Researcher at SLATE

Sam Urmian

My research is in algorithm design, automated theorem proving, and algorithmic learning theory. I am interested in the mathematical foundations of learning and reasoning systems, especially how algorithms can be designed, analyzed, and understood through computational, statistical, and logical resources.

My PhD work focuses on dynamic programming algorithms and automated theorem provers. More broadly, I study algorithmic methods for proof search, automated reasoning, optimization, and learning. I am especially interested in theoretical questions where clean models, efficient algorithms, lower bounds, and probabilistic or combinatorial analysis help clarify what is possible and what is computationally difficult.

On the application side, I am interested in human-centered AI systems: systems in which people learn, reason, make decisions, or collaborate with AI. My current applied research is in AI and education, where I study how intelligent systems can support learning, feedback, and educational decision-making.

Currently, I am a researcher at the Centre for the Science of Learning & Technology (SLATE), working with Mohammad Khalil and Barbara Wasson. I will defend my PhD in August 2026 under the supervision of Mateus de Oliveira Oliveira at the Department of Informatics, University of Bergen. Before that, I received my master's degree from Sharif University of Technology.