CV

General Information

Full Name Changhwa Park
Date of Birth 6th September 1993
Languages Korean, English

Education

  • 2021
    Master of Science
    Seoul National University, Seoul, Korea
    • M.S. in Electrical and Computer Engineering
    • Advisor: Prof. Sungroh Yoon
    • GPA: 4.20/4.30
    • March 2019 - February 2021
  • 2019
    Bachelor of Science
    Seoul National University, Seoul, Korea
    • B.S. in Electrical and Computer Engineering
    • GPA: 3.93/4.30 (total), 4.08/4.30 (major)
    • March 2012 - February 2019
  • 2018
    Exchange Student Program
    Cockrell School of Engineering, UT Austin, US
    • Electrical and Computer Engineering
    • GPA: 3.96/4.00
    • August 2017 - May 2018
  • 2012
    High School
    Seoul Science High School, Seoul, Korea
    • Specialized high school for students talented in math and science
    • GPA: 4.01/4.30
    • March 2009 - February 2012

Employment

  • 2022 -
    Machine Learning Engineer
    42dot Inc., Seoul, Korea
    • September 2022 - Present
  • 2021 - 2022
    AI Research Engineer
    AIRS Company, Hyundai Motor Group, Seoul, Korea
    • March 2021 - September 2022
    • Class imbalance research
      • Proposed a mutual learning framework that generates high-quality representations in long-tailed settings and established a new state-of-the-art record on several long-tailed benchmark datasets.
    • AutoML website, full stack development
      • Developed both client-side and server-side of the website for AutoML service from the ground.
    • Wheel alignment for a smart factory
      • Developed machine learning algorithm using tabular data to automate wheel alignment for a smart factory.

Research Experience

  • 2018 - 2019
    Undergraduate Research Intern
    Data Science & AI Lab, Seoul National University, Seoul, Korea
    • July 2018 - February 2019
    • Domain adaptation through label propagation
      • Advisor: Prof. Sungroh Yoon
      • To learn domain invariant and class-wise discriminative features, applied label propagation method and enforced cycle consistency. Proved theoretical rationale and achieved competitive performance.
  • 2018
    Undergraduate Research Intern
    Wireless Networking and Communications Group, UT Austin, US
    • January 2018 - May 2018
    • URLLC performance analysis
      • Advisor: Prof. Jeff Andrews
      • Studied existing URLLC schemes used in industrial and vehicular networks and incorporated these schemes into a probabilistic framework that enables performance analysis.

Projects

  • 2020 - 2021
    Renal Progression Risk Prediction
    Seoul National University Hospital, Seoul, Korea
    • May 2020 - February 2021
    • Analyzed machine learning approaches for the relationship between dyslipidemia and renal outcomes.
  • 2019 - 2021
    AI Consortium for Transfer Learning Research
    Hyundai Motor Group, Seoul, Korea
    • April 2019 - February 2021
    • Built domain adaptation model that utilizes contrastive learning to enhance feature discriminability.
  • 2020
    Domain-Adversarial Training of Neural Networks
    • Implemented Domain-Adversarial Training of Neural Networks (Ganin et al., 2016) with TensorFlow 2.0.
  • 2019
    Exercise Capacity Prediction using Body Composition Data
    Hilaris, Seoul, Korea
    • February 2019 - October 2019
    • Built deep learning model to predict the exercise capacity of each person using supervised learning.

Scholarships and Awards

  • 2021
    • Third place, Hyundai Motor Group Programming Festival
  • 2017
    • OIA Outgoing Exchange Student Scholarship
  • 2017
    • Full Scholarship granted by Sinyang Cultural Foundation
  • 2014
    • Academic Incentive from Electrical and Computer Engineering Scholarship Foundation
  • 2012
    • Eminence Scholarship granted by Seoul National University

Academic Interests

  • Deep learning
    • Domain adaptation
    • Long-tailed recognition

Professional Services

  • NeurIPS conference reviewer: 2020, 2021, 2022
  • ICLR conference reviewer: 2020, 2022
  • ICML conference reviewer: 2022