3rd Workshop on Causal Inference and Machine Learning in Practice

Schedule

  • Toronto, ON, Canada
  • Date: Wednesday, August 6
  • Time: TBD

Abstract

The 3rd Workshop on Causal Inference and Machine Learning in Practice at KDD 2025 aims to bring together researchers, industry professionals, and practitioners to explore the application of causal inference with machine learning. As causal machine learning techniques gain traction across industries, practical challenges related to trustworthiness, robustness, and fairness remain at the forefront. This workshop will provide a forum to discuss methodologies for applying and evaluating causal models in real-world scenarios and explore innovative applications that integrate causal inference with machine learning algorithms.

Building on the success of the previous editions at KDD 2023 and KDD 2024, which attracted over 200 and 250 participants, respectively, this workshop will continue fostering collaboration between academia and industry. Through invited talks, contributed papers, and interactive discussions, we will address key challenges and opportunities at the intersection of causal inference and machine learning. As the field continues to evolve, this workshop serves as a crucial platform for knowledge exchange and innovation, driving forward the application of causal techniques in machine learning.

Paper Submission

Please submit your paper to the CMT portal site, and check the Call for Paper page for details on important dates and submission guidelines.

Program

Coming Soon!

Invited Speakers

Organizers

  • Chu Wang, Amazon
  • Jingshen Wang, UC Berkeley
  • Sichao Yin, Instacart
  • Yingfei Wang, University of Washington
  • Zeyu Zheng, UC Berkeley, Amazon - main contact

The CausalML Team

  • Huigang Chen, Google
  • Jeong-Yoon Lee, Uber
  • Jing Pan, Snap - main contact
  • Paul Lo, Snap
  • Roland Stevenson, Consultant
  • Totte Harinen, AirBnB
  • Yifeng Wu, Uber
  • Zhenyu Zhao, Roblox

Past Workshop