Hongshik Ahn's specialty is tree-structured regression modeling for censored survival data. After earning his Ph.D., he initially worked as a statistician at the National Center for Toxicological Research (NCTR) on animal carcinogenicity, developmental toxicology, and drug stability analysis. He came to Stony Brook in 1996, but he continued working on NCTR problems while developing new collaborations with Stony Brook biomedical researchers. He worked as a biostatistician at General Clinical Research Center (GCRC) at the Stony Brook University Medical Center. Recently he is working on classification of high-dimensional data. For more information, see Ahn webpage.
Kyle Bradford’s dissertation was on the topic of adiabatic evolutions. After earning his Ph.D., he worked as a postdoctoral fellow at the University of Nevada Reno. He is currently working on machine learning to develop an algorithm for better image identification. He conducts research related to stochastic process, probability and discrete math. He has been trained in many areas of mathematics and statistics, but he has emphasized applied probability in his research such as probability approximations through the Poisson clumping technique, the coupling method, and large deviations techniques.
Tan H. Cao’s interests mainly focus on the area of Control Theory, Nonlinear and Variational Analysis, Nonsmooth Analysis and Generalized Differentiation, Optimization, and Applications. Currently, He is working on Optimal Control of a perturbed sweeping process and finding some applications to the crowd motion model.
Kazem Mahdavi’s research areas include Quantum Computation, Geometrical Group Theory, and Classical Group Theory. He is Ph.D. in mathematics as well as M.S. in mechanical engineering. After earning his Ph.D., Kazem Mahdavi worked at SUNY Potsdam from 1983 to 2006 as a Mathematics Professor. Since then, he worked at University of Texas at Tyler as Mathematics and Computer Science Professor until 2013. After visiting Ithaca College as a Visiting Professor of Mathematics, he joined SUNY Korea as a Research Professor in 2015.
Suil O's main research interests lie in extremal and spectral graph theory. One focus of his research is on understanding how the structure of a graph affects its eigenvalues and vice versa. For example, we may ask what the best upper bound for the second largest eigenvalue in a regular graph to guarantee a certain connectivity is. Another theme in his research is the analysis of graph structure in extremal problems on graphs. Extremal problems ask for the minimum or maximum of graph parameters in a certain family of graphs. See O webpage.
Surender Kumar received B.Sc. (Honors) and M.Sc. degree in Physics from University of Delhi, India in 1996 and 1998 respectively. After about a decade of academic career in a college affiliated to Himachal Pradesh University in India, he pursued his research interest in the subject, for which, he received his PhD in Physics from Shivaji University, India in 2016. His PhD work was interdisciplinary and focused on microwave-material interaction and soft synthesis techniques for nanoscale transition metal oxides. His research interests also include extensive study of the intricate relationship between crystal structure and electromagnetic properties of materials using Rietveld refinement. He is currently involved in development of multiferroic oxides for multifunctional devices, gas sensors, and high field switching materials.
Xiaolin Li’s major research objective is to design and implement a high resolution numerical method, the front tracking method, for the study of fluid interface instabilities such as the Rayleigh-Taylor instability and the Richtmyer-Meshkov instability. His research has involved collaborations with scientists at Los Alamos National Laboratory, Argonne National Laboratory and Brookhaven National Laboratory and the software has been used for research of various scientific problems such as the inertial confinement fusion and the study of fuel injection nozzle. See Li webpage.
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. His particular interest is applications to problems in computer graphics, visualization, robotics, manufacturing, geographic information systems, and computer vision. A major current application is helping air traffic controllers route airplanes around bad weather. See Mitchell webpage.
Moon W. Suh’s research areas include statistical and probability model for manufacturing and textile materials, processes and products, experimental design, regression analysis and generalized linear models, qualitative and quantitative decision models in manufacturing and management. , After earning his Ph.D., Moon W. Suh worked in both industry and academia. He was Senior Statistician & Operations Research Analayst at Burlington Industries until he joined North Carolina University. Since 2010, he was Charles A. Cannon Professor of Textile and Apparel Technology and Management, Professor of Statistics (Associate Member), and Professor of Operations Research (Regular Program Faculty) at North Carolina State University. He joined SUNY Korea in 2016.