Regular biography
Hongseok Yang is a faculty member at the School of Computing, KIAS, Korea. His research focuses on problems at the intersection of programming languages and machine learning, particularly in probabilistic programming and probabilistic inference. He develops program-analysis algorithms that integrate logic-based programming language techniques with data-driven machine learning methods. Yang also supports graduate studies at KAIST, mentoring students such as Gyeongwon Jung, Taeyoung Kim, Heesan Kong, Sangho Lim, Seonghun Park, and Sungkuk Shin. His contact email is hongseok00@gmail.com, and his profile page can be accessed at https://sites.google.com/view/hongseokyang/home.
Scholar-generated biography
Hongseok Yang is a professor at the School of Computing, KAIST, specializing in Probabilistic Programming, Programming Languages, Machine Learning, Software Verification, and Distributed Systems. His research focuses on formal methods for reasoning about programs, particularly in the context of data structures and concurrency. He has contributed to the development of shape analysis techniques, local reasoning, and separation logic, with applications in software verification and distributed systems. His work also explores probabilistic programming semantics, higher-order functions, and continuous distributions. Yang's publications emphasize compositional reasoning, abstraction, and the integration of probabilistic and logical frameworks.