Martin Radfar (PhD, University of Toronto)
Assistant Professor of Practice
Room 131, Dept. of Computer Science,
Stony Brook University, New York, USA
Also affiliated with:
Institute for AI-Driven Discovery and Innovation at Stony Brook University
"Everything should be made as simple as possible, but not simpler." (A.E.)
- Voice-based human-machine interface and auditory scene analysis.
- Developing fast and large-scale learning and inference methods for Bayesian networks.
- Natural language processing for speech alignment.
- Cancer drug target prediction using large-scale machine learning analysis of genomic data and networks.