Kihong Heo

Kihong Heo is an Associate Professor in the School of Computing and Graduate School of Information Security at KAIST (Korea Advanced Institute of Science and Technology) in South Korea. His academic career includes serving as an Assistant Professor at KAIST from 2017-2019 before being promoted to Associate Professor in 2020, following his postdoctoral research at the University of Pennsylvania. He earned both his Ph.D. and B.S. in Computer Science & Engineering from Seoul National University.

Dr. Heo's research focuses on developing program reasoning systems for safe and reliable software, with specific interests in AI-based program analysis systems for detecting deep semantic software bugs, general-purpose program simplification systems for secure and efficient software, and scalable program synthesis systems for automatic software generation and repair. His work bridges the gap between programming languages, program analysis, and machine learning techniques to create next-generation programming systems.

Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional program analysis methods, with significant contributions in compiler validation, software security, fault localization, and program debloating. His research has practical impact, with some of his work incorporated into Facebook's Infer static analyzer.

• ACM SIGSOFT Distinguished Paper Award, FSE 2025
• Amazon Research Award, 2024
• The Soo-Young Lee Teaching Innovation Award, KAIST, 2024
• Prize for Excellence in Teaching, KAIST, 2024
• Best Artifact Award, ICSE 2022
• ACM SIGPLAN Distinguished Paper Award, PLDI 2019
• ACM SIGSOFT Distinguished Paper Award, ICSE 2019

Dr. Heo actively mentors graduate students, currently advising several Ph.D. candidates including Yeonhee Ryou, Taeeun Kim, and Sujin Jang, as well as master's students. He has served on program committees for major software engineering and programming language conferences including PLDI, ICSE, POPL, and SPLASH, demonstrating his active role in the academic community. His laboratory, the Programming Systems Laboratory at KAIST, focuses on creating innovative programming systems that leverage both semantic-based program analysis and AI techniques.