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The Statistics group's main focus is applied statistics and data science where they collaborate with investigators in a range of scientific and business fields that make heavy use of sophisticated statistical methods. The statistics faculty also do extensive research on methodological questions that underlie their applied studies. Statistics faculty, alphabetically from A to Z, are Professors Hongshik Ahn, Stephen Finch, Pei Fen Kuan, Song Wu, Haipeng Xing, and Wei Zhu along with fellow statisticians and adjunct AMS faculty members Professors Wei Hou, Barbara Nemesure and Jie Yang in the School of Medicine. Their primary areas of application are biomedical research and financial statistics. Our statisticians collaborate with local biomedical researchers in the Stony Brook Medical School, nearby Brookhaven National Lab and Cold Spring Harbor Lab as well as scientists in major New York City medical centers, such as Columbia, NYU, Mt. Sinai and Sloan-Kettering, as well as other parts of US such as UNC Chapel Hill, UCLA, NCTR and internationally in China, Germany and South Korea etc. Our statistics faculty are also affiliated with the SBU Center for Finance, and collaborate actively with colleagues at the College of Business and Department of Economics, as well as financial statisticians at Columbia University, Stanford University, and the Wharton Business School at U. Penn.

Hongshik Ahn's  specialty is statistical machine learning, in particular, tree-structured regression modeling for censored survival data. After earning his Ph.D., he initially worked as a biostatistician 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 and researchers in NYU and Columbia University. His former students took positions in academia, research institutes, and pharmaceutical industry. Recently he served as the first Vice President and then founding Chair of the new AMS Department of SUNY Korea. For more information, see  Ahn webpage.

Stephen Finch  is an applied statistician whose major areas of interest are statistical genetic epidemiology and applied longitudinal data analysis. He is applying longitudinal data analysis techniques to data describing the progression of understanding the principles of evolution with Professor Ross Nehm of the Stony Brook University Biology Department. He also works with Professor Judith Brook of the New York University Langone School of Medicine to apply longitudinal data analysis methods to data on the progression of drug use and its consequences in normal populations. He is working with Professor Derek Gordon of Rutgers University to develop quantitative techniques for statistical genetic epidemiology, especially genetic associations with the longitudinal development of traits. For more information, see  Finch webpage.

Pei Fen Kuan’s  research interests focus on statistical and computational issues arising from the problems in genome biology and bioinformatics. Many of her research projects center around tiling arrays and the next generation sequencing platforms. Her research activities have been directed at developing statistical methodologies to facilitate the analysis, integration and interpretation of high-throughput omics data. Prof Kuan and her group are funded by the CDC for 9/11 WTC related health research, as well as NIH for melanoma research, see  Kuan webpage.

Song Wu  and his research group focus on developing and applying new statistical methodologies for the analysis of genetic and financial data, including big data. Specifically, his research interests are: statistical genomics (microarray, SNP array, MicroRNA array, methylation array), next-gen data analysis (WG-seq, RNA-seq, ChIP-seq, Methyl-seq), systems biology (gene network, pathway analysis), statistical learning (big data, data mining, classification), and statistical applications (longitudinal data analysis, functional data analysis, mixture models). For more information, see  Wu webpage.

Haipeng Xing  is an applied statistician whose research is focused on: (i) change-points detection, parameter estimation and adaptive control problems and their applications in engineering, economics and genetics; (ii) statistical models and methods in financial econometrics and engineering; (iii) time series modeling; (iv) stochastic control and its applications in finance and economics. He is co-author, with T.L. Lai of Stanford, of two major textbooks on financial statistics. Currently, he is working with Dr. Chris Chatfield to jointly draft the next edition of the popular textbook of “The Analysis of Time-series: An Introduction”. Prof. Xing has also served as consultant to World Bank and other financial institution. For more information, see  Xing webpage.

Wei Zhu and her team conduct research in the following directions: (1) statistical data mining and learning for unbalanced data and spatial-temporal data, (2) structural equation modeling (SEM) for joint longitudinal and contemporaneous data analysis, (3) errors in variable (EIV) modeling, new methods and applications, (4) extended autoregressive distributed lag (ADL) model and error correction model (ECM) for financial stress testing, and (5) stochastic modeling for carcinogenesis. Her former students have taken positions in academia (mathematics/statistics departments and college of business) and in a broad range of industry as data scientists, quality control managers, quantitative marketing managers, biostatisticians, financial risk managers and financial analysts. Professor Zhu served as the Deputy Chair of the AMS Department for 7 years, and is currently the AMS Graduate Program Director in charge of MS & AGC (advanced graduate certificate), as well as the Deputy Director of the SBU Center for Finance.  
For more information, see  
Zhu webpage.