Recruiting

I am actively looking for self-motivated students interested in data science and machine learning, especially in graph neural networks, information retrieval, recommender systems, time series etc.

Research interests:

  1. Graph Neural Networks
    • Text-attributed graph and multimodal graph with (M)LLMs
    • Graph foundation models
    • Robustness and scalability of graph learning (OOD, test-time, condensation, distillation, graph-MLP etc.)
  2. Recommendations and Information Retrieval
    • RL for recommendations
    • Rich side-information in recommendations with (M)LLMs
    • Domain-specific IR and document understanding with LLMs
  3. Time Series
    • Foundation models for time series
    • LLMs for time series
    • Time series for cross-disciplinary applications

For UQ’s master/undergraduate students

UQ master/bachelor programs have (Type 1) thesis project, capstone projects and honours project (with 6 or 8 units for one year) and (Type 2) summer/winter/internship project (no unit). These projects can be towards research paper/cross-disciplinary project. If you want to have research outcome such as a paper, please consider doing a Type 2 project and then a Type 1 project with me.

Students are expected to have either (1) a high GPA in math, algorithm, ML/DL/DM courses; or (2) a good understanding of fundamental ML/DL/DM knowledge equivalent to anyone of the following: CS229， CS231n, CS224n, or CS224w from Stanford, or RL from DeepMind&UCL, or CS285 from Berkeley, or STAT3006/STAT3007 from UQ. If you don’t have a good GPA, please take any of these courses first. If you want to do your thesis/project with me, welcome to email me.

Email me “r.last-name-lowwer-case@uq.edu.au”:

  1. Email topic: “UQ CS Thesis Application by Your Name”.
  2. Please attach your CV, transcripts and a representative writing sample (paper/preprint) if any.
  3. Please customize your email according to my research interest and be specific about your research interest, in several sentence.