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Yejin Lee 👩‍💻

Google Scholar ⋄ Github

📧 Email: [email protected]

Education 🎓

Hallym University (Kangwon, South Korea)
B.S. in Computer Science | Feb. 2023
GPA: 3.8/4.5 (Major)
Related Courses: Deep Learning, Artificial Intelligence, Computer Vision, NLP, Linear Algebra, etc.
Graduate Curriculum: Advanced Topics in Image Processing, Special Lecture on Machine Learning

Research Interests 🔍

  • Deep Learning
  • Computer Vision
  • Image Processing

Research Experience 🧑‍🔬

Research on Developing an AI Model for Camera Calibration for Indoor CCTV Video Pedestrian Re-identification
Apr. 2023 - Dec. 2023
Supervisor: Dr. Haesol Park, Korea Institute of Science and Technology (KIST)

  • Developed a feature using the mathematical model of radial distortion lenses to implement distortion.
  • Inferring Camera Parameters and Distortion Coefficients from a Single Image Implementing the distortion function.

A Deep Learning-Based Coyote Detection System Using Audio Data
Aug. 2022 - Dec. 2022
Supervisors: Anthony H. Smith and Yaqin Mia Wang, Purdue University (sponsored by IITP)

  • Implementation of Baseline Audio/Image Learning Models.
  • Implementation of Audio Feature Extraction Code.
  • Extraction and Visualization of Audio Features for Each Class to Construct a Dataset for Image Learning.

Survey Adversarial Attacks and Neural Rendering
Aug. 2022 - Oct. 2022
Supervisor: Prof. Jonguk Hou, Hallym University

  • Comparative Analysis of Related Research.
  • Investigation of Neural Rendering and 3D Representation Technologies.
  • Analysis of Adversarial Attacks on 3D Data and Neural Rendering.

Deep Learning-Based Rapid On-Site Evaluation and Prognosis Predicting Model Using 3D Holographic Microscopy and Single Cell RNA Sequencing in Pancreatic Cancer
Jun. 2022 - Oct. 2022
Supervisor: Prof. Jonguk Hou, Hallym University

  • Removed missing values from the dataset containing metadata.
  • Implemented 4-fold cross-validation to prevent overfitting on the test set.
  • Improved baseline accuracy from 0.93 to 0.96.

Publications 📚

  1. H. Jung, B. Kwon, Y. Kim, et al. "A deep learning-based coyote detection system using audio data," in 2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2023.

  2. Lee, Yejin, B. S. Shim, and J.-U. Hou "Survey adversarial attacks and neural rendering," 2022.

Development Experience 💻

Medical Image AI Challenge 2023: Pathology Data
Dec. 2023 - Jan. 2024
Team Member: Seoul National University Hospital

  • Predicted melanoma recurrence by utilizing pathological images and clinical data.
  • Data Pre-processing for Whole-Slide Image Preprocessing.
  • Ranked 6th out of 62 teams.

Future Technology Challenge 2023
Jun. 2023 - Aug. 2023
Team Member: CJ Logistics

  • Developed an algorithm to recognize the quantity and type of individual products in a cart image after training on individual product images.
  • Generated Synthetic Dataset for Multi-Object Detection.
  • Ranked 4th out of 90 teams.

SK telecom FLY AI Challenger
Aug. 2022 - Oct. 2022
Team Member: SK telecom

  • Development of a face recognition model.
  • Implementation of an API for serving the ChatGPT model.
  • Prompt engineering for generative models.
  • Ranked 1st out of 10 teams.

Achievements 🏆

  • 1st Place, SKT Fly AI Hackathon, awarded by SK telecom, 2023
  • 1st Place, SW Capstone Design Competition, awarded by Hallym University, 2022
  • 1st Place, Healthcare BigData Hackathon, awarded by Hallym University, 2021

Skills 💡

  • Programming Languages: Python, C/C++, Java
  • Machine Learning Tools: Pytorch, TensorFlow
  • Environment: Linux
  • Tooling: Docker, Github, Gitlab
  • Language: TOEIC 815, OPIC IM2

Activities 🌍

K-Mate Program
Aug. 2023 - Dec. 2023
Team Reader, Korea Institute of Science and Technology (KIST)

  • Cultural Exchange Program with International Colleagues.

Connective AI Workshop 2023
Aug. 2023 - Dec. 2023
Staff, Korea Institute of Science and Technology (KIST)

  • Academic Conference Management and Support.