Computer Science

Contact Information

Office:
Fuller Laboratories, 232
Phone: +1-508-831-5640
Fax: +1-508-831-5776
ruiz@wpi.edu

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Carolina Ruiz

Carolina Ruiz's research interests are in data mining, machine learning, and artificial intelligence. Together with her graduate and undergraduate students, colleagues in computer science and biology, and medical doctors, Ruiz investigates and develops data mining algorithms for genomics and for clinical medicine. In addition to being a faculty member in computer science, she is a founder and active member of the bioinformatics and computational biology program at WPI. She enjoys teaching courses, and advising undergraduate and graduate research projects in data mining and machine learning.

Research Interests

  • Data Mining
  • Machine Learning
  • Artificial Intelligence
  • Genomics
  • Clinical Medicine

Education

  • BS, Computer Science, Universidad de Los Andes, 1988
  • BS, Mathematics, Universidad de Los Andes, 1989
  • MS, Computer Science, Universidad de Los Andes, 1990
  • Ph.D., Computer Science, University of Maryland College Park, 1996

Featured Publications

  • Y. Gong, J. Beck, C. Ruiz. "Modeling Multiple Distributions of Student Performances to Improve Predictive Accuracy." Proc. of the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP 2012). Montreal, Canada. July 16-20, 2012.
  • S.A. Alvarez, C. Ruiz , T. Kawato, and W. Kogel. Neural expert networks for faster combined collaborative and content based recommendation. Journal of Computational Methods in Sciences and Engineering (JCMSE). IOS Press. Vol. 11, N. 4, pp. 161-172. 2011.
  • Z. Guo, M. Ward, E. Rundensteiner, C. Ruiz. "Pointwise Local Pattern Exploration for Sensitivity Analysis", (acceptance rate = 32%). Proc. IEEE Conference on Visual Analytics Science and Technology (IEEE VAST2011). Providence, RI, Oct. 23-28, 2011.
  • A. Khasawneh, S. A. Alvarez, C. Ruiz, S. Misra, and M. Moonis. "EEG and ECG Characteristics of Human Sleep Composition Types", full paper (acceptance rate = 48/538 = 8.92%). Proc. Fourth International Conference on Health Informatics (HEALTHINF 2011), in conjunction with the Fourth International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2011), pp. 97-106, Rome, Italy, Jan. 26-29, 2011. *Best Paper Award*
  • 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, vol. 49, issue 3, pp. 187-195, July 2010.

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