Ji-Yong Shin
Assistant Professor
Research interests
- Distributed systems
- Formal verification
- Cloud storage systems
- Operating systems
Education
- PhD in Computer Science, Cornell University
- MS in Computer Science, Korea Advanced Institute of Science and Technology — South Korea
- BS in Computer Science and Industrial Engineering, Yonsei University — South Korea
Biography
Ji-Yong Shin is an assistant professor in the Khoury College of Computer Sciences, based in Boston.
Shin researches formal verification methods that can be applied to system designs; he also designs novel systems such as distributed systems, cloud storage systems, and operating systems. Prior to joining Northeastern in 2020, he was an associate research scientist in the Department of Computer Science at Yale University.
In 2019, Shin received the NSF FMitF grant for a research project titled Track I: ADVERT: Compositional Atomic Specifications for Distributed System Verification. The project’s impacts include new tools to improve the reliability and security of large software infrastructures and the applications that run on them, as well as new courses on distributed-system design and verification that will broaden the participation of underrepresented groups.
Projects
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Compositional Atomic Specifications for Distributed System Verification
Lead PI: Zhong Shao (Yale University)Co PI: Robert Soule (Yale University)
Recent publications
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LiDO: Linearizable Byzantine Distributed Objects with Refinement-Based Liveness Proofs
Citation: Longfei Qiu, Yoonseung Kim, Ji-Yong Shin, Jieung Kim, Wolf Honoré, Zhong Shao. (2024). LiDO: Linearizable Byzantine Distributed Objects with Refinement-Based Liveness Proofs Proc. ACM Program. Lang., 8, 1140-1164. https://doi.org/10.1145/3656423 -
AdoB: Bridging Benign and Byzantine Consensus with Atomic Distributed Objects
Citation: Wolf Honoré, Longfei Qiu, Yoonseung Kim, Ji-Yong Shin, Jieung Kim, Zhong Shao. (2024). AdoB: Bridging Benign and Byzantine Consensus with Atomic Distributed Objects Proc. ACM Program. Lang., 8, 419-448. https://doi.org/10.1145/3649826 -
FusionFlow: Accelerating Data Preparation for Machine Learning with Hybrid CPU-GPU Processing
Citation: Taeyoon Kim, Chanho Park, Mansur Mukimbekov, Heelim Hong, Minseok Kim, Ze Jin, Changdae Kim, Ji-Yong Shin, Myeongjae Jeon. (2023). FusionFlow: Accelerating Data Preparation for Machine Learning with Hybrid CPU-GPU Processing Proc. VLDB Endow., 17, 863-876. https://www.vldb.org/pvldb/vol17/p863-kim.pdf -
Adore: atomic distributed objects with certified reconfiguration
Citation: Wolf Honoré, Ji-Yong Shin, Jieung Kim, Zhong Shao. (2022). Adore: atomic distributed objects with certified reconfiguration PLDI, 379-394. https://doi.org/10.1145/3519939.3523444 -
Much ADO about failures: a fault-aware model for compositional verification of strongly consistent distributed systems
Citation: Wolf Honoré, Jieung Kim, Ji-Yong Shin, and Zhong Shao. 2021. "Much ADO about failures: a fault-aware model for compositional verification of strongly consistent distributed systems." Proc. ACM Program. Lang. 5, OOPSLA, Article 97 (October 2021), 31 pages. DOI: 10.1145/3485474 -
WormSpace: A Modular Foundation for Simple, Verifiable Distributed Systems
Citation: "WormSpace: A Modular Foundation for Simple, Verifiable Distributed Systems,” Ji-Yong Shin, Jieung Kim, Wolf Honoré, Hernán Vanzetto, Srihari Radhakrishnan, Mahesh Balakrishnan, and Zhong Shao, In Proceedings of the ACM Symposium on Cloud Computing (SoCC), Santa Cruz, CA, U.S.A., Nov 2019. -
Towards Weakly Consistent Local Storage Systems
Citation: "Towards Weakly Consistent Local Storage Systems," Ji-Yong Shin, Mahesh Balakrishnan, Tudor Marian, Jakub Szefer and Hakim Weatherspoon, In Proceedings of the ACM Symposium on Cloud Computing (SoCC), Santa Clara, CA, U.S.A., Oct 2016. -
Isotope: Transactional Isolation for Block Storage
Citation: "Isotope: Transactional Isolation for Block Storage," Ji-Yong Shin, Mahesh Balakrishnan, Tudor Marian, and Hakim Weatherspoon, In Proceedings of the USENIX Conference on File and Storage Technologies (FAST), Santa Clara, CA, U.S.A., Feb 2016.
