In Kyu Lee
+8210-6287-9994
Seoul, South Korea
Contact
Education
While studying aerospace engineering, I had the opportunity to learn a lot about fluid dynamics. During my internship at Seoul National University Hospital, I discovered the numerous applications of fluid dynamics in relation to air pollution and respiratory health. Through this experience, I also realized the importance of CT image processing techniques and segmentation. Recognizing the potential for AI to address these challenges, I dedicated myself to learning and applying AI methods. This journey naturally sparked my interest in this field.
M.S. University of Kansas, Lawrence, KS
Major : Bioengineering – Computational Bioengineering
with Honors
GPA: 3.86/4.0
Advisor: Jiwoong Choi, PhD
B.S. University of Minnesota-Twin Cities, Minneapolis, MN
Major : Aerospace Engineering and Mechanics
GPA: 3.70 /4.0
Minor : Computer Science (B.A.)
GPA: 3.87 /4.0
Advisor : Hyun Soo Park, PhD
Experience
Research Scientist [Medipixel] August 2022 – Present
Led the MICCAI ARCADE Challenge 2023
  • 1st place in the coronary stenosis segmentation task
  • 2nd place in the coronary artery segmentation task
  • Developed a coronary angiography frame selection model
  • Developed an angiography based CFD model for coronary arteries
  • Automated a CFD pipeline using ANSYS Fluent (Pyfluent)
Graduate Research Experience

1

Quantitative CT Pipeline
Built a quantitative CT (QCT) pipeline for analysis, including deep learning airway and lung segmentation, image registration, and machine learning and statistical analysis.

2

Air Pollution Exposure Study
Participated in a Korea Environmental Industry & Technology Institute project on "CT image matching technology development for structural and functional assessment of environmentally induced lung disease" funded by the Korea Ministry of Environment. Conducted PCA and K-means clustering of air pollution exposure in adults with asthma, COPD, IPF, or no known lung disease, and performed statistical analysis to find associations between QCT variables and particulate matter exposure.
Undergraduate Research and Teaching
Computer Vision Research
As an Undergraduate Research Assistant in Computer Vision, I worked on processing the Human Multiview Behavior Imaging Dataset (HUMBI). This involved reconstructing 3D meshes of human bodies from 2D camera images, providing valuable insights into human behavior and movement.
Teaching Assistant
During my undergraduate studies, I served as a Teaching Assistant for the course AEM 3031 [Deformable Body Mechanics]. In this role, I assisted the instructor and supported students in their understanding of the course material.
Peer Tutoring
In addition to my research and teaching assistant roles, I was a SMART Learning peer tutor from September 2018 to May 2020. In this capacity, I tutored undergraduate students in various science and calculus courses, helping them succeed in their academic pursuits.
Military Service
Prior to my undergraduate studies, I served in the Korean Army as a Sergeant, where I worked as an ammunition specialist. This experience provided me with valuable skills and discipline that have contributed to my academic and professional development.
Activities
As an AI Kaggle Competition Expert (Top 1%), I am constantly pushing the boundaries of what is possible in the world of machine learning and data science. My expertise in this field has earned me a reputation as a leader in the industry, and I am proud to be recognized as being among the top 1% of Kaggle competitors.
In addition to my work in AI and data science, I have also taken on the role of President of the Korean American Society of Greater Kansas City. In this capacity, I was responsible for building the official website for the organization, which serves as a hub for the local Korean-American community. This work has been a labor of love, and I am honored to have the opportunity to contribute to the growth and development of this important organization.
Honors & Awards

2023

2023 MICCAI 2023: ARCADE challenge October 2023 Stenosis segmentation: 1st place Coronary artery segmentation: 2nd place 2023 Social Issues Data & AI Analysis Competition October 2023 2nd place ($1,600) Awarded by President of National Research Council Developed a deep learning precipitation nowcasting model The University of Kansas: Outstanding Master's Student Researcher Award May 2023 Selected as the most outstanding graduate master student researcher in bioengineering program

2022

2022 Burn Diagnosis AI Challenge - hosted by The Ministry of Science and ICT in Korea, November 2022 - 1st place ($2,400) Lung Cancer Segmentation Competition - hosted by Ajou University Medical Center, December 2022 - 2nd place ($2,400) RSNA 2022 Cervical Spine Fracture Detection - Bronze medal (October 2022) International Collaborative Asthma Network (ICAN) - Travel award for the oral presentation (March 2022) March Machine Learning Mania 2022: Men's - Silver medal (March 2022)

Scholarships & Fellowships

Scholarships & Fellowships Undergraduate Research Opportunity Program (UROP) Award, May 2019 - Participated HUMBI research as an undergraduate research assistant Chester Gaskell Aeronautical Engineering Scholarship - Merit-based scholarship given to top undergraduates who have outstanding academic records (Fall 2019) University of Minnesota: Dean's List (Fall 2014, Spring 2015, Fall 2017, Spring 2018, Fall 2018, Spring 2019)

Publication
Thesis
Lee IK. Extended Quantitative Computed Tomography Analysis of Lung Structure and Function. MS thesis, The University of Kansas, 2022.
Conference Paper
Lee IK, Shin J, Lee Y-H, Ku JH, Kim H-W. SASS: Semi-Supervised Approach for Stenosis Segmentation. Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs challenge (ARCADE). MICCAI Challenge 2023. (under review) | arXiv:2311.10281
Ku JH, Lee Y-H, Shin J, Lee IK, Kim H-W. MPSeg: Multi-Phase strategy for coronary artery Segmentation. Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs challenge (ARCADE). MICCAI Challenge 2023. (under review) | arXiv:2311.10306
Yu Z, Yoon JS, Lee IK, Venkatesh P, Park J, Yu J, Park HS. HUMBI: A Large Multiview Dataset of Human Body Expressions. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), virtual, June 16 - June 18, 2020.
Conference Abstract and Presentation
Quantitative CT and CFD
Lee IK, Choi J, Castro M, Kim T, Kang HR, LeeCH. Quantitative CT and CFD Explain Bronchodilator- induced Regional Ventilation Improvement in Asthma. International Collaborative Asthma Network (ICAN), San Francisco, CA, May 12-13, 2022. (oral and e-poster presentation)
Deep Transfer Learning
Lee IK, Choi J, Park EK, Tutkun E, Hoffman EA, Castro M, Lee CH. Toward extended quantitative CT imaging application with deep transfer learning. American Thoracic Society International Conference, San Diego, CA (virtual), May 14-19, 2021. Am J Respir Crit Care Med 2021;203:A4591 (poster)
Airway Remodeling
Boomer J, Lee IK, Kim T, Shi X, Christenson S, Nguyen J, Woodruff P, Peters M, Choi J, Castro M, for the National Heart, Lung, and Blood Institute's (NHLBI's) Severe Asthma Research Program (SARP) Investigators. Clinical Physiologic Variables, Transcriptomics and Proteomics Measures of Airway Remodeling Correlate to Non-Invasive qCT Metrics in Severe Asthma. International Collaborative Asthma Network (ICAN), San Francisco, CA, May 12-13, 2022. (oral and e-poster presentation)
Air Pollution Impacts
Choi J, Lee IK, Lee C-H, Choi S, Kang HR, Kim KN, Lee KS, Ko H, Chae KJ, Lin CL, Hoffman EA, Kim WJ, Park EK, Lee CH. Quantitative CT and Computational Fluid Dynamics Analysis of Air Pollution Impacts on Tidal Breathing in Asthma, COPD, and IPF Lungs. Radiological Society of North America Scientific Assembly and Annual Meeting, Chicago, IL, USA, November 27-December 1, 2022. (oral)
Quantitative CT Analysis Of Ambient Particulate MatterExposure
Asthma, COPD, and IPF Lungs
Quantitative CT analysis of ambient particulate matter exposure-associated multiscale structure and function alteration in healthy, asthma, COPD, and IPF lungs. The study was presented at the American Thoracic Society International Conference in San Francisco, CA in May 2022.
Healthy Old Adults and IPF Patients
Quantitative CT and computational fluid dynamics show SO2-associated altered regional lung structure and function relationship in healthy old adults and IPF patients. This work was presented at the 10th International Workshop on Pulmonary Functional Imaging (IWPFI) in Hannover, Germany in September 2022.
Radiological Society of North America
Quantitative CT analysis of ambient particulate matter exposure-associated multiscale structure and function alteration in healthy, asthma, COPD, and IPF lungs was presented at the Radiological Society of North America Scientific Assembly and Annual Meeting in Chicago, IL in November 2021.
Hyper-realistic Lung Model
Hyper-realistic lung model for quantitative CT and CFD-based lung assessment of personalized exposure to air pollution was presented at the 73rd Annual meeting of the American Physical Society (APS) Division of Fluid Dynamics in Chicago, IL (virtual) in November 2020.
Certifications & Patents
  1. Korean Patent [APE-2023-0723] September 2023
  • Method and apparatus for matching medical images considering phase of respiration signal
  1. Udacity: AI for healthcare Nanodegree September 2020
  1. NVIDIA: Fundamentals of accelerated computing with CUDA python June 2021
  1. Collaborative Institutional Training Initiative (CITI)
  • CITI Biomedical Researchers – Basic Course June 2020
  • GCP for clinical trials with investigational drugs and medical devices August 2021
  1. College Reading & Learning Association (CRLA) Certification | Certified Tutor October 2018
  • Level Ⅲ Master Tutor May 2019
Skill
  • Language: English, Chinese, Korean
  • Programming Language: MATLAB, Python, Fortran
  • Image Analysis and Visualization: SimpleITK, ITK-SNAP, VIDA Vision, Tecplot
  • Git