective of presenting and evaluating the statistical methodologies they have developed.
(631) 632-8373, nmendell@notes.cc.stonybrook.edu

ROBERT C. RIZZO, Assistant Professor
Ph.D. 2001, Yale University

Under the broad category of “Computational Structural Biology” the Rizzo research group seeks to understand the basis for molecular recognition at the atomic level for specific biological systems involved in human disease, such as influenza, SARS, and HIV/AIDS, with the ultimate goal of developing new and improved drugs. Computation is used to model how drugs (typically small molecules) interact with a given receptor (typically a protein). The resultant 3D atomic level structural and energetic information from the calculations can be used to quantify and rationalize drug-binding for known systems and to make predictions for new ones. The research is geared towards developing improved methods and computational tools for estimating binding energies and for virtual screening (docking) calculations which facilitate structure-based design. The research is very interdisciplinary and encompasses not only Applied Mathematics and Statistics, but Biochemistry, Informatics, and Computer Science/Programming. The group has active collaborations with researchers here at Stony Brook, Brookhaven National Laboratory, and the University of California at San Francisco .
(631)632-9340, rizzo@ams.sunysb.edu

STEPHEN FINCH, Professor
Ph.D. 1974, Princeton University

Stephen Finch’s major areas of interest are statistical genetic epidemiology and applied longitudinal data analysis. Statistical genetic epidemiology studies the genetics of complex human traits, such as bipolar disorder or schizophrenia. The focus of Finch’s research is to develop methodology for gene mapping that can be applied to traits that result from two more genes and to estimate the statistical properties of complex data analysis procedures. Research is underway with colleagues at Rockefeller University to identify data analysis procedures that are the most effective at identifying genetic linkages, especially multi-locus linkages. Finch is doing applied research on two longitudinal studies. He is working with colleagues at the Mt. Sinai School of Medicine on the development and consequences of drug usage, and with colleagues at the Stony Brook University Health Sciences Center’s Department of Psychiatry on the effects of medications on the course of mental illnesses.
(631) 632-8369, finchs@ams.sunysb.edu

WEI ZHU, Professor
Ph.D. 1996, University of California at Los Angeles

Wei Zhu is a biostatistician. Her major research areas are brain image analysis, design and analysis of clinical trials, genetics modeling, environmental statistics, and aviation safety analysis. In the brain image analysis area, she is collaborating with medical researchers at Brookhaven National Laboratory (BNL) to quantify changes in brain functional relationships under drug influence. She is among the pioneers in applying the concept of multiple-objective optimal design to clinical trials and quantal dose-response experiments. In genetics, she is working on the analysis of microarrays to ascribe genes to various functional groups. Zhu has experience with the analysis of large data sets on the scale of terabytes, and she is an affiliate of the BNL Center for Data Intensive Computing. In addition to her close collaboration with BNL, Zhu has also worked with researchers at Stony Brook, the New York State Department of Health, the New York State Department of Environmental Conservation, Merck Research Laboratories, the Federal Aviation Administration, and Veeco USA.
(631) 632-8374, Zhu@ams.sunysb.edu

XIANGMIN (JIM) JIAO, Assistant Professor
Ph.D., 2001, University of Illinois at Urbana-Champaign

Dr. Jiao conducts fundamental as well as applied research in several crosscutting areas in computational science, including numerical methods, applied computational geometry and topology, high-performance computing, and geometric data analysis. After receiving his Ph.D., he was a Research Scientist at the DOE Center for Simulation of Advanced Rockets (the Rocket Center) at University of Illinois and then a Visiting Assistant Professor in College of Computing at Georgia Institute of Technology, before joining Stony Brook in 2007. At the Rocket Center, he developed a software framework and a number of underlying algorithms for integrating complex multiphysics systems for rocket simulations. Recently, he has been developing accurate and efficient techniques for moving interfaces in combustion, materials science and other application areas. He is currently a principal investigator on an NSF-sponsored project on computing optimal mappings between discrete surfaces with applications in multiphysics coupling and shape matching.
Contact - (631) 632-4408, jiao@ams.sunysb.edu.

XIAOLIN LI, Professor
Ph.D. 1987, Columbia University

As an interdisciplinary researcher in applied physics and scientific computing, Xiaolin Li’s major research objective is to design and implement a high resolution numerical method, known as the Front Tracking Method, for the study of fluid interface instabilities, such as the Rayleigh-Taylor instability and the Richtmyer-Meshkov instability. These problems are characterized by the existence of a dynamic interface that separates different materials. The interface may bend, expand, and bifurcate. The numerical method Li employs tracks the physical and topological changes of the interface. He has combined the Lagrangian and Eulerian approaches to robustly resolve the dynamic changes of the interface. This numerical method has been implemented into a software package named FronTier. Li’s research has involved collaborations with scientists at Los Alamos National Laboratory, Argonne National Laboratory, and Brookhaven National Laboratory, and the software he helped develop has been used in research for various scientific problems, such as inertial confinement fusion and the study of the fuel injection nozzle.
(631) 632-8353, linli@ams.sunysb.edu

YONG-MIN ZHANG, Assistant Professor
Ph.D. 1997, University of Chicago

Yong-Min Zhang’s research objective is to study the hydrodynamics of turbulent mixing of fluids by computer simulations. Turbulent mixture of fluids is among the most difficult problems of science. Such problems arise in the study of inertially confined fusion (ICF), high-speed combustion, and evolution of supernova. He has developed front-tracking algorithms that apply to unstable and highly singular flows. His algorithms have been successfully applied to simulations of phenomena of supernova explosions in collaboration with the Los Alamos National Laboratory, the Lawrence Livermore National Laboratory, and the University of Michigan. Before Zhang came to Stony Brook, his research focused on computational methods associated with variational inequalities. He made several important advances in improving numerical solutions to variational inequalities.
(631) 632-8552, yzhang@ams.sunysb.edu

YUEFAN DENG, Professor
Ph.D. 1989, Columbia University

Yuefan Deng concentrates his research on developing parallel computing algorithms and their scientific and engineering applications. He is working on developing efficient parallel molecular dynamics algorithms, which involve multiple time stepping and thus synchronization among participating processors so that particles moving at varying speeds are modeled properly. Deng’s group applies parallel molecular dynamics, widely employed in the physical and life sciences, as well as in engineering, to analyze large macromolecular complexes for their specificity properties. He also works on parallelizing a family of optimization techniques called simulated annealing. These algorithms are essential for breakthroughs in many computational science areas. Deng uses them for finding the parameters of a large system of ordinary differential equations—a classical inverse problem—arising in developmental genetics. In addition, Deng is developing a system to manage computation and communication resources on loosely coupled wide area network parallel platforms. This helps provide tools, and even justifications, for true global computing.
(631) 632-8614, deng@ams.sunysb.edu

Research Professor

Frey Robert, Ph.D., 1986, University at Stony Brook: quantitative finance.

Adjunct Faculty
In addition to our core faculty, our department utilizes the expertise of several other department faculty to enhance our graduate program.

Alonso, Carlos, Associate Professor, Ph.D., 1992, Federal University of Rio De Janeiro: computational biology.

Badr, Hussein G., Associate Professor, Ph.D., 1980, Pennsylvania State University: Operating systems; computer system performance evaluation.

Bender, Michael, Associate Professor, Ph.D., 1998, Harvard University, combinatorial algorithms.

Ferguson, David, Professor. Ph.D., 1980, University of California, Berkeley: Mathematics education; educational technology.

Grove, John, Professor. Ph.D., 1984, Ohio State University: Conservation laws; front tracking.

Martyna, Glenn, Professor, Ph.D., 1989, Columbia University: Molecular dynamics.

Peierls, Ronald, Professor, Ph.D., 1959, Cornell University: Parallel computing; particle physics.

Pinezich, John, Adjunct Professor, Ph.D.. 1998, SUNY at Stony Brook: Radar, ballistics, sonar, acoustics.

Dubey, Pradeep, Professor, Ph.D., 1975, Cornell University: Game theory; mathematical economics.

Sharp, David, Professor. Ph.D., 1963, California Institute of Technology: Mathematical physics; computational fluid dynamics.

Simmerling, Carlos, Associate Professor, Ph.D., 1995, University of Illinois at Chicago: Protein structcure.

Skiena, Steven, Professor, Ph.D., 1988, University of Illinois: Combinatorial algorithms; computational geometry; data structures.

Skorin-Kapov, Jadranka, Professor, Ph.D., 1988, University of British Columbia, Canada: Mathematical programming; production management.

Sokal, Robert R., Emeritus Distinguished Professor, Ph.D., 1952, University of Chicago: Numerical taxonomy; theory of systematics; geographic variation; spatial models in ecology and evolution.

Spirov, Alexander, Associate Professor, Ph.D., 1987, Irktsk State University: Computational biology.

Sheldon Weinig, Professor, Ph.D., 1955, Columbia University: Manufacturing management, material sciences.

Zemanian, Armen H. 14, Distinguished Professor, Eng.Sc.D., 1953, New York University: Network theory; food system modeling.

 

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