This is a one-day workshop with no restrictions on attendance. The workshop is open to researchers, practitioners, and industry professionals interested in AI with causal techniques. There are no specific criteria or maximum number of attendees. The specific time schedule is shown below:

9:00am - 9:05am Welcome Remarks

9:05am - 9:35am Keynote Talk 1: Causal Inference with Large Language Model

Jing Ma, Case Western Reserve University

9:35am - 9:55am Oral Talk 1: A Causal World Model Underlying Next Token Prediction in GPT

Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu, Estelle Aflalo, Vasudev Lal (Intel Labs)

9:55am - 10:30am Poster Session 1

10:30am - 11:00am Coffee Break

11:00am - 11:30am Keynote Talk 2: Possibility and Impossibility of Real World Causal Inference

Konrad Körding, University of Pennsylvania

11:30am - 11:50am Oral Talk 2: Integrating Transfer Entropy into Transformer for Time Series Forecasting

YongKyung Oh, Alex Bui (University of California, Los Angeles)

11:50am - 12:10pm Oral Talk 3: Constrained Identifiability of Causal Effects

Yizuo Chen, Adnan Darwiche (University of California, Los Angeles)

12:10pm - 12:30pm Oral Talk 4: Time-Varying Causal Survival Learning

Xiang Meng, Iavor Bojinov (Harvard University)

12:30pm - 2:00pm Lunch Break

2:00pm - 2:20pm Oral Talk 5: Causal Discovery for Cloud Microservice Architectures

Christopher Lohse (IBM Research Europe, Dublin & University of Dublin Trinity College), Diego Tsutsumi, Amadou Ba (IBM Research Europe, Dublin), Pavithra Harsha, Chitra Subramanian, Martin Straesser (IBM T. J Watson Research Center), Marco Ruffini (University of Dublin Trinity College)

2:20pm - 2:40pm Oral Talk 6: CLOUD-CG: Clustering on Longitudinal Causal Graphs

Shinpei Nakamura Sakai (Yale University & Banco de Mexico), Yuhe Gao, Chi-Hui Yen, Christoph Scheidiger (Amazon), Jasjeet S Sekhon (Yale University)

2:40pm - 3:00pm Oral Talk 7: Wald-Difference-in-Differences Estimation without Individual-Level Treatment Data

Takumi Hattori, Kohsuke Kubota, Keiichi Ochiai (NTT DOCOMO, INC)

3:00pm - 3:30pm Keynote Talk 3: Causal Representation Learning

Burak Varıcı, Carnegie Mellon University

3:30pm - 4:00pm Coffee Break

4:00pm - 4:20pm Oral Talk 8: Policy-Aware Learning of Transition Models Using a Causal Approach

Maksim Anisimov, Edwin Hamel-de le Court, Francesco Belardinelli (Imperial College London)

4:20pm - 4:55pm Poster Session 2

4:55pm - 5:00pm Closing Remarks