talk

Invited Talks

• 2024/07. International Conference on Frontiers of Data Science. “Causal Discovery with Fewer Independence Tests”.
• 2024/05. American Causal Inference Conference (ACIC). “Learning Causal Representations: Identifiability and Extrapolation to Unseen Interventions”.
• 2024/04. MIT Health Science Technology (HST) Conference. “Optimal Experimental Design for Genetic Perturbation”.
• 2024/03. Online Causal Inference Seminar (OCIS). Discussant on “Towards Causal Foundation Models: on Duality between Causal Inference and Attention”.
• 2024/02. Bellairs Workshop on Causality. “Causal Representation Learning in Genomics”.
• 2023/12. Causality, Abstraction, Reasoning, & Extrapolation (CARE) Seminar. “Causal Representation Learning via Soft Interventions: Identifiability and Combinatorial Extrapolation”.
• 2023/11. Models, Inference & Algorithms (MIA) Seminar. “Causal representation learning of genetic perturbations: identifiability and combinatorial extrapolation”.
• 2023/07. Relation Therapeutics. “Causal Representation Learning of Genetic Perturbation using Discrepancy-based Auto-encoding Bayes”.
• 2023/04. Cell Circuits and Epigenomics (CC&E) Seminar. “Causal Learning and Optimal Design of Genetic Perturbation”.
• 2023/01. Causality Seminar. “Experimental Design in Causal Model”.
• 2022/11. Klarman Cell Observatory (KCO) Seminar. “Active Learning for Optimal Intervention Design in Causal Models for Biological Applications”.
• 2022/10. Online Causal Inference Seminar (OCIS). Talked about “Active learning for optimal inrtervention design in causal model”.

Online Videos

Causal Representation Learning of Genetic Perturbations

Causal Representation Learning via Soft Interventions: Identifiability and Combinatorial Extrapolation

Active Learning for Optimal Interventions in Causal Models