Hideaki Takahashi

Hideaki Takahashi

日本語版はこちら

I am a first-year PhD student in Computer Science department at Columbia University, advised by Prof. Junfeng Yang. I also work closely with Prof. Suman Jana. My research interests revolve around AI, security, privacy, and systems. My current work focuses on Zero Knowledge Proofs.

I received a Bachelor of Arts and Science in Informatics from the University of Tokyo, where I was advised by Prof. Alex Fukunaga, focusing on privacy-preserving AI planning. During my undergraduate studies, I spent a gap year as a research intern at Tsinghua University under the supervision of Prof. Yang Liu and Prof. Jingjing Liu, investigating security vulnerabilities in Federated Learning.

I am also passionate about open-source development. My project, AIJack, which aims to attack, defend, and debug machine learning models, has gained traction with over 300 stars on GitHub and has been widely used in research.
CV  Semantic Scholar  Google Scholar  GitHub 

Education


Papers (peer-reviewed)


Preprints


Softwares

  • AIJack

    Security risk simulator for machine learning (more than 300 stars on GitHub and used in 8 papers)
  • rhoevm

    Symbolic EVM execution engine written in Rust to find vulnerabilities within Ethereum smart contracts
  • Gymbo

    Symbolic execution engine using gradient descent to solve path constraints
  • My*
    This series aims to implement various algorithms, compilers, and solvers from scratch.
    - MyDisassembler: Disassembler for X86-64 implemented from scratch in C++.
    - MyCompiler: Toy compiler from a simple language to LLVM-IR implemented from scratch in Haskell.
    - MyPlanner: PDDL Solver implemented from scratch in C++.
    - MyOptimizer: Implementations of popular optimization and search algorithms.

Research Experience

  • Fukunaga Lab, The University of Tokyo - Undergraduate Student
    Apr. 2023 - Mar. 2023
    Conducted research on the transit obfuscation problem, which is a new task of privacy-preserving AI planning, under the supervision of Prof. Alex Fukunaga.
  • Institute for AI Industry Research, Tsinghua University - Federated Learning & Privacy Computing Intern
    Jan. 2022 ‑ Feb. 2023
    Conducted research on federated learning and privacy computing under the supervision of Prof. Yang Liu and Prof. Jingjing Liu.
  • Laboratory for Software Design and Analysis, Nara Institute of Science and Technology - Visiting Student
    Aug. 2021 ‑ Sep. 2021
    Conducted research on the free‑rider problem of federated learning under the supervision of Prof. Kohei Ichikawa and Prof. Keichi Takahashi.

Industry Experience

  • Apple Inc. - Technical Internship: AIML/Software Engineer
    Feb. 2024 - present
    Working on AIML/software engineering.
  • UTokyo Economic Consulting Inc. - Research Assistant
    Oct. 2020 - present
    Working on research and social implementations of econometrics and machine learning.
  • RECRUIT - Data Science Intern
    Aug. 2020 - Sep. 2020
    Worked on a location‑based restaurant recommendation iOS app.
  • M3, Inc. - Data Analysis Intern
    Feb. 2020 - Jun. 2020
    Worked on a data analysis project in the field of medical surveys.
  • FRONTEO, Inc. - Research Intern
    Sep. 2019 ‑ Mar. 2020
    Worked on the detection of anomaly documents with NLP and network analysis.

Honors


Service