Rafid Mahmood

I am an Assistant Professor at the Telfer School of Management in the University of Ottawa. I am also a part-time Sr. Research Scientist at the NVIDIA Toronto AI Lab.

I am interested in the operational challenges behind the deployment and use of AI systems. I use deep learning and data-driven optimization for problems where the typical forms of large-scale data collection and model tuning are prohibitive. My work addresses ML technology (e.g., computer vision systems), healthcare (e.g., personalized medicine), and finance (e.g., portfolio optimization). I am also interested in general data science problems (e.g., sports analytics).


Sep 14, 2022 Our paper Optimizing Data Collection for Machine Learning was accepted at NeurIPS 2022.
Mar 3, 2022 Our paper How Much More Data Do I Need? Estimating Requirements For Downstream Tasks was accepted at CVPR 2022.
Jan 24, 2022 Our paper Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach was accepted at ICLR 2022.
Oct 24, 2021 I am chairing a virtual session VMB05: Optimization for Machine Learning at the INFORMS Annual Meeting 2021.
Sep 12, 2021 Check out the pre-print of our review paper: Inverse optimization: Theory and applications.