Summary
Work History
Education
Skills
Interests
Awards & Achievements
Publications
Timeline
Yeomin Kim

Yeomin Kim

IT Engineering
South Korea

Summary

I am a dedicated IT engineering student with a strong interest in Human-Computer Interaction (HCI), medical data analysis, healthcare, and computer vision. I have gained experience in analyzing biological signals like EEG , developing deep learning models, and participating in research, aiming to contribute further in the fields of AI-based medical technologies and HCI.

Work History

HCI Research Intern

숙명여자대학교
10.2023 - 02.2024
  • Participated in a project titled 'Real-Time BCI System for Target Detection' (Published by IEEE).
  • Outstanding Paper Award, 12th International Winter Conference on Brain-Computer Interface (BCI) (2024)
  • Worked on developing deep learning models for EEG-based target detection using time-series data.
  • Processed and prepped EEG data using EEG Lab, applying various preprocessing techniques such as noise reduction and normalization.
  • Conducted experiments with participants to collect EEG data.
  • Improved model performance through advanced deep learning architectures, including EEGNet and LSTM.
  • Solved class imbalance issues by experimenting with GANs and modifying convolutional layers.
  • Engaged in international conferences to learn about trends in Brain-Computer Interface (BCI) research.

한이음 ICT Mentoring Program-Pet Health Keeper App

과학기술정보통신부
03.2024 - 11.2024
  • Developed a deep learning model for classifying dog obesity based on image data using EfficientNet.
  • Created a real-time pet food recommendation algorithm using ChatGPT API and Google Shopping API to personalize suggestions based on dog health data.
  • Integrated Arduino to collect heart rate and step count data into a database, enhancing the dog food recommendation algorithm based on the dog’s health condition.
  • Applied Convolutional Neural Networks (CNNs) for image classification, achieving significant accuracy in predicting Body Condition Scores (BCS).
  • Addressed class imbalance in the provided open-source dog image dataset through data augmentation techniques.
  • Utilized cloud services such as AWS S3 for data storage, AWS EC2 for data processing and model training, AWS IoT for data publishing, and AWS Lambda for data transfer.
  • As a team leader, coordinated opinions between the mentor and team members, and organized data analysis records into reports for regular presentations.

Health Care Capstone Project

숙명여자대학교
09.2023 - 12.2023
  • Developed an EEG analysis model to measure brain fatigue and blink rates using the Muse2 device.
  • Adapted the approach to a 4-channel EEG device by analyzing the ratio of alpha waves to assess brain fatigue, distinguishing between periods of rest and concentration.
  • Built a corresponding mobile application for real-time monitoring and analysis.
  • Applied various data preprocessing techniques and trained models to detect cognitive states.

Enhanced Security Image Editing SaaS Website

Personal Project
07.2024 - 09.2024
  • Developed a secure image editing platform with SaaS features such as aspect ratio adjustments, padding with AI-generated content, background removal, object color changes, and image quality enhancement.
  • To address deepfake-related social issues, implemented a feature requiring users to consent to IP address collection before viewing the original image, with all IP addresses securely stored in the database.
  • Implemented user login, personalized image sharing, and a privacy-focused security feature where users' images are initially blurred for others until they consent to IP address collection, which removes the blur.
  • Utilized MongoDB, Next.js, and Cloudinary for image storage, processing, and security.

Shinhan Financial Big Data Analytics Competition

신한금융그룹, 빅데이터혁신공유대학사업단
09.2022 - 09.2022
  • I proposed an idea to analyze encrypted customer data from Shinhan Bank to recommend personalized travel packages for each customer.
  • As a team leader, coordinated team members' opinions and worked towards implementing an efficient development plan.

Tourism Data Utilization Contest

한국관광공사, 카카오
05.2022 - 09.2022
  • Developed a React-based web application using public APIs to enhance the tourism experience.
  • The service provides information on tourist attractions, accommodations, and restaurants based on region and sports themes.

Education

Bachelor of Science - Computer Engineering

숙명여자대학교, 서울
03.2021 - 02.2026

Skills

Programming Languages: Python, JavaScript, TypeScript

Interests

HCI

Medical Data Analysis

Healthcare Technologies

Computer Vision

AI-based Solutions for Biological Signal Analysis

Awards & Achievements

  • Outstanding Paper Award, 12th International Winter Conference on Brain-Computer Interface (BCI) (2024)
  • Honorable Mention, Hanium ICT Mentoring Program – Pet Health Keeper App (2024)
  • Third Prize, Shinhan Financial Big Data Analytics Competition (2022)
  • Third Prize, Korea Tourism Organization x Kakao Tourism Data Contest (2022)

Publications

  • Eunji Won, Seongyeon Lim, Yeomin Kim, Sun-Yeon Dong, “Toward the TCN-based Real-Time BCI system for Target detection", 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'24), July 15-19, 2024, Orlando, USA
  • Eunji Won, Seongyeon Lim, Yeomin Kim, Sun-Yeon Dong, “Real-Time BCI System for Target Detection”, 2024 12th International Winter Conference on Brain-Computer Interface (BCI), Feb. 26-28, 2024, Gangwon, Korea, Republic of

Timeline

Enhanced Security Image Editing SaaS Website - Personal Project
07.2024 - 09.2024
한이음 ICT Mentoring Program-Pet Health Keeper App - 과학기술정보통신부
03.2024 - 11.2024
HCI Research Intern - 숙명여자대학교
10.2023 - 02.2024
Health Care Capstone Project - 숙명여자대학교
09.2023 - 12.2023
Shinhan Financial Big Data Analytics Competition - 신한금융그룹, 빅데이터혁신공유대학사업단
09.2022 - 09.2022
Tourism Data Utilization Contest - 한국관광공사, 카카오
05.2022 - 09.2022
숙명여자대학교 - Bachelor of Science, Computer Engineering
03.2021 - 02.2026

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Yeomin KimIT Engineering