# Sungjin Im

> Ph.D. 2012

**Wikidata**: [Q102406976](https://www.wikidata.org/wiki/Q102406976)  
**Source**: https://4ort.xyz/entity/sungjin-im

## Summary
Sungjin Im is a South Korean computer scientist and university professor known for his work in theoretical computer science. He earned his Ph.D. in 2012 and has held academic positions at Duke University, University of California, Merced, and University of California, Santa Cruz.

## Biography
- Born: Not specified
- Nationality: South Korean
- Education: Ph.D. from University of Illinois Urbana–Champaign (2012); undergraduate degree from Seoul National University
- Known for: Research in theoretical computer science and algorithms
- Employer(s): University of California, Santa Cruz (current); previously University of California, Merced (2014-2024) and Duke University (2012-2013)
- Field(s): Computer science, theoretical computer science

## Contributions
Sungjin Im has made significant contributions to theoretical computer science, particularly in algorithms and computational complexity. His research focuses on scheduling algorithms, approximation algorithms, and online algorithms. He has published numerous papers in top-tier computer science conferences and journals, advancing understanding in areas such as resource allocation, network design, and optimization problems. His work has been influential in both theoretical foundations and practical applications of algorithm design.

## FAQs
### Q: What is Sungjin Im's area of expertise?
A: Sungjin Im specializes in theoretical computer science, with a focus on algorithms, scheduling, approximation algorithms, and online algorithms.

### Q: Where did Sungjin Im complete his Ph.D.?
A: Sungjin Im completed his Ph.D. at the University of Illinois Urbana–Champaign in 2012.

### Q: What universities has Sungjin Im taught at?
A: Sungjin Im has taught at Duke University, University of California, Merced, and currently teaches at University of California, Santa Cruz.

## Why They Matter
Sungjin Im's research has advanced the theoretical foundations of computer science, particularly in algorithm design and analysis. His work on scheduling algorithms has provided new insights into resource allocation problems that are fundamental to computer systems and operations research. By developing approximation algorithms for complex optimization problems, he has helped bridge the gap between theoretical computability and practical solvability. His contributions have influenced both academic research and practical applications in areas ranging from cloud computing to logistics optimization.

## Notable For
- Ph.D. graduate from University of Illinois Urbana–Champaign in 2012
- Published extensively in top theoretical computer science venues
- Developed novel approximation algorithms for scheduling problems
- Held faculty positions at multiple prestigious U.S. universities
- Mentored numerous graduate students in theoretical computer science

## Body
### Academic Background
Sungjin Im received his doctoral degree from the University of Illinois Urbana–Champaign in 2012, where he worked under the supervision of Chandra Sekhar Chekuri. He completed his undergraduate studies at Seoul National University in South Korea.

### Research Focus
Im's research centers on theoretical computer science, with particular emphasis on:
- Scheduling algorithms and their applications
- Approximation algorithms for NP-hard problems
- Online algorithms for dynamic environments
- Resource allocation and optimization

### Professional Career
After completing his Ph.D., Im began his academic career as an Assistant Professor at Duke University (2012-2013). He then joined the faculty at University of California, Merced, where he worked from 2014 to 2024. In 2025, he moved to University of California, Santa Cruz.

### Publications and Impact
Im has published extensively in premier computer science conferences including STOC, FOCS, SODA, and ICALP, as well as in journals such as Journal of the ACM and SIAM Journal on Computing. His work has been cited hundreds of times by other researchers, indicating significant influence in the field.

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## References

1. [Source](https://sites.google.com/view/sungjinim)
2. Mathematics Genealogy Project