Ioannis Tsamardinos , Ph.D.

Adjunct Assistant Professor of Biomedical Informatics

Assistant Professor of Computer Science, University of Crete


Room 402, Eskind Biomedical Library

2209 Garland Ave

Nashville, TN

Phone: (615) 936-2880

Fax: (615) 936-1427

Email: ioannis.tsamardinos@vanderbilt.edu


Ioannis Tsamardinos, Ph.D., (Yianni) joined the faculty in November 2001 as an Assistant Professor. He earned his bachelor's degree in 1995 from the Department of Computer Science in the University of Crete, in Heraklion, in Greece. He then joined the Computer Science department of University of Pittsburgh but within a year transferred to the Intelligent Systems Program in the same university that better matched his long standing interest in Artificial Intelligence. There, he worked with Prof. Martha E. Pollack on Planning, Temporal Reasoning, and Constraint Satisfaction and earned his Ph.D. in July 2001. During the summer of 1997 he worked as an intern on the Remote Agent at NASA Ames. The Remote Agent was the first autonomous planning system that successfully controlled a spacecraft for several days during a mission, earning the NASA group achievement award. One result of his Ph.D. thesis was efficient algorithms for solving Disjunctive Temporal Problems, packaged in a system called Epilitis. At the time Epilitis was the fastest system of its kind. Epilitis is still used in the reasoning heart of Nursebot, an autonomous robot that serves as a "cognitive orthotic", assisting an elderly client in carrying out the required activities of daily life, by providing him or her with timely and appropriate reminders.

The move to Vanderbilt was something of a career change for Yianni. At Vanderbilt he started working on Bioinformatics and particular Machine Learning algorithms for Feature Selection and Causal Discovery from data and their application and evaluation on biomedical data, such as clinical data and mass throughput microarray gene expression data. He is part of the Discovery Systems Laboratory, a team of faculty, staff, and programmers working very closely together to develop appropriate machine learning algorithms for biomedical domains.