Richard Zanibbi Headshot

Richard Zanibbi

Professor

Department of Computer Science
Golisano College of Computing and Information Sciences
rxzvcs@rit.edu
585-475-5023
Office Hours
Tues, Thurs 3:30-5pm
Office Location
GOL-3551
Office Mailing Address
Dept. Computer Science Rochester Institute of Technology 102 Lomb Memorial Drive, Rochester, NY 14623-5608

Richard Zanibbi

Professor

Department of Computer Science
Golisano College of Computing and Information Sciences

Education

BMusic; BA (minor) in Computer Science; MS in Computer Science; Ph.D. in Computer Science, Queen's University (Canada)

Bio

I am a Professor of Computer Science at RIT, where I direct the Document and Pattern Recognition Lab.  I hold a PhD and Master's in Computer Science, a BA with a minor in Computer Science, and a Bachelor of Music degree, all from Queen's University, Canada.

My research interests include information retrieval, document recognition, pattern recognition, and machine learning. Recently I co-authored a book manuscript on mathematical information retrieval for Foundations and Trends in Information Retrieval. We expect the book to be published early in 2025.

I was a Program Co-Chair for ICDAR 2023, and I previously chaired the ICFHR 2018, DRR 2012, and DRR 2013 conferences. I also serve on program committees for information retrieval conferences (e.g., SIGIR, and the new SIGIR-AP conference).

rxzvcs@rit.edu
585-475-5023
Personal Links
Personal Website
ORCID
Publication Database
Curriculum Vitae
Google Scholar
Areas of Expertise
Artificial Intelligence
Document Recognition
Human-Computer Interaction
Information Retrieval

Currently Teaching

CSCI-536
Information Retrieval
3 Credits
An introduction to the theories and techniques used to construct search engines. Topics include search interfaces, traditional retrieval models (e.g., TF-IDF, BM25), modern retrieval techniques (e.g., neural reranking and retrieval), search engine evaluation, and search applications (e.g., conversational IR, enterprise search). Students will also review current IR research topics, and complete a group project in which they will design and execute experiments for search engine components.
CSCI-636
Information Retrieval
3 Credits
An introduction to the theories and techniques used to construct search engines. Topics include search interfaces, traditional retrieval models (e.g., TF-IDF, BM25), modern retrieval techniques (e.g., neural reranking and retrieval), search engine evaluation, and search applications (e.g., conversational IR, enterprise search). Students will also review current IR research, provide written summaries of current research papers, and complete a group project in which they will design and execute experiments for search engine components.