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 the 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. For more information, see Cao webpage.


Myoungshic Jhun’s interest is computer-intensive methods in statistics.  After earning his Ph.D., he worked at the University of Michigan at Ann Arbor and Korea University as a professor of Statistics. Most of his research has been focused on theoretical justifications for newly suggested methods for data analysis. Recently, he is interested in developing statistical methods for regression analysis and support vector machine to solve the problem of over-fitting and variable selection.


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.


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.


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. For more information, see O webpage.


Changsoon Park’s research is the statistical process monitoring. His Ph.D. dissertation was the nonparametric process control when the control value is not known. Since his Ph.D., he has worked on the variable sampling process control, integrated process control, economic process control, and variance component process control. Recently he also has worked on the structural equation modeling especially to the implementation of engineering fields such as the multi-stage monitoring of the modern manufacturing industries. Currently, he is focusing his research on the development of the unified approach to the process monitoring. Most of his work has been supported by the Korean National Research Fund.


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 Analyst 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.


Alex Krejci's research focuses on developing environmental sensing instruments based on open source hardware. The "maker" movement has opened up doors to low-cost sensing and lowered the knowledge barrier of entry to developing electronics. Environmental sensing data is often a limiting factor to understanding the environment. My current project is the development of a low-cost, light-weight weather station with potential for applications citizen science and aerial deployments.