Published a paper in Nature Medicine (Apr 2024): 'Causal Machine Learning for Predicting Treatment Outcomes'
Two papers accepted at NeurIPS 2024: 'Treatment Effect Estimation for Optimal Decision-Making' and 'Conformal Prediction for Causal Effects of Continuous Treatments'
One paper accepted at ICLR 2025: 'Differentially Private Learners for Heterogeneous Treatment Effects'
Two additional NeurIPS 2024 papers: 'Quantifying Aleatoric Uncertainty of the Treatment Effect' and 'DiffPO: A causal diffusion model for predicting potential outcomes of treatments'
One paper accepted at ICML 2024: 'Fair Off-Policy Learning from Observational Data'
Three papers accepted at ICLR 2024: 'A Neural Framework for Generalized Causal Sensitivity Analysis', 'Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation', and 'Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation' (Spotlight)
Three papers accepted at NeurIPS 2023: 'Sharp Bounds for Generalized Causal Sensitivity Analysis', 'Reliable Off-Policy Learning for Dosage Combinations', and 'Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model' (Spotlight)