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  Sungjin Im

Sungjin Im

Associate Professor

 

Baskin School of Engineering

Computer Science and Engineering

Associate Professor

Faculty

Regular Faculty

Sungjin Im

Engineering Building 2
541B

SOE3

My area of expertise lies in the design and analysis of algorithms, along with their various applications. My current research focuses on two main areas. Firstly, I'm interested in strengthening traditional worst-case algorithms by incorporating machine learning predictions. This involves exploring how machine learning can improve the performance of algorithms in situations where the worst-case scenario might not be the most common. Secondly, I'm passionate about developing meta-algorithms that can be easily adapted to solve a wide range of problems. This research has a particular emphasis on scheduling and resource allocation. In addition to these current interests, I also maintain a strong interest in database theory and the development of big data algorithms, particularly those that leverage massively parallel processing. Overall, I'm driven by a passion for tackling fundamental algorithmic problems. My research encompasses a broad spectrum of areas, including approximation algorithms, online algorithms, combinatorial optimization, scheduling algorithms, game theory, machine learning, and database theory.

  • Best paper finalist. ACM Symposium on Parallelism in Algorithms and Architectures, 2021, 2024
  • NSF Career Award, 2019
  • Best student paper award, ACM-SIAM Symposium on Discrete Algorithms, SODA 2010

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