Sungjin Im

Sungjin Im is an Associate Professor in the Department of Computer Science and Engineering at the University of California, Santa Cruz. His expertise spans algorithm design, analysis, and applications, with a focus on integrating machine learning into traditional algorithms and developing adaptable meta-algorithms for scheduling. He maintains active research in database theory and parallel processing for big data.

• Education: B.S./M.S. in Computer Science & Engineering from Seoul National University, Ph.D. in Computer Science from University of Illinois at Urbana-Champaign
• Employment: UC Santa Cruz (2025-current), UC Merced (2014-2025), Consulting Faculty at RelationalAI (2019-current), Visiting Scholar at Google (2021)

His research bridges fundamental algorithmic problems with practical applications, covering approximation algorithms, online algorithms, combinatorial optimization, game theory, and machine learning. Recent work emphasizes:

• Enhancing worst-case algorithms with machine learning predictions
• Developing flexible meta-algorithms for diverse problem domains
• Advancing database theory and parallel processing techniques

Selected Scientific Awards:

• NSF Career Award (2019)
• Best Student Paper at SODA (2010)
• Samsung Fellowship (2006)
• Korea Foundation for Advanced Studies Scholarships (2000-2003)
• IMO Silver Medal (1996)