I am currently a postdoctoral research scientist at Columbia University, under the direction of Prof. Elias Bareinboim in the Computer Science Department. Prior to Columbia, I graduated with a Ph.D. in Applied Mathematics from the University of Cambridge under the supervision of Prof. Mihaela van der Schaar.

My research focuses on causal inference, hypothesis testing, and its applications, most notably in healthcare. I intend to broaden the use of causal insights to improve the robustness and interpretability of machine learning algorithms, as well as extend existing causal inference and causal discovery algorithms to handle modern heterogeneous datasets that inevitably manifest many complexities for algorithm development, such as high-dimensionality, biases, and missing data.

Publications on Causality

► Consistency of mechanistic causal discovery in continuous-time using Neural ODEs
Alexis Bellot, Kim Branson, Mihaela van der Schaar.
Preprint available, 2021.
► Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding
Alexis Bellot, Mihaela van der Schaar.
Preprint available, 2021.
► Accounting for Unobserved Confounding in Domain Generalization
Alexis Bellot, Mihaela van der Schaar.
Preprint available, 2020.
► Policy Analysis using Synthetic Controls in Continuous-Time
Alexis Bellot, Mihaela van der Schaar.
To appear in International Conference of Machine Learning, 2021.
► Learning Overlapping Representations for the Estimation of Treatment Effects
Yao Zhang, Alexis Bellot, Mihaela van der Schaar.
Conference on Artificial Intelligence and Statistics, 2020.

Publications on Hypothesis Testing

► Kernel Hypothesis Testing for Set-valued Data
Alexis Bellot, Mihaela van der Schaar.
To appear in Conference on Uncertainty in Artificial Intelligence, 2021.
► A Kernel Two-Sample test for Unbiased Decisisons
Alexis Bellot, Mihaela van der Schaar.
To appear in Conference on Uncertainty in Artificial Intelligence, 2021.
► Conditional Independence Testing using Generative Adversarial Networks
Alexis Bellot, Mihaela van der Schaar.
Conference on Neural Information Processing Systems (Spotlight presentation), 2019.

Publications on Modelling Healthcare Data

► Learning Dynamic and Personalized Comorbidity Networks
Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Jem Rashbass, Mihaela van der Schaar.
Conference on Artificial Intelligence and Statistics, 2020.
► A Bayesian Approach to Modelling Longitudinal Data in Electronic Health Records
Alexis Bellot, Mihaela van der Schaar.
ACM Computing in Helthcare, 2020, and Machine Learning for Health Workshop at Neurips, 2019.
► Boosting Transfer Learning with Survival Data from Heterogeneous Domains
Alexis Bellot, Mihaela van der Schaar.
Conference on Artificial Intelligence and Statistics, 2019.
► Multitask Boosting for Survival Analysis with Competing Risks
Alexis Bellot, Mihaela van der Schaar.
Conference on Neural Information Processing Systems, 2018.