I am currently a Postdoctoral Research Fellow at the School of Computing - National University of Singapore (NUS), working with Professors Leong Tze Yun and Arnab Bhattacharyya. My research interests include causal inference, causal discovery, and point processes.

I completed my PhD in computer science at the NUS on problems related to causal inference from observational data. I was advised by Professor Leong Tze Yun.

News

02 Aug 2022Our paper 'Adaptive Multi-Source Causal Inference from Observational Data' was accepted to CIKM 2022 full paper track!
29 Jul 2022I am awarded the Dean's Graduate Research Excellence Award!
11 Jun 2022Our paper 'Transfer Kernel Learning for Multi-source Transfer Regression' was accepted to IEEE TPAMI!
16 May 2022Our paper 'Bayesian Federated Estimation of Causal Effects from Observational Data' was accepted to UAI 2022!
09 Feb 2022I passed my PhD oral defense!
08 Aug 2021I submitted my PhD thesis!

Selected publications

  1. Bayesian Federated Estimation of Causal Effects from Observational Data.
    Thanh Vinh Vo, Young Lee, Trong Nghia Hoang, Tze-Yun Leong.
    38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022. (accepted)
  2. Adaptive Multi-Source Causal Inference from Observational Data.
    Thanh Vinh Vo, Pengfei Wei, Trong Nghia Hoang, Tze-Yun Leong.
    31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. (accepted)
  3. Transfer Kernel Learning for Multi-source Transfer Regression.
    Pengfei Wei, Thanh Vinh Vo, Xinghua Qu, Yew Soon Ong, Zejun Ma.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022. (Impact Factor: 24.314) (accepted)
  4. Life Events that Cascade: An Excursion into DALY Computations.
    Young Lee, Thanh Vinh Vo, Derek Ni, Gang Mu.
    Quantitative Models in Life Science Business, 2022. Springer. (Book chapter, to appear)
  5. Causal Modeling with Stochastic Confounders.
    Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze-Yun Leong.
    24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
  6. Z-Transforms and its Inference on Partially Observable Point Processes.
    Young Lee, Thanh Vinh Vo, Kar Wai Lim, Harold Soh.
    27th International Joint Conference on Artificial Intelligence (IJCAI), 2018.
  7. Generation Meets Recommendation: Proposing Novel Items for Groups of Users.
    Thanh Vinh Vo, Harold Soh.
    ACM Recommender Systems Conference (RecSys), 2018. (Best Long Paper Award Runner-up)
  8. Instance Reduction for Time Series Classification using MDL Principle.
    Thanh Vinh Vo, Duong Tuan Anh.
    Intelligent Data Analysis 21(3), IOS Press, 2017.

Preprints and work in progress

  1. Bayesian Learning of Causal Structure. (In progress).
    Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong.
  2. An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects.
    Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong.
  3. Learning High-dimensional Gaussians from Censored Data.
    Arnab Bhattacharyya, Constantinos Daskalakis, Themis Gouleakis, Thanh Vinh Vo, Wang Yuhao.

Services

  • PC member (reviewer): AISTATS 2022, AAAI 2023.

PhD Thesis

  • Causal Inference from Observational Data
    Advisor: Professor Leong Tze Yun