Da-In Lee

AI/ML Engineer with 3+ years of experience designing and deploying deep learning solutions for medical imaging and multi-modal data. Skilled in building high-performance models, automating end-to-end ML pipelines, and leveraging AWS services for scalable AI deployment. Experienced in collaborating with cross-functional teams and communicating technical concepts to stakeholders, ensuring AI solutions align with real-world needs.

• Development of an AI model for predicting MRI cerebrovascular events (Jul. 2024 to Jan. 2025, Medical Twin)
• Development of an AI navigation system for EVD brain surgery (Feb. 2024 to Jan. 2025, National Cancer Center)
• Development of a service for anonymizing medical images using AWS (Apr. 2023 to Jun. 2024, Medical IP)
• Development of an AI-based liver cancer prediction software for chronic hepatitis B patients and an AI-based liver cancer recurrence prediction software after curative treatment (Nov. 2022 to Mar. 2024, Doctor Answer 2.0)
• Development of a prognostic prediction model using TiSepX-based quantitative and qualitative assessments for acute infectious diseases (including COVID-19) (Nov. 2022 to Mar. 2024, CDSS (Clinical Decision Support System))
• Development of a rapid RT-PCR COVID-19 diagnostic system (Jul. 2021 to Mar. 2022, Hallym Kangnam Sacred Heart Hospital)
• Establishment of Language Resources for Automated Diagnosis of Language Disorders and Deep Learning/Natural Language Processing (Mar. 2021 to Feb. 2022, National Research Foundation of Korea)
• Development of an Aortic Dissection Detection System (Aug. to Dec. 2021, Hallym Kangnam Sacred Heart Hospital)
• Development of Commercial Technology for PSC Bridge Duct Exploration Using AI (Dec. 2020 to Dec. 2021, Korea SMEs and Startups Agency)

Engineer Information Processing License

• Deep learning for automatic volumetric bowel segmentation on body CT images (May 2025, Co-Author) European Radiology (SCIE)
• Detection of Aortic Dissection and Intramural Hematoma in Non-Contrast Chest Computed Tomography Using a You Only Look Once-Based Deep Learning Model (Nov. 2024, Co-Author) Journal of Clinical Medicine (SCIE)
• Comparison of the Diagnostic Performance of Deep Learning Algorithms for Reducing the Time Required for COVID-19 RT–PCR Testing (Jan. 2023, Co-Author) Viruses (SCIE)
• Utilization of LSTM Auto-Encoder for Duct Void Detection inside the PSC Box Girder Bridge (Feb. 2022, First Author) KIISE Transactions on Computing Practices (KCI)
• Utilization of Unsupervised Machine Learning for Detection of Duct Voids inside PSC Box Girder Bridges (Jan. 2022, First Author) Applied Sciences (SCIE)
• The application of a deep learning system developed to reduce the time for RT-PCR in COVID-19 detection (Jan. 2022, Co-Author) Scientific Reports (SCIE)
• Automatic Segmentation of Aorta in CT image using U-Net (Dec 2021, Co-Author) Korea Software Congress (Conf.)
• LSTM Auto-Encoder for Duct Void Detection (Jun 2021, First Author) Korea Computer Congress (Conf.)
• CNN Auto-Encoder for duct void detection inside PSC (Sep. 2021, First Author) International Conference on Applied System Innovation (Conf.)
• Vector-based word representation for media frame analysis: focused on covid-19 (Nov. 2020, First Author) Korea Information Processing Society (Conf.)
• Analysis of National petition contents and number of consents using K-Means Clustering (Jul. 2020, First Author) Korea Computer Congress (Conf.)

• Lung region segmentation method and device thereof (August 3, 2023 | 10-2023-0101745 (Republic of Korea)) (June 27, 2024 | 24185117.9 (Europe)) (July 2, 2024 | 18/762,627 (USA))
• Image reconstruction model generation method and device thereof, and image reconstruction method and device using the image reconstruction model (April 26, 2023 | 10-2023-0055001 (Republic of Korea) (April 26, 2024 | 24172731.2 (Europe)) (April 26, 2024 | 18/647,766 (USA))

• Korea Computer Congress 2021, Korean Institute of Information Scientists and Engineers, Jul. 2021

Outstanding Presentation Paper Award: Awarded for the paper titled ‘LSTM Auto-Encoder for Duct Void Detection’ in the field of artificial intelligence.

• Body Morphometry A.I. Segmentation Challenge, Wonkwang University Hospital Medical Convergence Research Center, Oct. 2021

The 2nd Prize in a competition to recognize normal kidneys and kidneys with cancer from medical CT images. Applied UNet++ with EfficientNet model based on the results of with various models.

• Hallym Bigdata AI Hackathon, Hallym University, Feb. 2022

Excellence Award, Conducted the project 'Creating Covid-19 Risk Index for each Seoul autonomous district'. Predicted cumulative number of confirmed cases with multiple linear regression model.

• Hallym AI+X R&D Challenge Contest, Hallym University, Jan. 2022

Gold Award in the Surgical Equipment Classification Track, The problem of classifying which surgical equipment was used in surgical scene images. Silver Award in Robot Surface Detection Track, The problem of classifying the types of surfaces by analyzing the acceleration data generated when the small robot impacts the surface. 

• Teaching Assistantship at KNU: Medical Imaging classification (Sep. to Oct. 2023)
• Teaching Assistantship at HU: Natural language processing (Undergraduate 3rd, 4th grade subject) Linear Algebra (undergraduate freshman subject) (Sep. 2021 to Dec. 2021)
• Conference Presentation: KCC (Jun 2021), ICASI (Sep. 2021)
• Poster Presentation: KIPS (Nov. 2020), KCC (Jul. 2020)

• China (Mar. 2018 to Jan. 2019) For Chinese language training, take one semester each at the Shanghai Ocean University in Shanghai and the Beijing Foreign Language University in Beijing (HSK5 級-230)
• Australia (Jan. 2017 to Jan. 2017) Take Unity game-related classes as an exchange student at Griffith University, Gold coast and perform game development projects (Project name: Surfing koala game)