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Data Mining

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Faculty

Picture of Daniel Larose

Daniel Larose, Ph.D.
Data Mining Program Director
Professor of Statistics
Department of Mathematical Sciences
larosed@ccsu.edu 

Professor Larose received his Ph.D. in Statistics from the University of Connecticut in Storrs in 1996 (Dissertation: Bayesian Approaches to Meta-Analysis, Advisor: Dipak Dey).  He is the author of Discovering Knowledge in Data: An Introduction to Data Mining (Wiley, 2005), Data Mining Methods and Models (Wiley, 2006), and the co-author (with Dr. Zdravko Markov) of Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage (Wiley, 2007). He is the author of Discovering Statistics, an undergraduate statistics textbook to be published by W.H. Freeman in 2009.  His consulting work includes a $750,000 Phase II grant from the Air Force Office of Research, Storage Efficient Data Mining of High Speed Data Streams.  He is the Series Editor for the new Wiley Series on Methods and Applications in Data Mining.  Since 1998, he has taught dozens of online courses, in both statistics and data mining.  For the data mining program, he teaches Stat 521 Intro to Data Mining, Stat 522 Data Mining Methods, and Stat 523 Applied Data Mining and Stat 525 Web Mining.   Dr. Larose lives in Tolland, CT with his wife Debra, daughters Chantal and Ravel, and son Tristan.   More information may be found at www.math.ccsu.edu/larose/.  

Picture of Daniel S. Miller

Daniel S. Miller, Ph.D.
Professor of Statistics
Department of Mathematical Sciences
millerds@ccsu.edu

Dr. Miller received his Ph.D. in Statistics from the University of Connecticut in 1989.  He has been on the faculty of CCSU for 20 years teaching statistics and actuarial science courses of all levels.  In 1998 he co-developed and has twice co-taught a self-supported on-line review course for the Casualty Society of Actuaries Part 4A examination.  He has collaborated with faculty from other disciplines and the Center for Social Research as a surveying and statistical analysis expert, resulting in publication and expert witness testimony.  For the data mining program, he teaches Stat 416 Mathematical Statistics II, Stat 570 Applied Multivariate Analysis, and Stat 521 Intro to Data Mining.

Zdravko Markov, Ph.D.
Associate Professor of Computer Science
Department of Computer Science
markovz@ccsu.edu

Dr. Zdravko Markov has an M.S. in Mathematics and Computer Science and a Ph.D. in Artificial Intelligence. He has been teaching and doing research in the area of Machine Learning and Data Mining for more than 10 years. Dr. Markov has published 3 textbooks (two in Machine Learning) and more than 40 research papers in conference proceedings and journals. He has been teaching at CCSU for 6 years in the areas of Computer Architecture and Design, Computing and Communication technology, Machine Learning and Data Mining. His graduate courses are offered in two graduate programs at CCSU - Computer Information Technology and Data Mining.  For the data mining program, he teaches CS 580 Data Mining and CS 570 machine Learning.

Roger Bilisoly, Ph.D.
Associate Professor of Statistics
Department of Mathematical Sciences  
bilisolyr@ccsu.edu

Dr. Bilisoly received his Ph.D. in Statistics from The Ohio State University and his M.S. in Mathematics from Purdue University.  Prior to coming to CCSU in 2004, he was a senior member of technical staff at Sandia National Laboratories in the Geohydrology Department, where he worked on both geostatistical and optimization projects.  His current areas of interest include data mining, analysis of scientific data, and spatial statistics.  For the data mining program, Dr. Bilisoly teaches Stat 521, Introduction to Data Mining, and Stat 527, Text Mining.

Darius Dziuda, Ph.D.
Assistant Professor of Statistics and Data Mining 
Department of Mathematical Sciences
dziudadad@ccsu.edu

Dr. Darius Dziuda has a Ph.D. in Computer Science and extensive academic and biotech experience in data mining and biomarker discovery.  His research and professional activities have been focused on efficient data mining of biomedical data sets, and on identification of small and acurate multivariate markers for genomics, proteomics, drug discovery, and medical diagnosis and prognosis.  He is a consultant in bioinformatics and author of the MbMD data mining software system for biomarker discovery.  His recent and ongoing collaborations include research projects with Baylor College of Medicine and Virginia Bioinformatics Institute.  For the data mining program, he teaches Stat 526 Data Mining for Genomics and Proteomics, and a course in Biomarker Discovery.







Krishna Saha, Ph.D.
Assistant Professor of Statistics
Department of Mathematical Sciences
sahakrk@ccsu.edu

Dr. Saha received his Ph.D. in Statistics from the University of Windsor in Canada in 2004, and his doctoral dissertation was in the area of biostatistics. At different universities, he has taught a range of statistics and mathematics courses and worked as a statistical consultant. Prior to coming to CCSU in 2005, he was Assistant Professor in the University of British Columbia Okanagan and Postdoctoral fellow in the University of Windsor. His ongoing research has been focused in the area of biostatistics, generalized linear models, zero-inflated and over-dispersed discrete data modeling, analysis of biomedical data sets, and non-linear regression analysis. He has publications on some of these areas in Biometrics and Statistics in Medicine.  For the data mining program, he teaches Stat 521 Intro to Data Mining and Stat 567 Linear Models.