Jianan Yao

Jianan Yao

Ph.D. Candidate in Computer Science

Columbia University

About Me

I am a final-year Ph.D. candidate in computer science at Columbia University. I am fortunate to be advised by Prof. Ronghui Gu, and work closely with Prof. Jason Nieh and Prof. Suman Jana. Prior to that, I obtained my Bachelor’s degree of computer science from Tsinghua University in 2019.

My research spans the fields of programming languages, distributed systems, and machine learning, with the overarching goal of ensuring the correctness and security of safety-critical systems software through formal verification. I am particularly interested in automating the verification process, reducing the proof burden and specialized expertise required, thus facilitating its broader real-world application. To achieve higher automation, my research encompasses a combination of innovative pipelines, classical algorithms, and machine learning models, and has proven effective across various domains, including sequential programs, distributed protocols, and blockchain systems.

I am on the academic job market this year! Feel free to reach out.

Publications

  • Mostly Automated Verification of Liveness Properties for Distributed Protocols with Ranking Functions.
    Jianan Yao, Runzhou Tao, Ronghui Gu, and Jason Nieh.
    POPL 2024.
    PDF Code
  • Leveraging Large Language Models for Automated Proof Synthesis in Rust.
    Jianan Yao, Ziqiao Zhou, Weiteng Chen, and Weidong Cui.
    arXiv preprint. 2023
    PDF
  • DuoAI: Fast, Automated Inference of Inductive Invariants for Verifying Distributed Protocols.
    Jianan Yao, Runzhou Tao, Ronghui Gu, and Jason Nieh.
    OSDI 2022.
    PDF Code
  • Giallar: Push-Button Verification for the Qiskit Quantum Compiler.
    Runzhou Tao, Yunong Shi, Jianan Yao, Xupeng Li, Ali Javadi-Abhari, Andrew W. Cross, Frederic T. Chong, and Ronghui Gu.
    PLDI 2022.
    PDF Code
  • Formal Verification of a Multiprocessor Hypervisor on Arm Relaxed Memory Hardware.
    Runzhou Tao, Jianan Yao, Xupeng Li, Shih-Wei Li, Jason Nieh, and Ronghui Gu.
    SOSP 2021.
    PDF Code
  • Scivik: A Versatile Framework for Specifying and Verifying Smart Contracts.
    Shaokai Lin, Xinyuan Sun, Jianan Yao, and Ronghui Gu.
    Memorial Volume for Shoucheng Zhang, World Scientific. 2021.
    PDF
  • DistAI: Data-Driven Automated Invariant Learning for Distributed Protocols.
    Jianan Yao, Runzhou Tao, Ronghui Gu, Jason Nieh, Suman Jana, and Gabriel Ryan.
    OSDI 2021.
    Jay Lepreau Best Paper Award
    PDF Code
  • Gleipnir: Toward Practical Error Analysis for Quantum Programs.
    Runzhou Tao, Yunong Shi, Jianan Yao, John Hui, Frederic T Chong, and Ronghui Gu.
    PLDI 2021.
    PDF Code
  • Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks.
    Jianan Yao, Gabriel Ryan, Justin Wong, Suman Jana, and Ronghui Gu.
    PLDI 2020.
    PDF Code
  • CLN2INV: Learning Loop Invariants with Continuous Logic Networks.
    Gabriel Ryan, Justin Wong, Jianan Yao, Ronghui Gu, Suman Jana.
    ICLR 2020.
    PDF Code

Experience

Teaching

  • [CSOR 4231] Analysis of Algorithms. Spring 2022.
  • Blockchain Cyberdefense Design Challenge. Summer 2021.
  • [COMS W4115] Programming Languages & Translators. Spring 2021.

Service

  • ASPLOS 2024: External Reviewer
  • APLAS 2023: External Reviewer
  • OSDI 2023: Artifact Evaluation Committee
  • USENIX ATC 2023: Artifact Evaluation Committee
  • PLDI 2022: External Reviewer
  • POPL 2022: External Reviewer

Contact