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Faculty
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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/. |
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- 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. |
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- 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. |
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Roger Bilisoly,
Ph.D.
Assistant Professor of Statistics
Department of Mathematical Sciences
bilisolyr@ccsu.edu
Dr. Bilisoly
received his Ph.D. in Statistics from The Ohio State
University in 1998 and his M.S. in Mathematics from
Purdue
University
in 1986. 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. |
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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. |
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- Chun
Jin,
Ph.D.
- Professor of Statistics
- Department
of Mathematical Sciences
- jinc@ccsu.edu
Professor
Jin has taught a wide range of statistics courses at
CCSU. He has considerable research experience in
Decision Theory and Multivariate Analysis, and has published
many research articles in these fields. He is a co-author of the
Handbook of Exponential Distributions, which
will be published by Chapman & Hall / CRC soon, and
has also
co-authored a textbook, Ready, Set, Run! A Student Guide
to SAS Software for Microsoft Windows. He
teaches Stat 315 Mathematical Statistics I. |
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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. |
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