Dr. Zelikovitz joined the faculty of the Computer Science Departments at the College of Staten Island and the Graduate Center of CUNY in 2002. Dr. Zelikovitz's research interests lie in the use of unlabeled or background knowledge in the aid of text classification. This cutting edge research combines the areas of statistics, artificial intelligence, machine learning and information retrieval. Dr. Zelikovitz’s approach to classifying textual documents, such as technical articles, web pages, advertisements, etc. has been to incorporate readily available information to aid in this task. As a result of the explosion of the amount of digital data that is available, it is often the case that text, databases, or other sources of knowledge that are related to a text classification problem are easily accessible. She terms this additional information "background knowledge", and has incorporated background knowledge into a number of different learning algorithms.  She has funded both graduate students and undergraduate students  to work on this problem with her, and has co-authored papers with these students.


BS, Brooklyn College

MA, Brooklyn College

PhD, Rutgers University (New Brunswick)

Scholarship / Publications

Dr. Zelikovitz has published extensively in both Artificial Intelligence and Information Retrieval venues.  She has also served on numerous program committees for various Artificial Intelligence conferences, and has reviewed for journals in her field of expertise.  A list of  publications and pdf files can be retrieved from her publication page at http://www.cs.csi.cuny.edu/~zelikovi/publications.htm