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Contact Information

Name Hyunseung Hwang
Professional Title Postdoctoral Researcher · NYU Center for Responsible AI
Email aguno94@gmail.com
Location Brooklyn, NY, USA, Brooklyn, NY
Website https://aguno.github.io

Professional Summary

Postdoctoral researcher at NYU’s Center for Responsible AI (with Julia Stoyanovich) and a KAIST Ph.D. I stress-test the explanation methods practitioners rely on to audit high-stakes models, exposing their hidden vulnerabilities and engineering more transparent, robust alternatives. My work spans from developing explainability-first clustering frameworks to demonstrating how tools like SHAP are highly sensitive to data-engineering choices. I aim to build trustworthy AI systems where model risk is strictly managed, ensuring that automated decisions in critical domains—from AI alignment to financial services—are safe, accountable, and highly confident.

Experience

  • 2026 -

    Brooklyn, NY, USA

    Postdoctoral Researcher
    New York University (NYU), Center for Responsible AI
    • Conducting advanced research on the interpretability and safety of machine learning models under the supervision of Prof. Julia Stoyanovich.
    • Stress-testing explanation models to ensure safe, confident, and defensible outputs for end-users and stakeholders in high-stakes domains.
  • 2025 - 2025

    Daejeon, South Korea

    Research Collaborator
    Global Frontier Lab
    • Collaborated with Julia Stoyanovich’s Responsible AI group at NYU.
    • Investigated the sensitivity and robustness of AI explainability techniques to deliver safe, confident explanations to stakeholders.
  • 2019 - 2019

    Seongnam, South Korea

    Research Intern
    Naver
    • Implemented community detection (Girvan–Newman) on PySpark to cluster unsupervised data for video recommendation.
  • 2018 - 2018

    Murray Hill, NJ, USA

    Software Engineering Intern
    Kiswe Mobile
    • Built Android features for a live video-streaming service using Android Studio.
    • Updated the application to meet Android Oreo (8.0+) requirements.

Education

  • 2021 - 2026

    Daejeon, South Korea

    Ph.D.
    KAIST
    Electrical Engineering
    • Advisor: Steven Euijong Whang (Data Intelligence Lab)
    • Dissertation: Enhancing Explainability in Machine Learning — Explainable Clustering and Explanation Multiplicity
  • 2019 - 2021

    Daejeon, South Korea

    M.S.
    KAIST
    Electrical Engineering
  • 2013 - 2019

    Daejeon, South Korea

    B.S.
    KAIST
    Computer Science
  • 2010 - 2013

    Fairfax County, VA, USA

    High School Diploma
    Langley High School
    General Studies

Skills

Research: Explainable AI (XAI), SHAP / feature attribution, Explanation multiplicity and robustness, Fairness and responsible AI, Explainable clustering
Technical: Python, PySpark, Machine learning, Data visualization

Languages

Korean : Native speaker
English : Fluent