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Evangelos Coutsias Coutsias

Professor, Ph.D., 1979
California Institute of Technology

Evangelos Coutsias' research has focused on the modeling of nonlinear systems and continua, using techniques of applied mathematics on problems motivated from applied physics, engineering and biology. These include asymptotics and perturbation methods for the study of stability and bifurcation phenomena in plasma physics, biology and fluid mechanics; high accuracy numerical spectral methods for solving PDEs arising in continuum mechanics; and robust numerical methods for systems of multivariate polynomials for the solution of problems of inverse kinematics arising in molecular structure studies. His present work is on the development of computational methods for the study of protein structure, especially on the kinematic geometry of protein backbones subject to constraints. Current interests focus on the refinement of protein structure and the development of computational geometric methods for the efficient exploration of macromolecular shapespaces with application to protein design and drug discovery.

Office: Math Tower 1-119
Phone: 631-632-1822 

photo not avail 2 David Green

Graduate Program Director, Associate Professor, Ph.D., 2000, MIT, Computational biology; protein interactions and networks

David Green's research is focused on computational studies of protein interactions.  Key areas include: Understanding the determinants of specificity in protein interactions through biomolecular simulation; development and application of algorithms for the design of binding interfaces; and development of tools for the study of protein-carbohydrate interactions, with a focus on the glycobiology of HIV-1 infection.  His research combines techniques from applied mathematics and models from biophysical chemistry to solve problems in biology and medicine.

Office: Math Tower P-137
Phone: 631-632-9344   

Dima Photo Dima Kozakov

Assistant Professor, Ph.D., 2006
Boston University; Computational Biology

Dr. Kozakov research interests lie at the intersection of applied mathematics, physics and computational biology. He focuses on two main goals. The first is the development of mathematically elegant, computationally efficient and physically accurate algorithms for modeling macromolecular structure and function on the genome scale. The second is the application of novel methods to improving the understanding of biological problems and to the design of therapeutic molecules with desired biological and biomedical properties.

Office: Math Tower, 1-116
Phone: 631-632-8368 

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Tom MacCarthy

Assistant Professor, Ph.D.
University College London, 2005,Computational Biology;

Tom MacCarthy’s research uses computational modeling to study fundamental biological questions in both immunology and evolutionary biology. In Computational Immunology he uses computational and statistical methods to better understand the mechanisms underlying the generation of antibody diversity in response to infection and disease. In Evolutionary Systems Biology he uses modeling to study the evolution of gene regulatory networks with the aim of revealing the forces driving changes in developmental networks and the causes underlying the evolution of robustness, or tolerance to failure, in these networks.

Office: Math Tower 1-101
Phone: 631-632-1739 

photo not avail 2 Robert Rizzo

Professor, Ph.D., 2001
Yale University: Computational biology; drug design

Rob Rizzo works in Computational Structural Biology. His research group seeks to understand the atomic basis for molecular recognition for specific biological systems involved in human disease such as HIV/AIDS, cancer, and influenza with the ultimate goal of developing new and improved drugs.  Computational methods are used to model how molecules interact at the atomic level with a given drug target.  The resultant 3D structural and energetic information is used to quantify and rationalize drug-binding for known systems and to make new predictions.

Office: Math Tower 1-111
Phone: 631-632-9340  


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