Frank Rudzicz is an Associate Professor in the Faculty of Computer Science at Dalhousie University. His research is in machine learning in healthcare, especially in natural language processing, speech, and safety. Frank completed his PhD in the Department of Computer Science at the University of Toronto and his Master’s in Electrical and Computer Engineering from McGill University. Frank is also the co-founder of several health+AI companies, some of which, like WinterLight Labs, have seen successful exits. He teaches courses on data mining, deep speech technologies, and ML in clinical medicine.
Associate Professor, Faculty of Computer Science, Dalhousie University
Associate professor (Status Only), Department of Computer Science, University of Toronto
Canada CIFAR Artificial Intelligence Chair
Research Interests
- Natural Language Processing
- Machine Learning
- Healthcare
- Speech Technologies
- Explainable AI
- Fairness in Machine Learning
Highlights
- Co-founded WinterLight Labs
- Recipient, Connaught Innovation award
- Recipient, Early Researcher Award, Ontario Ministry of Research, Innovation and Science
- Recipient, Excellence in Applied Research award, National Speech-Language & Audiology Canada
- President, Joint Special Interest Group of the Association for Computational Linguistics (ACL) and the International Speech Communication Association (ISCA), 2015-present
- Member, CIHR College of Reviewers
- Appeared in the New York Times, the Globe & Mail, Wired, Maclean’s, Space, CTV News, CBC News, the Toronto Star, Nature, and Scientific American.
Publications
Comparing pre-trained and feature-based models for prediction of Alzheimer’s disease based on speech
2021
Coughwatch: Real-world cough detection using smartwatches
2021
Machine Learning–Based Prediction of Growth in Confirmed COVID-19 Infection Cases in 114 Countries Using Metrics of Nonpharmaceutical Interventions and Cultural Dimensions: Model Development and Validation
2021
Using machine learning to predict children’s reading comprehension from linguistic features extracted from speech and writing.
2021
Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation
2021
Intraoperative Adverse Event Detection in Laparoscopic Surgery: Stabilized Multi-Stage Temporal Convolutional Network with Focal-Uncertainty Loss
2021
Deep Learning for Voice Gender Identification: Proof‐of‐concept for Gender‐Affirming Voice Care
2021
Predicting Fine-Tuning Performance with Probing
2022
Population-based incidence of invasive pneumococcal disease in children and adults in Ontario and British Columbia, 2002–2018: A Canadian Immunization Research Network (CIRN) study
2021
1211. Incidence of All-Cause Community-Acquired Pneumonia in Ontario and British Columbia, Canada, 2002-2018; a Canadian Immunization Research Network (CIRN) study
2021
System, method, and computer program for cognitive training
2021
An Evaluation of Disentangled Representation Learning for Texts
2021
A machine learning approach to chronic obstructive pulmonary disease exacerbation identification and readmission risk quantification
2021
Hierarchical cnn-transformer based machine learning
2021