About

I am currently a doctoral student in Computer Science at the National University of Singapore, working with Professors Leong Tze-Yun and Arnab Bhattacharyya. My research interests include causal inference, causal discovery, and point processes.

Preprints

  • Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong. Bayesian Learning of Causal Structure.
  • Thanh Vinh Vo, Pengfei Wei, Trong Nghia Hoang, Tze-Yun Leong. Adaptive Multi-Source Causal Inference. arXiv.
  • Thanh Vinh Vo, Young Lee, Trong Nghia Hoang, Tze-Yun Leong. Federated Estimation of Causal Effects from Observational Data. arXiv.
  • Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong. Random Fourier Features for Federated Learning of Causal Effects.
  • Pengfei Wei, Thanh Vinh Vo, Zejun Ma. Dynamic Adaptive Transfer Kernel Learning.
  • Pengfei Wei, Thanh Vinh Vo, Xinghua Qu, Yew Soon Ong, Zejun Ma. Transfer Kernel Learning for Multi-source Transfer Regression.

Selected publications

  • Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze-Yun Leong. Causal Modeling with Stochastic Confounders. International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
  • Young Lee, Thanh Vinh Vo, Kar Wai Lim, and Harold Soh. Z-Transforms and its Inference on Partially Observable Point Processes. International Joint Conference on Artificial Intelligence (IJCAI), 2018.
  • Thanh Vinh Vo, Harold Soh. Generation Meets Recommendation: Proposing Novel Items for Groups of Users. ACM Recommender Systems Conference (RecSys), 2018. (Best Long Paper Award Runner-up)
  • Thanh Vinh Vo, Duong Tuan Anh. Instance Reduction for Time Series Classification using MDL Principle. Intelligent Data Analysis 21(3), IOS Press, 2017.

Teaching

GAP teaching assistant at National University of Singapore, 2017-2020.

  • Programming methodology
  • Data structures and algorithms