Ga Wu
About
Dr. Ga Wu is an Assistant Professor in the Faculty of Computer Science at Dalhousie University, where he leads the Applied Machine Learning Research (DAMLR) Lab. His work is at the intersection of Probabilistic Machine Learning and Deep Learning, with a strong emphasis on Responsible AI and scalability. Dr. Wu’s research focuses on enabling "conditional inference" in deep generative models—allowing complex AI systems like Variational Autoencoders (VAEs) to handle missing data or specific queries more efficiently. Before his academic appointment, he held senior research positions at Twitter (working on extreme-scale recommender systems) and Borealis AI (RBC), experiences that heavily influence his lab's mission to bridge pioneering theoretical AI with robust industrial applications.
Research Performance Summary
First Recorded Paper
Bayesian model averaging naive bayes (bma-nb): Averaging over an exponential number of feature models in linear time
Year: 2015
Citations: 7
Venue: Proceedings of the AAAI Conference on Artificial Intelligence 29 (1)
Latest Recorded Paper
Resolving Lexical Bias in Edit Scoping with Projector Editor Networks
Year: 2025
Citations: 0
Venue: In Proceedings of the 42 International Conference on Machine Learning (ICML-25)
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.