Thong Pham

Associate Professor, Shiga University
Visiting Scientist, RIKEN AIP
Visiting Researcher, Kyoto University

prof_pic.jpg

Room 430

Data Science Building

Shiga University

Shiga, Japan

I am an associate professor (tenured) at Data Science and AI Innovation Research Promotion Center, Shiga University. I also work as a visiting scientist at Causal Inference Team, RIKEN AIP, and as a visiting researcher at Fukuma Research Group, Kyoto University Graduate School of Medicine. Previously, I was a postdoctoral researcher at RIKEN AIP. Before that, I received my Ph.D. in Statistics from Shimodaira Laboratory at Osaka University.
My research interests include network science, causal inference, and causal discovery.

news

Nov 11, 2024 We developed a causal-discovery-based method for identifying root causes of failures in machine learning models.
Feb 4, 2024 I co-authored a paper on combining large language models with causal discovery algorithms.
Jan 13, 2024 Our paper has been accepted to CLeaR 2024.
Nov 3, 2023 Our paper on causal inference with optimal transport is on arXiv.
Jun 8, 2023 I started working as a visiting researcher at Kyoto University.

fundings (as PI)

04/2024 - 03/2029 JSPS Grant-in-Aid for Early-Career Scientists 24K20741 (Direct cost: 5.0M JPY from JSPS and 2.2M JPY from Shiga University)
06/2023 - 03/2024 Research Startup Grant from Shiga University Competitive Research Fund (Direct cost: 0.9M JPY)
04/2019 - 03/2022 JSPS Grant-in-Aid for Early-Career Scientists 19K20231 (Direct cost: 2.8M JPY)
04/2016 - 03/2017 JSPS Research Fellowship for Young Scientists 16J03918 (Direct cost: 2.3M JPY)

selected publications

  1. Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosis
    Nov 2024
  2. Scalable Counterfactual Distribution Estimation in Multivariate Causal Models
    Pham, ThongShimizu, ShoheiHino, Hideitsu, and Le, Tam
    Proceedings of the Third Conference on Causal Learning and Reasoning, Apr 2024
  3. Non-parametric Estimation of the Preferential Attachment Function from One Network Snapshot
    Journal of Complex Networks, Sep 2021
  4. PAFit: An R Package for the Non-Parametric Estimation of Preferential Attachment and Node Fitness in Temporal Complex Networks
    Journal of Statistical Software, Feb 2020
  5. Joint Estimation of Preferential Attachment and Node Fitness in Growing Complex Networks
    Scientific Reports, Sep 2016
  6. PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks
    PLOS ONE, Sep 2015