Frank Rudzicz

Frank Rudzicz is a scientist at the Li Ka Shing Knowledge Institute at Unity Health Toronto, Director of Artificial Intelligence at Surgical Safety Technologies Inc., an associate professor of Computer Science at the University of Toronto, co-founder of WinterLight Labs Inc., faculty member at the Vector Institute for Artificial Intelligence, and CIFAR Chair in Artificial Intelligence.

His work is in machine learning in healthcare, especially in natural language processing, speech recognition, and surgical safety.

His research has appeared in popular media such as Scientific American, Wired, CBC, and the Globe and Mail, and in scientific press such as Nature.

Selected Publications

Kostas D, Rudzicz F (Accepted)Thinker Invariance: Enabling Deep Neural Networks for BCI Across More People, Journal of Neural Engineering.

Abdalla Moh, Abdalla Mou, Hirst G, Rudzicz F (2020) Exploring the privacy-preserving properties of word embeddings: Algorithmic validation, JMIR, 22(7):e18055.

Abdalla Moh, Abdalla Mou, Rudzicz F, Hirst G (2020) Using Word Embeddings to Improve the Privacy of Clinical Notes, JAMIA, 27(6):901-907.

Khalid S, Goldenberg M, Grantcharov T, Taati B, Rudzicz F (2020) Evaluation of Deep Learning Models for Identifying Surgical Actions and Measuring Performance, JAMA Network Open, 3(3).

Smith MJ, Axler R, Bean S, Rudzicz F, Shaw J (2020) Four Equity Considerations for AI in Public Health, Bulletin of the World Health Organization, 98:290-292.

Khattak FK, Jeblee S, Pou-Prom C, Abdalla M, Meaney C, Rudzicz F (2019) A survey of word embeddings for clinical text, Jeblee S, Gomes M, Jha P, Rudzicz F, Hirst G (2019)

Automatically determining cause of death from verbal autopsy narratives, BMC Medical Informatics, 9:127. Journal of Biomedical Informatics, 4, December.

Gordon L, Grantcharov T, Rudzicz F (2019) Explainable artificial intelligence for safe intraoperative decision support, JAMA Surgery, 154(11):1064-1065.

Shaw J, Rudzicz F, Jamieson T, Goldfarb, A (2019) Artificial intelligence and the implementation challenge, Journal of Medical Internet Research, 21(7):e13659.

Kostas D, Pang E, Rudzicz F (2019) Machine learning for MEG during speech tasks, Nature, 9:1609.

Orozco-Arroyave JR, Vasquez-Correa JC, Vargas-Bonilla JF, Arora R, Dehak N, Nidadavolu PS, Christensen H, Rudzicz F, Yancheva M, Chinaei H, Vann A, Vogler N, Bocklet T, Cernak M, Hannink J, Noth E (2018) NeuroSpeech: An open-source software for Parkinson's speech analysis, Digital Signal Processing, 77:207-221.