Hah Min Lew

AI Researcher at Klleon

I’m an AI Researcher at Klleon.

Data-centric approaches leading to ML systems can solve valuable real-world problems. I value building efficient systems through agile trials and errors based on a clarified problem. Proactively growing, challenging, and sharing are my core values and attitude toward my life. My recent projects are as follows:

  • Virtual Human Dialogue System
  • Diffusion Model
  • Finetuning
  • Vector Quantization

Conference Publications

  • Chroma-HS: High-Fidelity Industrial Head Swapping with Chroma Keying [project page]
    Hah Min Lew*, Sahng-Min Yoo*, Hyunwoo Kang*, and Gyeong-Moon Park (* equal contribution)
    In Submission to ECCV 2024

  • Synthetic High-Resolution In-Depth Ultrasound Imaging via Test-time Adaptation with an Attachable Dual-Element Endoscopic Ultrasound Probe
    Moon Hwan Lee, Hah Min Lew, Jae Seong Kim, Jaegeun Park, Sangyeon Youn, Jihun Kim, Hee Man Kim, and Jae Youn Hwang
    In Submission to MICCAI 2024

  • Deep Learning-based Synthetic High-Resolution In-Depth Imaging Using an Attachable Dual-element Endoscopic Ultrasound Probe [paper]
    Hah Min Lew*, Jae Seong Kim*, Moon Hwan Lee, Jaegeun Park, Sangyeon Youn, Hee Man Kim, Jihun Kim, and Jae Youn Hwang (* equal contribution)
    Arxiv Preprint 2023

  • CSS-Net: Classification and Substitution for Segmentation of Rotator Cuff Tear [paper]
    Kyungsu Lee, Hah Min Lew, Moon Hwan Lee, Minji Kang, Junyoung Kim, and Jae Youn Hwang
    ACCV 2022

Journal Publications

  • Deep learning-based framework for fast and accurate acoustic hologram generation [paper]
    Moon Hwan Lee, Hah Min Lew, Sangyeon Youn, Tae Kim, and Jae Youn Hwang
    IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (IF: 3.267, Featured on the front cover) 11.04.2022.

  • Multi-task and Few-shot Learning-based Fully Automatic Deep Learning Platform for Mobile Diagnosis of Skin Diseases [paper]
    Kyungsu Lee, Thiago Coutinho Cavalcanti, Sewoong Kim, Hah Min Lew, Dong Hun Lee, and Jae Youn Hwang.
    IEEE Journal of Biomedical and Health Informatics (IF: 7.021) 07.25.2022.

  • Speckle Reduction via Deep Content-Aware Image Prior for Precise Breast Tumor Segmentation in an Ultrasound Image [paper]
    Haeyun Lee, Moon Hwan Lee, Sangyeon Youn, Kyungsu Lee, Hah Min Lew, and Jae Youn Hwang.
    IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (IF: 3.267) 07.25.2022.

  • Intelligent Smartphone-based Multimode Imaging Otoscope for the Mobile Diagnosis of Otitis Media [paper]
    Thiago Coutinho Cavalcanti, Hah Min Lew, Kyungsu Lee, Sang-yeon Lee, Moo Kyun Park, and Jae Youn Hwang.
    Biomedical Optics Express (IF: 3.562, Spotlight on Optics) 11.23.2021.

  • Ultrasonic Blood Flowmeter with a Novel Xero Algorithm for a Mechanical Circulatory Support System [paper]
    Hah Min Lew, Heean Shin, Moon Hwan Lee, Sangyeon Youn, Hee Chan Kim, and Jae Youn Hwang.
    Ultrasonics (IF: 4.062) 08.01.2021.

  • Forward-looking Multimodal Endoscopic System based on Optical Multispectral and High-frequency Ultrasound Imaging Techniques for Tumor Detection [paper]
    Jihun Kim, Hah Min Lew, Jung-Hee Kim, Sangyeon Youn, Hasan Al Faruque, An Na Seo, Soo Yeun Park, Jin Ho Chang, Enjoo Kim, and Jae Youn Hwang.
    IEEE Transactions on Medical Imaging (IF: 11.037) 10.20.2020.

Work Experiences

  • AI Researcher, Klleon AI Research, Seoul, South Korea, Aug. 2022 - present
    • Building efficient data preprocessing pipelines and generative models for a virtual human dialogue system.
    • Tasks: Vector Quantization, Text-to-Image Generation, ML-based Image Captioning, Head Swapping, Neural Talking Head Synthesis, Explicit Controllable 3D Parameterized Modeling.
  • Graduate Researcher, Multimodal Biomedical Imaging and System Lab, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea, Mar. 2019 - Aug. 2022
    • Advisor: Prof. Jae Youn Hwang
    • 6 SCIE publications, 7 international conferences, 9 projects, 6 patents, and 2 awards.
    • ML-based anomaly labeling and generative model design for various biomedical applications under multimodal, class-imbalance, and multi-task problems.
    • Development of application-specific systems integrating hardware and software.
    • Advanced signal processing and computer vision skills.
    • Collaborative research experiences with medical doctors (e.g., SNUH, SNUDH, Yonsei Severance).
  • Co-founder, LANTERN, Daegu, South Korea, Nov. 2016 - July 2017
    • Founded a data-driven personalized tutor matching service company. Co-working with Class101 .

Education

  • M.S. in Electrical Engineering & Computer Science (EECS), Daegu Gyeongbuk Institute of Science and Technology (DGIST), Mar. 2019 - Aug. 2021

  • B.E. in Bachelor of Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Mar. 2014 - Feb. 2019 - (Best Project Award)