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Rafid Mahmood

Mahmood, Rafid
Assistant Professor
B.A.Sc. (Honors) (University of Toronto), M.A.Sc. (University of Toronto), Ph.D. (University of Toronto)
DMS 6123
613-562-5800 x 4699
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Rafid Mahmood is an Assistant Professor at the University of Ottawa Telfer School of Management. From 2020-2022, he was a research scientist at the NVIDIA Toronto AI Lab. From 2019-2021, he was a Postgraduate Affiliate of the Vector Institute for Artificial Intelligence. He received his BASc and MASc in Electrical Engineering, as well as his PhD in Industrial Engineering, all from the University of Toronto.

Research Interests

His research interests lie along two major themes: (1) can we build predictive and prescriptive models to automate decision-making; and (2) how can we better manage the data-centric pipelines needed to operationalize these models. This research targets applications in healthcare operations and large-scale artificial intelligence (AI) systems such as autonomous vehicles. He has published in OR journals (INFORMS Journal on Optimization, OR Letters), ML conferences (ICLR, NeurIPS, CVPR), and medical journals (Medical Physics, Journal of Nutrition, Journal of Medical Systems).

Publications during the last 7 years

Papers in Refereed Journals

  • Babier, A., Zhang, B., Mahmood, R., Moore, K., Purdie, T., McNiven, A. and Chan, T.C.Y. 2021. OpenKBP: The Open-access Knowledge-Based Planning Grand Challenge and Dataset. Medical Physics, 48(9): 5549–5561.
  • Babier, A., Chan, T.C.Y., Lee, T., Mahmood, R. and Terekhov, D. 2021. An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization. INFORMS Journal on Optimization, 3(2): 119–138.
  • Wong, R.K., Pitino, M.A., Mahmood, R., Zhu, I.Y., Stone, D., Unger, S., O’Connor, D.L. and Chan, T.C.Y. 2021. Prediction of Protein and Fat Content in Human Donor Milk Using Machine Learning. The Journal of Nutrition, 151(7): 2075–2083.
  • Crowson, M.J., Dixon, P., Mahmood, R., Lee, J.W., Shipp, D., Le, T., Lin, V., Chen, J. and Chan, T.C.Y. 2020. Predicting Post-Operative Cochlear Implant Performance Using Supervised Machine Learning. Otology & Neurotology, 41(8): e1013-e1023.
  • Babier, A., Mahmood, R., McNiven, A., Diamant, A. and Chan, T.C.Y. 2020. The Importance of Evaluating the Complete Knowledge-Based Planning Pipeline. Physica Medica: European Journal of Medical Physics, 72(12): 73-79.
  • Crowson, M.J., Hamour, A., Mahmood, R., Babier, A., Lin, V., Tucci, D. and Chan, T.C.Y. 2020. AutoAudio: Deep Learning for Automatic Audiogram Interpretation. Journal of Medical Systems, 44(163).
  • Chan, T.C.Y., Diamant, A. and Mahmood, R. 2020. Sampling from the Complement of a Poly- hedron: An MCMC Algorithm for Data Augmentation. Operations Research Letters, 48(6): 744–751.
  • Babier, A., Mahmood, R., McNiven, A., Diamant, A. and Chan, T.C.Y. 2019. Knowledge-based Automated Treatment Planning with Three-dimensional Generative Adversarial Networks. Medical Physics, 47(2): 297-306.
  • Mahmood, R., Badr, A. and Khisti, A. 2016. Convolutional Codes with Maximum Column Sum Rank for Network Streaming. IEEE Transactions on Information Theory, 62(6): 3039–3052.

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