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 2022 | Our paper 'Adaptive Multi-Source Causal Inference from Observational Data' was accepted to CIKM 2022 full paper track! |
29 Jul 2022 | I am awarded the Dean's Graduate Research Excellence Award! |
11 Jun 2022 | Our paper 'Transfer Kernel Learning for Multi-source Transfer Regression' was accepted to IEEE TPAMI! |
16 May 2022 | Our paper 'Bayesian Federated Estimation of Causal Effects from Observational Data' was accepted to UAI 2022! |
09 Feb 2022 | I passed my PhD oral defense! |
08 Aug 2021 | I submitted my PhD thesis! |
Selected publications
- 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) - 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) - 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) - 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) - 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. - 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. - 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) - 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
- Bayesian Learning of Causal Structure. (In progress).
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong. - An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects.
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong. - 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