Data mining involves developing techniques rooted in statistics and machine
learning to efficiently extract meaningful and useful information from large
collections of data.
I have made contributions to the analytical foundations
of this field, as well as to applications within
personalized information systems.
Please note that I take great care to safeguard any private
personal information that is needed in my work.
Much of my recent work involves the modeling of data arising in
human sleep studies,
in collaboration with colleagues and students at WPI.
I have also collaborated with medical colleagues from the
U. of Massachusetts Medical School.
We've developed a variety of approaches, from probabilistic clustering
to deep learning.
We've also applied data mining techniques in
My earliest work in data mining focused on the paradigm of
(e.g., Lin*, W.-Y., Alvarez, S. A., Ruiz, C.,
"Efficient Adaptive-Support Association Rule Mining for Recommender Systems",
Data Mining and Knowledge Discovery, Vol. 6, No. 1, pp. 83-105, Jan. 2002).
Selected papers on data mining (asterisks * denote student co-authors)
M. Sokolovsky*, F. Guerrero*, S. Paisarnsrisomsuk*, C. Ruiz, and S. A. Alvarez.
Deep learning for automated feature discovery and classification of sleep stages,
IEEE / ACM Transactions on Computational Biology and Bioinformatics,
to appear (2019)
Near-final version available here.
S. Paisarnsrisomsuk*, M. Sokolovsky*, F. Guerrero*, C. Ruiz, and S. A. Alvarez.
Deep Sleep: convolutional neural networks for predictive modeling of human sleep time-signals, KDD 2018 Deep Learning Day, 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, Aug. 2018
S. A. Alvarez, E. Winner, A. Hawley-Dolan, L. Snapper*. What gaze fixation and pupil dilation can tell us about perceived differences between abstract art by artists vs. by children and animals, Perception, 44(11): 1310-1331 (Nov. 2015)
Near-final version available
S. A. Alvarez and C. Ruiz.
``Collective probabilistic dynamical modeling of sleep stage transitions'',
short paper, Proc. Sixth International Conference on Bio-inspired Systems
and Signal Processing (BIOSIGNALS 2013), in conjunction with the Sixth
International Joint Conference on Biomedical Engineering Systems and
Technologies (BIOSTEC 2013), Barcelona, Catalunya, Spain, Feb. 11-14, 2013
A. Khasawneh*, S. A. Alvarez, C. Ruiz, S. Misra*, and M. Moonis.
"Discovery of sleep composition types using expectation-maximization",
Proc. 23rd IEEE International Symposium on Computer-Based Medical Systems
(CBMS 2010), Perth, Australia, Oct. 12-15, 2010
J. Hayward*, S. A. Alvarez, C. Ruiz, M. Sullivan, J. Tseng, and G. Whalen.
"Machine learning of clinical performance in a pancreatic cancer database",
Artificial Intelligence in Medicine, special issue on Data Mining
Approaches to the Study of Disease Genes and Proteins (Sun Kim, ed.),
vol. 49, issue 3, July 2010, 187-195
P. Laxminarayan*, S.A. Alvarez, C. Ruiz, and M. Moonis.
"Mining statistically significant associations for exploratory
analysis of human sleep data",
IEEE Transactions on Information Technology in Biomedicine,
Vol. 10, No. 3, 440-450, July 2006
- Lin*, W.-Y., Alvarez, S. A., Ruiz, C.,
"Efficient adaptive-support association rule mining for recommender systems",
Data Mining and Knowledge Discovery,
Vol. 6, No. 1, pp. 83-105, Jan. 2002