Sangmin Lee
Machine Learning Engineer
"저는 Machine Learning Engineer을 목표로 경기대학교에서 공학사, 이학석사를 취득하였고, 해당 과정을 통해 연구 경력은 4년을 쌓았으며 다양한 분야의 역량 향상을 위해 노력해왔습니다.
경험을 통해 쌓은 문제해결역량을 통해 산업 발전에 기여하는 것이 목표입니다."
Technical Writer @Slashpage
Education
I am pleased to introduce my educational background.
Kyonggi University / M.S. of Computer Science (2022.03 ~ 2024.02)
G. P. A: 4.25 / 4.5
Transcript: https://drive.google.com/file/d/1M9FXnkug1mlgOMzFjaqaePkw-dTLapX-
Graduate Certificate: https://drive.google.com/file/d/1MAzl9yFkpjk7_8OnHp7P3RMP70OTpuuW
Research Field : Network, Deep Learning (Recommendation System, Computer Vision, Graph Neural Network)
Advisor : Prof. Namgi Kim (Kyonggi university)
Kyonggi University / B.S. of Computer Engineering (2015.03 ~ 2022.02)
G. P. A: 3.62 / 4.5
Honors & Awards
The honors I have had and the awards I have received are as follows.
Top 0.04%
DACON Competition Rank
11th / 104,243th
(2024.03.26)
Top 4.41%
DACON Code Sharing Rank
110th / 2,495th
(2024.02.27)
212 EA
Programmers Ranking
18,378th, 1,421 point
(2024.01.27)
87,863th
BAEKJOON Rank: Silver 5
(2024.01.27)
Participation
Kyonggi University Department of AI and Computer Science
No. 2021-0005
Best Paper
Paper: Health Trainer Web Services with PostNet
KIIT, No. 21-222
Publication
The results of my efforts to build artificial intelligence capabilities are as follows.
Master’s thesis
Optimization methods of Graph Convolution Networks for Recommendation Systems
International journal
Deep Learning Model Ensemble for the Accuracy of Classification Degenerative Arthritis
Weighted Forwarding in Graph Convolution Networks for Recommendation Information System
Embedding Enhancement method for LightGCN in Recommendation Information Systems
Learning optimization method for Graph Neural Network-Based Graph Convolutional Network Optimization
International conference
Egress Initialization for Graph Convolution Network in Recommendation Systems
Thin Graph Convolution Network in Recommendation Systems
Over-smoothing in LightGCN doesn’t happen much
Leverage time-based data to improve recommendation system accuracy
Using Deep Learning for Medical Automation in Diagnosis of Degenerative Arthritis
Classification of degenerative arthritis using Xception model in radiographic images
Domestic journal
Analyzing the use of time-based user behavior data to improve the performance of graph neural network-based recommendation systems
Improved Pancreas Segmentation using Multiple Concatenated U-Net Model for Medical Image Systems
Domestic conference
Analysis of performance of unsupervised anomaly detection methods according to anomaly score threshold selection criteria
Analysis of Traffic Flow Prediction Performance According to Spatial-Temporal Attention Module Structures in GNN-based Deep Learning Model
Time-based data Analysis for improving recommendation system performance
A Study on the Flow Classification Method Using Auto-Encoder Model in SDN Environment
Optimizing caching servers using a recommender system
Implementation of attendance system through RFID tags
Accuracy analysis of convolutional neural network models for overlapped character image classification
Health Trainer Web Services with PostNet
Project
The projects to develop my software skills are as follows.
💬
Optimizing GCN for Recsys (23.01 ~ 23.12)
WF Technique, Egress Technique, Non-combination architecture
Role: Project leads and researchers
Research Field : Graph Convolutional Network, Recommendation Systems, Optimization techniques.
Description: During the second year of his master's program, he proposed WF technique, Egress technique and Non-combination architecture for optimizing graph convolutional networks in recommendation systems, and improved learning speed and accuracy through this project.
🗃️
Smart I.o.T Lab Homepage (21.12 ~ 22.04)
Role: Front Developer
Skill : Vue.js, Node.js, JavaScript
Description: Creation of the Smart I.o.T Lab website and addition of features commissioned by Prof. Nam-Ki Kim
🧞‍♂️
IA^2S (Image Analysis Automation System)
(21.10 ~ 22.02)
Role: Team Leader, Front Developer
Skill : JavaScript, Django, OpenCV, Python 3.7.
Description: Web services for crack flattening, crack length measurement, and data automation to improve existing methods for physical exterior wall repair and building maintenance companies.
📔
Fit-sibang (21.03 ~ 21.06)
Role: Team Leader, Front Developer
Skill : React.js, Node.js, JavaScript
Description: Made as a web app, it can be accessed on any device and helps you exercise through posture estimation using AI.
External Activities
Activities to develop my communication and research skills are as follows.
💬
LG Aimers (24.01 ~ 24.02)
Role: 4th semester.
Research Field: Deep Learning
Description: LG Aimers is LG Group's youth education program that provides AI education and the opportunity to experience participating in AI hackathons that deal with LG's actual data.
🗃️
Pseudo-lab (22.09 ~ 22.11)
Team: 그래프로 설득하기.
Research Field : Graph Neural Network
Description: Conduct projects in their respective domains that utilize Graph to solve real-world needs, from defining the problem to why the need should be met with Graph.
🧞‍♂️
DIYA (21.03 ~ 23.02)
4th Team: Computer Vision
Role: Team members
Research Field : Deep Learning, Computer Vision(paper review, participate in competition).
5th Team: Computer Vision, Graph Neural Network, Pytorch
Role: Team members
Research Field : Computer Vision, Graph Neural Network, Deep Learning.
💡
CS224W-KOR (22.07 ~ 22.09)
Role: Team members
Research Field : Graph Neural Network.
Description: CS224W, presenting and organizing the parts they studied and translating them into Korean.
📔
7th college student coding camp
(21.06 ~ 21.07)
Competition
The list of artificial intelligence competitions I participated in to improve my problem-solving skills is as follows, and I have organized the competitions that ranked in the top 10%.
Top 8.48%
80th / 943 team
대구 교통사고 피해 예측 AI 경진대회
Top 0.012%
4th / 330 team
HD현대 AI Challenge (예선)
Top 8.84%
16th / 181th
데이콘 Basic 풍속 예측 AI 경진대회
Top 9.09%
46th / 506 team
월간 데이콘 법원 판결 예측 AI 경진대회
Top 7.6%
20th / 262th
데이콘 Basic 자동차 가격 예측 AI 경진대회
Top 8.98%
61th / 679 team
제2회 코스포 x 데이콘 도서 추천 알고리즘 AI경진대회
Top 3.6%
37th 1025 team
도배 하자 유형 분류 AI 경진대회
Top 8.31%
30th / 361th
데이콘 Basic 칼로리 소모량 예측 AI 경진대회
Top 3.2%
16th / 499 team
월간 데이콘 항공편 지연 예측 AI 경진대회
Top 3.6%
20th / 555th
월간 데이콘 ChatGPT 활용 AI 경진대회
Top 0.64%
5th / 771th
데이콘 Basic 전화 해지 여부 분류 AI 경진대회
Top 5.85%
27th / 461 team
포디블록 구조 추출 AI 경진대회
Top 0.71%
3th / 420th
데이콘 Basic 서울 랜드마크 이미지 분류 경진대회
Top 1.91%
8th / 418th
데이콘 Basic 수화 이미지 분류 경진대회
Top 5.82%
28th/481 team
월간 데이콘 컴퓨터비전 이상치탐지 알고리즘 경진대회
Top 1.72%
5th/290 team
2021 Ego-Vision 손동작 인식 AI 경진대회
Acknowledgments.
Thank you for viewing my resume.
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