CV

Master of Science

• M.S. in Electrical and Computer Engineering
• Advisor: Prof. Sungroh Yoon
• GPA: 4.20/4.30
• March 2019 - February 2021

Bachelor of Science

• B.S. in Electrical and Computer Engineering
• GPA: 3.93/4.30 (total), 4.08/4.30 (major)
• March 2012 - February 2019

Exchange Student Program

• Electrical and Computer Engineering
• GPA: 3.96/4.00
• August 2017 - May 2018

High School

• Specialized high school for students talented in math and science
• GPA: 4.01/4.30
• March 2009 - February 2012

Machine Learning Engineer

• January 2023 - Present
• Anomaly detection for a smart factory
  • Developed an anomaly detection algorithm tailored for the vision inspection of battery, integrating optimized training, positional encoding, and ROI masking techniques.

Machine Learning Engineer

• September 2022 - January 2023
• 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.

AI Research Engineer

• March 2021 - September 2022
• 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.

Undergraduate Research Intern

• 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.

Undergraduate Research Intern

• 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.

Renal Progression Risk Prediction

• May 2020 - February 2021
• Analyzed machine learning approaches for the relationship between dyslipidemia and renal outcomes.

AI Consortium for Transfer Learning Research

• April 2019 - February 2021
• Built domain adaptation model that utilizes contrastive learning to enhance feature discriminability.

Domain-Adversarial Training of Neural Networks

• Implemented Domain-Adversarial Training of Neural Networks (Ganin et al., 2016) with TensorFlow 2.0.

Exercise Capacity Prediction using Body Composition Data

• February 2019 - October 2019
• Built deep learning model to predict the exercise capacity of each person using supervised learning.

• Third place, Hyundai Motor Group Programming Festival

• OIA Outgoing Exchange Student Scholarship

• Full Scholarship granted by Sinyang Cultural Foundation

• Academic Incentive from Electrical and Computer Engineering Scholarship Foundation

• Eminence Scholarship granted by Seoul National University