Saber Salehkaleybar is an assistant professor at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University. Prior to this, he worked as a research scientist in the School of Computer and Communication Sciences (IC) and College of Management of Technology (CDM) at École Polytechnique Fédérale de Lausanne. His research interests include causal inference, stochastic optimization, and reinforcement learning. He is particularly interested in causal discovery, experiment design, and applications of causality in generative AI. Additionally, he is focused on developing efficient optimization algorithms for training large learning models.
Latest News
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May 2024, Our paper Causal Effect Identification in LiNGAM Models with Latent Confounders was accepted in ICML 2024.
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Apr 2024, I became an ELLIS member.
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Apr 2024, Our paper Momentum-Based Policy Gradient with Second-Order Information was accepted in TMLR.
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Jan 2024, Our paper Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data was accepted in AISTATS 2024.
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Dec 2023, I am honored to be serving as the Workflow Chair for the UAI 2024 conference.
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Dec 2023, Our paper A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models was accepted in JMLR.
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Sep 2023, Our paper A Cross-Moment Approach for Causal Effect Estimation was accecpted as a spotlight paper in NeurIPS 2023.