Ga Wu, Dalhousie University

Research

Deep Learning Conversational System Deep Generative Model Large-scale Application Probabilistic Graphical Model Recommender System Reliable Machine Learning Responsible AI

Latest funding

Trustworthy Retrieval Augmented Generation for General Population Facing Services
NSERC · 2025 · Principal investigator
$16,662
Towards Unbiased, Robust and Highly Scalable User Preference Estimation on Social Media Platforms
NSERC · 2023 · Principal investigator
$62,000
Towards Unbiased, Robust and Highly Scalable User Preference Estimation on Social Media Platforms
NSERC · 2023 · Principal investigator
$12,500

All 3 grants and awards

Trustworthy Retrieval Augmented Generation for General Population Facing Services

Principal investigatorNSERC2025Research Tools and Instruments

Principal investigators: Wu, Ga

Keywords: machine learning; ai safety; retrieval augmented generation; trustworthy ai; deep learning

$16,662

Towards Unbiased, Robust and Highly Scalable User Preference Estimation on Social Media Platforms

Principal investigatorNSERC2023Discovery Grants Program - Individual

Principal investigators: Wu, Ga

Keywords: recommender system; user preference estimation; responsible ai; reliable machine learning; deep learning; probabilistic graphical model; deep generative model; large-scale application; conversational system

$62,000

Towards Unbiased, Robust and Highly Scalable User Preference Estimation on Social Media Platforms

Principal investigatorNSERC2023Discovery Launch Supplement

Principal investigators: Wu, Ga

$12,500

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

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Applying for

Mention their NSERC grant from 2025

Subject: Prospective PhD student: Deep Learning Dear Professor Wu, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. Your research on deep learning connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your NSERC-funded project "Trustworthy Retrieval Augmented Generation for General Population Facing Services" (2025), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]