Pascal Poupart

Machine Learning, including Reinforcement Learning, Federated Learning, Continual Learning, Self-Supervised Learning, Meta Learning, Few Shot Learning, Causal Learning, Uncertainty Quantification and Calibration Applications of Machine Learning in Natural Language Processing (Conversational Agents, Grammar Error Correction, Automated Text Editing) and Material Design (Bayesian Optimization of catalysts, oxygen carriers and other materials to facilitate desirable chemical reactions for CO2 conversion and CO2 capture)

Pascal Poupart is Professor at the University of Waterloo, affiliated with Computer Science, Data Science. This summary considered 2 collected sources. Listed research or teaching areas include Machine Learning, including Reinforcement Learning, Federated Learning, Continual Learning, Self-Supervised Learning, Meta Learning, Few Shot Learning, Causal Learning, Uncertainty Quantification and Calibration Applications of Machine Learning in Natural Language Processing (Conversational Agents, Grammar Error Correction, Automated Text Editing) and Material Design (Bayesian Optimization of catalysts, oxygen carriers and other materials to facilitate desirable chemical reactions for CO2 conversion and CO2 capture).