I am currently a 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
07 April 2023 | Our paper 'Discovering Low-Dimensional Causal Pathways between Multiple Interacting Neuronal Populations' was just accepted to CogSci 2023 as full paper publication. |
04 Jan 2023 | Our paper 'Hierarchical Reinforcement Learning with Human-AI Collaborative Sub-Goals Optimization' was just accepted to AAMAS 2023 as an extended abstract. |
08 Oct 2022 | I received the NeurIPS 2022 Scholar Award. |
15 Sep 2022 | Our paper 'An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects' was accepted to NeurIPS 2022. |
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. |
Selected publications
- Hierarchical Reinforcement Learning with Human-AI Collaborative Sub-Goals Optimization.
Haozhe Ma, Thanh Vinh Vo, Tze-Yun Leong.
22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023.
(extended abstract)
[PDF] - Discovering Low-Dimensional Causal Pathways between Multiple Interacting Neuronal Populations.
Evangelos Sigalas, Thanh Vinh Vo, Tze-Yun Leong, Camilo Libedinsky.
45th Annual Meeting of the Cognitive Science Society (CogSci), 2023.
(full paper)
[PDF] - An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects.
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong.
36th Conference on Neural Information Processing Systems (NeurIPS), 2022.
[PDF] [OpenReview] [Supplementary] [Slides] [Poster] [Code] - 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.
[PDF] [OpenReview] [Supplementary] [Code] - 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.
(full paper track)
[PDF] [Slides] [Code] - 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)
[PDF] - 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.
[PDF] - 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.
[PDF] [Supplementary] [Code] - 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.
[PDF] - 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
- Federated Learning of Causal Effects from Incomplete Observational Data.
Thanh Vinh Vo, Young Lee, Tze-Yun Leong.
[PDF] - A Distribution Over DAGs for Uncertain Causal Discovery.
Thanh Vinh Vo, Young Lee, Arnab Bhattacharyya, Tze-Yun Leong. - Mixed-Initiative Bayesian Sub-Goal Optimization in Hierarchical Reinforcement Learning.
Haozhe Ma, Thanh Vinh Vo, Tze-Yun Leong.
Services
- PC member (reviewer): AISTATS 2022, AISTATS 2023, AISTATS 2024, AAAI 2023, AAAI 2024, UAI 2023, ICLR 2024, NeurIPS 2023.
- Journal reviewer: Expert Systems with Applications