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Computational Geometry

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Estie Arkin

Professor, Ph.D., 1986
Stanford University:  Combinatorial optimization, computational geometry

Estie Arkin's primary research area is the design and analysis of algorithms that arise in network optimization, computational geometry, graph theory, scheduling, robotics, geographic information systems, computer graphics, manufacturing, and computer vision. Arkin is interested in analysis of worst-case complexity and approximation algorithms.  

Office: Math Tower P-134B
Phone: 631-632-8363  


photo not avail 2 Joseph Mitchell

Professor, Ph.D., 1986
Stanford University: Computational geometry

Joe Mitchell is one of the country’s leaders in computational geometry, which studies the design, analysis, and implementation of efficient algorithms to solve geometric problems. Hi particular interest is applications to problems in computer graphics, visualization, robotics, manufacturing, geographic information systems, and computer vision.  In the 1990’s, he chaired the National Science Foundation advisory committee in computational geometry.  A major current application is helping air traffic controllers route airplanes around bad weather.

Office: Math Tower 1-109
Phone: 631-632-8366 

Stochastic Optimization

photo not avail 2 Eugene  Feinberg

Professor, Ph.D., 1979
Vilnius University: Operations Research

Eugene Feinberg works in stochastic methods of operations research and their industrial applications.  He is one of the world leaders in Markov decision processes and its application to telecommunication, manufacturing, transportation, service and to other man-made systems. He is one of the country’s experts on optimizing electric energy transmission and forecasting energy demand. Dr. Feinberg previously held appointments at Moscow Institute of Transport Engineering (Russia ), Yale University, and MIT.

Office: Math Tower 1-110
Phone: 631-632-7189  

photo not avail 2 Jiaqiao Hu

Associate Professor, Ph.D., 2006
University of Maryland College Park: Operations Research

Jiaqiao Hu's research is focused on designing and analyzing randomized algorithms for solving Markov decision processes and global optimization problems.  He has been investigating new sampling and simulation-based techniques to overcome the computational difficulties associated with traditional methods, 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. 

Office: Math Tower 1-107
Phone: 631-632-8239  

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