Hamit Efe Çınar

Efe Çınar

PhD Student in Computer Science at the University of British Columbia

I am a PhD student in Computer Science at the University of British Columbia, advised by Prof. Kevin Leyton-Brown. Before that, I completed a double major in Computer Science and Engineering and Industrial Engineering at Sabancı University. My research interests lie in Algorithm Configuration, Algorithmic Game Theory, Knowledge Representation and Reasoning, Multi-Agent Systems.

Education

University of British Columbia

Vancouver, Canada

Sep 2026 - Present

Ph.D. in Computer Science
Supervisor: Prof. Kevin Leyton-Brown

  • Research areas: Algorithm Configuration and Algorithmic Game Theory

Sabancı University

Istanbul, Turkey

2021 - 2026

B.S. in Computer Science and Engineering, Minor in Mathematics
B.S. in Industrial Engineering
Full Tuition Scholarship

  • GPA: 3.98/4.00
  • Top 3 GPA in the Faculty of Engineering and Natural Sciences

Uppsala University

Uppsala, Sweden

Jan 2024 - June 2024

Erasmus Exchange Program
Computer Science and Mathematics

Research Interests

Algorithm Configuration

Automatically tuning and selecting algorithms instead of hand-tweaking them. Interested in automated configuration, algorithm selection, and empirical performance models that make solvers for hard combinatorial problems faster, along with the methodology needed to evaluate such claims honestly.

Algorithmic Game Theory

Computation in settings where participants act strategically. Interested in mechanism and market design, incentives and equilibrium computation, and how learning methods can be used to design rules that lead to good collective outcomes.

Knowledge Representation and Reasoning

Formal methods for representing knowledge and enabling automated reasoning through logic-based representations and symbolic systems. Interested in the theoretical foundations of how knowledge can be structured to enable intelligent behavior, and in integrating symbolic reasoning with learning-based AI to enhance explainability and interpretability.

Multi-Agent Systems

Coordination, communication, and collaborative planning among autonomous agents. Focused on how multiple agents interact, share knowledge, and make decisions collectively. Interested in decentralized control, collective intelligence, and mechanisms for fair and effective multi-agent coordination.

Awards & Honors