CHAI Seminar series
We are excited to bring you the CHAI Seminar Series, organised by our Early Career Researchers (ECRs). This seminar series will provide a platform for knowledge exchange and discussion on cutting-edge research in causal AI and related fields.
Upcoming Seminars
January Seminar - Causal Effect Estimation with Context and Confounders
December Seminar - Towards Inherently Interpretable Neural Networks for Differential Diagnosis
June Seminar - How Causal AI Can Help Improve Radiation Cancer Treatments
Our June seminar “How Causal Analysis Can Help Improve Radiation Cancer Treatment” was led by Dr. Eliana Vasquez Osorio, University of Manchester.
May Seminar - On the Identifiability of Switching Dynamical Systems
Our May seminar titled “On the Identifiability of Switching Dynamical Systems”, was given by Dr Yingzhen Li, Imperial College London.
April Seminar - Regulating AI for Healthcare: Developments, Challenges, and Prospects.
Our April seminar titled “Regulating AI for Healthcare: Developments, Challenges, and Prospects.”, was given by James Lowe, University of Exeter.
Our September seminar “See, Think, Act: Training Agents by Reinforcing Reasoning” was led by Dr. Maning Li, Northwestern University.
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October Seminar - Causal Roadmap for generation of reliable Real-World Evidence with application to genomics and biomarker discovery
Our October seminar “Causal Roadmap for generation of reliable Real-World Evidence with application to genomics and biomarker discovery” will be led by Dr. Ava Khamesh, University of Edinburgh.
Past Seminars
September Seminar - See, Think, Act: Training Agents by Reinforcing Reasoning
Our December seminar “Towards Inherently Interpretable Neural Networks for Differential Diagnosis” will be led by Tom Nuno Wolf, a PhD candidate at TU Munich.
November seminar - Ambiguous Interventions and Causal Abstractions
Our November seminar “Amiguous Interventions and Causal Abstractions” will be led by Dr. Sander Beckers, University College London (UCL).
Our January seminar “Causal Effect Estimation with Context and Confounders” will be led by Professor Arthur Gretton, UCL.
February Seminar - Assessing Real-World Performance of AI-Based Neuroimaging Diagnosis Tools Through Hospital Data Warehouses
Our February seminar “Assessing Real-World Performance of AI-Based Neuroimaging Diagnosis Tools Through Hospital Data Warehouses” will be led by Ninon Burgos who is a CNRS research director at the Paris Brain Institute in France, co-head of the ARAMIS Lab, and PR[AI]RIE fellow.