Featured Faculty

College of Art and Design College of Engineering Technology College of Health Sciences and Technology College of Liberal Arts College of Science Golisano College of Computing and Information Sciences Golisano Institute for Sustainability International Campuses Kate Gleason College of Engineering National Technical Institute for the Deaf Saunders College of Business School of Individualized Study
portrait of Richard Zanibbi

Richard Zanibbi

Golisano College of Computing and Information Sciences

Richard Zanibbi is a Professor in the Computer Science Department of GCCIS, where he directs the Document and Pattern Recognition Lab (DPRL). Dr. Zanibbi received his BMusic, BA (minor, Computer Science), MSc, and PhD degrees from Queen's University, Canada. He was an NSERC postdoctoral fellow at the Centre for Pattern Recognition and Machine Intelligence in Montréal during 2005-2006, before starting as an Assistant Professor at RIT in Fall 2006. He has held a cross-appointment in the RIT Center for Imaging Science since 2009.

The DPRL focuses on the extraction and search of graphical information in documents, images, and videos. In April 2020, the lab released MathDeck, a novel search interface combining multi-modal math input (i.e., from handwriting, typing, and images) with formula autocompletion, text and math-searchable formula concept cards, and sending queries containing keywords and formulas to various search engines. MathDeck is part of the MathSeer project led by Dr. Zanibbi, funded by the NSF and Alfred P. Sloan foundation, and being run in collaboration with faculty and students from Penn State and the University of Maryland. MathSeer's primary goal is developing 'math search for the masses,' including a math-aware extension of the well-known CiteSeerX technical document search engine.

Dr. Zanibbi is also a member of the Molecule Maker Lab Institute (MMLI) based at the University of Illinois. In August 2020, the MMLI received $20M as one of the first NSF-sponsored AI research centers in the United States. For the MMLI project, the DPRL is extending their work with math formulas to chemical diagrams, and collaborating with MMLI members on extracting and organizing information from the chemical literature into graphs used to drive AI systems for chemical synthesis planning. A key goal of the MMLI project is creating improved materials for solar cells.

Richard Zanibbi
Professor
Golisano College of Computing and Information Sciences Computer Science

View All submissions by Richard Zanibbi