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Workshop Sat, Dec 6, 2025 • 8:00 AM – 5:00 PM PST Upper Level Room 8

CauScien: Uncovering Causality in Science

Dingling Yao · Jiaqi Zhang · Piersilvio De Bartolomeis · Ying Jin · Alexander D'Amour · Caroline Uhler · Kun Zhang · Francesco Locatello
Project Page [ OpenReview] 

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Schedule

Timezone: America/Los_Angeles
8:15 AM
Opening Remarks
Francesco Locatello
11:00 AM
Poster Session 1
→ CLAM: Causal Spatial Disaggregation to Infer Local Effects From Coarse Data
Gerrit Großmann · Sumantrak Mukherjee · Sebastian Vollmer
11:00 AM
How reliable are treatment effects in clinical trials with dropout?
Yuxin Wang · Dennis Frauen · Jonas Schweisthal · Stefan Feuerriegel
→ Inductive Biases for Disentangled Representation Learning with Correlated Treatment--Nuisance Factors
Luka Kovacevic · Sara Jane Dunn · Hagen Triendl · Lindsay Edwards · Sach Mukherjee · John Whittaker · Thomas Gaudelet
→ Causal Scissor: root cause discovery via the measure of edge cuts in graphs
Jingi Ju · Mincheol Shin · Minwoo Kim · Giwoong Lee · Jiseung Ahn · Jeongyeol Choe
→ MIIC-SR: From Complex Data to Structural Causal Models
Nadir Sella · Adam Perbost · Louis VERNY
→ Transformer Is Inherently a Causal Learner
Xinyue Wang · Zhiguang Wang · Biwei Huang
→ CUVET: A Partitioning Approach for Continuous Treatment Assignment At Scale
Artem Betlei · Mariia Vladimirova · Victor Girou · Thibaud Rahier
→ Applying Time-Series Causal Discovery to Understand Algal Bloom Mechanisms
Ayush Prasad · Snehal Verma · Mohammad Aatish Khan
→ Instrumental Variable Representation Learning under Confounded Covariates
Jungsoo Kim · Kwonho Kim · Inwoo Hwang · Sanghack Lee
→ Using causal abstractions to accelerate decision-making in complex bandit problems
Joel Dyer · Nicholas Bishop · Anisoara Calinescu · Michael Wooldridge · Fabio Massimo Zennaro
→ Confounding is a Pervasive Problem in Real World Recommender Systems
Alexander Merkov · David Rohde · Benjamin Heymann · Alexandre Gilotte
→ Uncovering Hidden Correctness in LLM Causal Reasoning via Symbolic Verification
Paul He · Yinya Huang · Mrinmaya Sachan · Zhijing Jin
→ On Double Robustness in Double Machine Learning
Simon Valentin · Gianluca Detommaso · Yikuan Li · Manfred Opper · Michael Brueckner
11:00 AM
CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models
Benjamin Herdeanu · Juan Nathaniel · Carla Roesch · Jatan Buch · Gregor Ramien · Johannes Haux · Pierre Gentine
→ Dynamic causal discovery in Alzheimer’s disease through latent pseudotime modelling
Natalia Glazman · Jyoti Mangal · Pedro Borges · M. Jorge Cardoso
→ CAST: Causal Modeling of Time-Varying Treatment Effects on Head and Neck Cancer
Everest Yang · Ria Vasishtha · Luqman Dad · Lisa Kachnic · Andrew Hope · Eric Wang · Xiao Wu · Yading Yuan · David Brenner · Igor Shuryak
→ Data Decomposition beyond Splitting for Causal Estimation
Xuelin Yang · Dhruv Singal · Rina Friedberg · Niloy Biswas
→ Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
Minghao Fu · Biwei Huang · Zijian Li · Yujia Zheng · Ignavier Ng · Guangyi Chen · Yingyao Hu · Kun Zhang
→ A Causal Formulation of Spike-Wave Duality
Kasra Jalaldoust · Erfan Zabeh
→ Realizing LLMs’ Causal Potential Requires Science-Grounded, Novel Benchmarks
Ashutosh Srivastava · Lokesh N · Gautam Jajoo · Aniket Vashishtha · Parameswari Krishnamurthy · Amit Sharma
11:00 AM
Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priors
Nikita Dhawan · Daniel Shen · Leonardo Cotta · Chris Maddison
→ Can LLMs Propose Instrumental Variables for Causal Reasoning?
Ivaxi Sheth · Zhijing Jin · Bryan Wilder · Dominik Janzing · Mario Fritz
→ How Effective is Your Rebuttal? Identifying Causal Models from the OpenReview System
Longkang Li · Ibrahim Aldarmaki · Minghao Fu · Wong Kang · Yunlong Deng · Qiang Huang · Jing Yang · Jin Tian · Guangyi Chen · Kun Zhang
→ Searching for actual causes: Approximate algorithms with adjustable precision
Samuel Reyd · Ada Diaconescu · Jean-Louis Dessalles
→ CauSciBench: Assessing LLM Causal Reasoning for Scientific Research
Sawal Acharya · Terry Jingchen Zhang · Andrew Kim · Anahita Haghighat · Xianlin Sun · Rahul Babu Shrestha · Maximilian Mordig · Furkan Danisman · Clijo Jose · Yahang Qi · Pepijn Cobben · Bernhard Schölkopf · Mrinmaya Sachan · Zhijing Jin
→ Causal AI Scientist: Facilitating Causal Data Science with Large Language Models
Vishal Verma · Sawal Acharya · Devansh Bhardwaj · Samuel Simko · Yongjin Yang · Anahita Haghighat · Dominik Janzing · Mrinmaya Sachan · Bernhard Schölkopf · Zhijing Jin
→ Causal Machine Learning for Sustainable Agriculture
Vasileios Sitokonstantinou · Emiliano Diaz · Jordi Cerda-Bautista · Maria Piles Guillem · Ioannis Athanasiadis · Ilias Tsoumas · Gustau Camps-Valls
→ Not All Splits Are Equal: Rethinking Attribute Generalization Across Unrelated Categories
Firca Nicolae · Elena Burceanu · Antonio Barbalau · Dan Oneata
→ Efficient Greedy Equivalence Search for Non-Score-Equivalent Criteria using Sampling
Rafailia Chatzianastasiou · Osman Mian · Jilles Vreeken
→ Learning Causal Gene Relationships in Biological Pathways with Graph Attention Networks (GATs)
Gavin Wong · Ping Ho · Ivan Yeung · Ka Chun Cheung · Simon See
→ LongSurv: Bridging Short-Term Data and Causal Priors for Longitudinal Survival Modeling
Shivaram Velayutham · Anuva Kapoor · Kangan Maria · Preetha Balasubramanian · Bhanu Duggal · Mona Duggal · Balaraman Ravindran · Lakshminarayanan Subramanian
→ Estimating Misreporting in the Presence of Genuine Modification: A Causal Perspective
Dylan Zapzalka · Trenton Chang · Lindsay Warrenburg · Sae-Hwan Park · Daniel Shenfeld · Ravi Parikh · Jenna Wiens · Maggie Makar
12:30 PM
Lunch Break
3:00 PM
Panel Discussion
Jason Hartford · Nathan Kallus · Mihaela van der Schaar · Riccardo Cadei · Elizabeth Tipton
4:50 PM
Closing Remarks
Dingling Yao · Jiaqi Zhang · Piersilvio De Bartolomeis