Sina Akbari

Sina Akbari is a PhD candidate and researcher in the Business Analytics department at the College of Management of Technology, École Polytechnique Fédérale de Lausanne (EPFL). He focuses on causal inference, integrating methodologies from statistics and machine learning.

• Education: BSc in Electrical Engineering and Computer Science (2019)

Research Interests: Sina's work centers on causal inference, with a particular emphasis on experimental design and proxy experiments. His projects include developing frameworks like the Triple Changes Estimator to generalize causal effect identification techniques.

Recent Publications: Sina has contributed to journals like the Journal of Machine Learning Research (JMLR) and conferences such as NeurIPS and ICML. His research trends include optimizing causal inference algorithms and enhancing statistical modeling for real-world applications.

Contributions: He actively participates in academic conferences, including serving on the organizing committee for UAI 2024 and presenting at ICML 2024. His GitHub projects, such as the OpenReview Workflow, demonstrate his commitment to automating conference workflows.