I am a researcher at SLATE and a PhD student in the Department of Informatics at the University of Bergen, where I am part of the Algorithms Group. My research lies at the intersection of algorithms and artificial intelligence, combining theoretical computer science with practical questions in machine learning and data-driven systems. I currently work on synthetic data generation and federated learning. More broadly, I am interested in algorithms, optimization, model checking, automated theorem proving, and combinatorial problems. I am also involved in organizing the AI Olympiad in Norway. If you are interested in these topics, feel free to contact me.

I am involved in organizing the AI Olympiad in Norway (NOKI), helping connect students with AI, algorithms, and problem solving.

I am interested in teaching and supervision in algorithms, optimization, artificial intelligence, machine learning, automated reasoning, and related topics in theoretical computer science.

Professional article

• Emmanuel Jean Paul Pierre Arrighi; Pål Grønås Drange; Kenneth Langedal et al. (2023). PACE Solver Description: Zygosity. (external link)

Conference poster

• Bilal Mahmood; Mehdi Elahi; Farhad Vadiee et al. (2024). A Supervised Machine Learning Approach for Supporting Editorial Article Selection. (external link)

Academic article

• Mateus De Oliveira Oliveira; Farhad Vadiee (2023). From Width-Based Model Checking to Width-Based Automated Theorem Proving. (external link)
• Mateus De Oliveira Oliveira; Farhad Vadiee (2024). State Canonization and Early Pruning in Width-Based Automated Theorem Proving. (external link)
• Bilal Mahmood; Mehdi Elahi; Farhad Vadiee et al. (2025). A Supervised Machine Learning Approach for Supporting Editorial Article Selection. (external link)
• Fidel Ernesto Diaz Andino; Maria Kokkou; Mateus De Oliveira Oliveira et al. (2021). Unitary Branching Programs: Learnability and Lower Bounds. (external link)

See a complete overview of publications in Cristin.

An up-to-date list of my publications is available via Google Scholar and DBLP. Google Scholar: https://scholar.google.com/citations?user=RktHIgcAAAAJ&hl=en DBLP: https://dblp.org/search/author?q=Farhad+Vadiee Earlier publications may appear under the name Farhad Vadiee.

Current involvements include ASPIRE, EduTrust AI, AI LEARN, and NOKI. Earlier work includes AUTOPROVING: Automated Theorem Proving from the Mindset of Parameterized Complexity Theory (Project no. 288761).