Meet Our Team

Dr. Ophir Frieder

Georgetown University
Department of Computer Science

Ophir Frieder holds the Robert L. McDevitt, K.S.G., K.C.H.S. and Catherine H. McDevitt L.C.H.S. Chair in Computer Science and Information Processing and previously served as the Chair of the Department of Computer Science at Georgetown University. He is also Professor of Biostatistics, Bioinformatics and Biomathematics in the Georgetown University Medical Center. In addition to his academic positions, he is the Chief Scientific Officer for UMBRA Health Corp.(UHC) and a Research Associate at the Institute of Information Science and Technology at the Italian National Research Council (ISTI-CNR). He is a Fellow of the AAAS, ACM, IEEE, and NAI, and a Member of the European Academy of Sciences and Arts.

Dr. David Grossman

Associate Director of the Information Retrieval Lab

Dr. Grossman is currently a faculty affiliate at Georgetown. He was a tenured Associate Professor of Computer Science at the Illinois Institute of Technology from 2005-2012. He earned his B.S. in Computer Science from Clemson University, his M.S. in Computer Science from American University and a Ph.D. in Information Technology from George Mason University. He has co-authored two books: Computer Science Programming Basics in Ruby and Information Retrieval: Algorithms and Heuristics and, has published over seventy-five papers and was the director of the IIT Information Retrieval Lab. He teaches information retrieval, data mining courses, and information security courses. His research focuses on the problems surrounding the integration of structured and unstructured data and using machine learning to improve search. He is currently the chair of the steering committee for the Conference on Information and Knowledge Management. At present he is a consultant on a number of large search-related projects.

Roman Yurchak, PhD

Data Scientist & Founder of Symerio SAS

Roman graduated from ENS Cachan in applied physics. During his PhD at Ecole Polytechnique, he was working on predictive modeling of laboratory astrophysics experiments using massively parallel simulation codes. At present, he is involved in data science projects in predictive modeling, semi-supervised learning and information retrieval.

Eugene Yang

Candidate, Doctor of Philosophy in Computer Science

Georgetown Univ. – Candidate, Doctor of Philosophy
National Tsing Hua Univ – Bachelor of Science