Doohyun Park, Ph.D.

Research Scientist | Data Science · Computer Vision · Applied AI

I am a Research Scientist at VUNO with experience in data science, computer vision, and applied machine learning. My work focuses on analyzing complex real-world datasets, developing AI/ML models, evaluating model behavior, and translating data-driven findings into practical decision-support evidence.

I have worked across heterogeneous imaging domains and led industry-driven AI/ML projects. My broader interest is in using data-centric approaches to identify meaningful patterns, improve model reliability, and support real-world decision-making.

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News

2026

One paper accepted to the CVPRW 2026 - MMFM-BIOMED Workshop

2026

One paper accepted to ICLR 2026

2026

Two papers accepted to ISBI 2026

2025

One paper accepted to npj Precision Oncology (IF 9.9, JCR Top 11.0%)

2025

Two patents granted (US & KR)

Education

Mar. 2016 — Feb. 2024

Ph.D. in Electrical and Electronic Engineering

Yonsei University, Seoul, Republic of Korea

Dissertation: Artificial Intelligence-based Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer using Whole Slide Images

Advisor: Prof. Dosik Hwang

Mar. 2012 — Feb. 2016

B.S. in Electrical and Electronic Engineering

Yonsei University, Seoul, Republic of Korea

Selected Publications

[10] 2026 CVPRW - MMFM-BIOMED Workshop

When Prompts Mislead: Textual Dominance and Diagnostic Bias in MLLMs

Inhyuk Park, Doohyun Park†

† Corresponding author

URL

[09] 2026 ICLR

Frequency-Balanced Retinal Representation Learning with Mutual Information Regularization

Seunghoon Lee, Seongjae Kang, Inhyuk Park, Gitaek Kwon, Jihyeon Baek, Doohyun Park†

† Corresponding author

URL

[08] 2026 ISBI

Task-Agnostic Noisy Label Detection via Standardized Loss Aggregation

Inhyuk Park, Doohyun Park†

† Corresponding author

URL

[07] 2026 ISBI

A Comparative Study of Machine Learning and Deep Learning for Out-of-Distribution Detection

Jihyeon Baek, Seunghoon Lee, Gitaek Kwon, Doohyun Park†

† Corresponding author

URL

[06] 2025 npj Precision Oncology (JCR top 11.0%)

Multimodal AI model for preoperative prediction of axillary lymph node metastasis in breast cancer using whole slide images

Doohyun Park, Yong-Moon Lee, Taejoon Eo, Hee Jung An, Haeyoun Kang, Eunhyang Park, Yoon Jin Cha, Heejung Park, Dohee Kwon, Sun Young Kwon, Hye-Ra Jung, Su-Jin Shin, Hyunjin Park, Yangkyu Lee, Sanghui Park, Ji Min Kim, Sung-Eun Choi, Nam Hoon Cho, Dosik Hwang

URL

[05] 2024 Bioengineering (JCR top 40.7%)

A Comprehensive Review of Performance Metrics for Computer-Aided Detection Systems

Doohyun Park

URL

[04] 2024 Diagnostics (JCR top 17.0%)

Deep Learning-based Slice Thickness Reduction for Computer-Aided Detection of Lung Nodules in Thick Slice CT

Jonghun Jeong*, Doohyun Park*, Jung-Hyun Kang, Myungsub Kim, Hwa-Young Kim, Woosuk Choi, Soo-Youn Ham

* Equally contributed

URL

[03] 2024 European Radiology (JCR top 12.4%)

Weakly-Supervised Deep Learning for Multi-Label Classification of Vertebral Compression Fracture in CT

Euijoon Choi*, Doohyun Park*, Geonhui Son, Seongwon Bak, Taejoon Eo, Daemyung Youn, Dosik Hwang

* Equally contributed

URL

[02] 2023 Scientific Reports (JCR top 18.3%)

Development and Validation of A Hybrid Deep Learning-Machine Learning Approach for Severity Assessment of COVID-19 and Other Pneumonias

Doohyun Park, Ryoungwoo Jang, Myung Jin Chung, Hyun Joon An, Seongwon Bak, Euijoon Choi, Dosik Hwang

URL

[01] 2022 European Radiology (JCR top 11.5%)

Importance of CT Image Normalization in Radiomics Analysis: Prediction of 3-Year Recurrence-Free Survival in Non-Small Cell Lung Cancer

Doohyun Park, Daejoong Oh, MyungHoon Lee, Shin Yup Lee, Kyung Min Shin, Johnson SG Jun, Dosik Hwang

URL

Other Publications

[24] 2026 ISBI, International Symposium on Biomedical Imaging (Abstract)

Prompt-Induced Bias from One-Shot Multimodal Large Language Models Prompting in Medical Imaging

Inhyuk Park, Jihyeon Baek, Doohyun Park

[23] 2026 ISBI, International Symposium on Biomedical Imaging (Abstract)

Prompt Dominance in Medical Multimodal Large Language Models

Inhyuk Park, Jihyeon Baek, Doohyun Park

[22] 2025 npj Digital Medicine

Interpretable Multimodal Transformer for Prediction of Molecular Subtypes and Grades in Adult-type Diffuse Gliomas

Yunsu Byeon, Yae Won Park, Soohyun Lee, Doohyun Park, HyungSeob Shin, Kyunghwa Han, Jong Hee Chang, Se Hoon Kim, Seung-Koo Lee, Sung Soo Ahn, Dosik Hwang

[21] 2025 Preprints

Multi-center Validation of Pulmonary Nodule Classification Model for Lung Cancer Screening

Doohyun Park, Jung-Hyun Kang, Changhyun Park

[20] 2025 MIDL, Medical Imaging with Deep Learning (Short Paper)

Attention-based Interpretable Deep Learning with Radiomic Features for Pulmonary Nodule Classification

Doohyun Park, Nahyuk Lee, Sungjoo Lim

[19] 2025 ECR (Oral Presentation), European Congress of Radiology

Foundation Model-based Unsupervised CT Kernel Conversion for Standardizing Emphysema Quantification

Doohyun Park, Jung-Hyun Kang, Jonghun Jeong

[18] 2025 ECR, European Congress of Radiology

Evaluation Metrics for Computer-Aided Detection Systems in Medical AI: What You Need to Know

Doohyun Park

[17] 2025 JRC, Japan Radiology Congress

Deep Learning-based Lesion Segmentation for Patients with Usual Interstitial Pneumonia in High-Resolution CT: A pilot study

Doohyun Park, Jung-Hyun Kang, Jonghun Jeong, Kyoung Min Moon

[16] 2025 JRC, Japan Radiology Congress

Fully Automated Segment-Anything-Model for Robust Lobe Segmentation in Patients with Interstitial Lung Disease

Sungjoo Lim, Doohyun Park, Jonghun Jeong, Changhyun Park, Kyoung Min Moon

[15] 2025 JRC, Japan Radiology Congress

Deep Learning-based Slice Thickness Reduction for Lung Nodule Detection of Thick Slice Chest CT

Jonghun Jeong, Doohyun Park, Jung-Hyun Kang, Myungsub Kim, Hwa-Young Kim, Woosuk Choi, Soo-Youn Ham

[14] 2024 WCLC, World Conference on Lung Cancer

Nodule Type Classification for Lung Cancer Screening with CT

Doohyun Park, Jung-Hyun Kang, Changhyun Park, Jinyoung Kim

[13] 2024 ESTI, European Society of Thoracic Imaging

A Standardized Performance Evaluation Metric for Chest CT Nodule Detection

Doohyun Park, Chanmin Park, Jung-Hyun Kang, Jinyoung Kim

[12] 2024 RSNA, Radiological Society of North America

A Multi-center Retrospective Study of Nodule Type Classification using Artificial Intelligence for Lung-RADS Scoring with CT

Doohyun Park, Jung-Hyun Kang, Changhyun Park, Jonghun Jeong

[11] 2024 RSNA, Radiological Society of North America

Quantity or Certainty: Can Ambiguously Annotated Data Improve Lung Nodule Detection Performance?

Chanmin Park, Jung-Hyun Kang, Doohyun Park, Jonghun Jeong

[10] 2024 MICCAI, Medical Image Computing and Computer Assisted Intervention

LLM-guided Multi-modal Multiple Instance Learning for 5-year Overall Survival Prediction of Lung Cancer

Kyungwon Kim, Yongmoon Lee, Doohyun Park, Taejoon Eo, Daemyung Youn, Hyesang Lee, Dosik Hwang

[09] 2024 ISMRM (Oral Presentation), International Society for Magnetic Resonance in Medicine

Unified Diffusion model for Multi-contrast Ensembling Synthesis

Yeeun Lee, Yejee Shin, Doohyun Park, Geonhui Son, Taejoon Eo, Dosik Hwang

[08] 2024 ISMRM (Oral Presentation), International Society for Magnetic Resonance in Medicine

Deep Learning Algorithm for Prediction of Molecular Subtypes and Grades in Adult-type Diffuse Gliomas: According to the 2021 WHO Updates

Yunsu Byeon, Yae Won Park, Soohyun Lee, Hyungseob Shin, Doohyun Park, Sung Soo Ahn, Seung-Koo Lee, Dosik Hwang

[07] 2024 Diagnostics

Deep Learning-based Joint Effusion Classification in Adult Knee Radiographs: A Multi-Center Prospective Study

Hyeyeon Won, Hye Sang Lee, Daemyung Youn, Doohyun Park, Taejoon Eo, Wooju Kim, Dosik Hwang

[06] 2023 LNCS, Lecture Notes in Computer Science (MICCAI SEG.A Technical Paper)

M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography

Yunsu Byeon, Hyeseong Kim, Kyungwon Kim, Doohyun Park, Euijoon Choi, Dosik Hwang

[05] 2023 CICS - Conference on Information and Control Systems

Foundation Models in Healthcare: Applications, Challenges, and Future Directions

Hyeyeon Won, Doohyun Park, Taejoon Eo, Yeeun Lee, Dosik Hwang

[04] 2018 ISMRM, International Society for Magnetic Resonance in Medicine

Iterative Cross-Domain Deep-Learning Approach for Reconstructing Undersampled Radial MRI

Doohyun Park, Taejoon Eo, Taeseong Kim, Jinseong Jang, Dosik Hwang

[03] 2018 ISMRM, International Society for Magnetic Resonance in Medicine

Deep Sinogram Learning for Radial MRI: Comparison with k-space and Image Learning

Taeseong Kim, Taejoon Eo, Doohyun Park, Yohan Jun, Dosik Hwang

[02] 2018 Medical Physics

Correction of severe beam‐hardening artifacts via a high‐order linearization function using a prior‐image‐based parameter selection method

Daejoong Oh, Sewon Kim, Doohyun Park, Seungwon Choi, Hundong Song, Yunsu Choi, Seunghyuk Moon, Jongduk Baek, Dosik Hwang

[01] 2017 SPIE Medical Imaging

Beam Hardening Correction Using Length Linearization

Daejoong Oh, Sewon Kim, Doohyun Park, Dosik Hwang

Patents

[14] 2026 KR Application (10-2026-0068438)

Apparatus, method and computer program of training image encoder

[13] 2026 KR Application (10-2026-0031507)

Apparatus, method and computer program for detecting noisy data

[12] 2025 US Granted (US12500003B2)

Method of predicting prognosis of patient with adenocarcinoma using image feature

[11] 2025 KR Granted (10-2758775)

Method for Predicting Prognosis in Cancer Patient Using Radiomic Feature

[10] 2024 EPO Application (EP4218032A4)

Method of predicting prognosis of patient with adenocarcinoma using image feature

[09] 2024 KR Application (10-2024-0176698)

Method for outputting segmentation information for an image and device therefor

[08] 2023 US Granted (US11748980B2)

Makeup evaluation system and operating method thereof

[07] 2022 CN Granted (CN110235169B)

Cosmetic evaluation system and operation method thereof

[06] 2022 JP Granted (JP7020626B2)

Makeup evaluation system and its operation method

[05] 2021 US Granted (US11113511B2)

Makeup evaluation system and operating method thereof

[04] 2021 KR Granted (10-2305806)

Method for Prodicting Prognosis in Lung Cancer Patient using Clinical Information and Gene Polymorphism Information

[03] 2020 EPO Application (EP3579176A4)

Makeup evaluation system and operation method thereof

[02] 2020 KR Granted (10-2066892)

Make-up evaluation system and operating method thereof

Technology transfer: ₩20,000,000

[01] 2019 KR Granted (10-2039472)

Device and Method for Reconstructing Computed Tomography Image

Projects

Representation Learning for Fine-Grained Visual Patterns

Developed self-supervised learning methods to capture subtle local patterns in large-scale image datasets, especially when task-specific labels are limited or expensive to obtain.

Noisy Label Detection and Dataset Refinement

Designed data-centric methods to identify potentially mislabeled samples, supporting more reliable training datasets, cleaner evaluation sets, and more trustworthy model development.

Image Enhancement for Downstream Analysis

Developed deep learning-based image enhancement methods to improve the visibility of small or subtle visual structures before applying downstream detection or classification models.

Weakly Supervised Detection with Limited Annotation

Built weakly supervised learning frameworks that use coarse image-level labels to infer more detailed object-level or region-level patterns, reducing the need for exhaustive manual annotation.

Multimodal Modeling from Images and Structured Data

Developed models that combine visual features from large-scale images with structured variables, enabling prediction workflows that use complementary information from multiple data sources.

Robust Modeling Across Heterogeneous Data Conditions

Studied preprocessing, normalization, and feature selection strategies to improve model robustness when data are collected under different acquisition settings, devices, or environments.

Evaluation Frameworks for Detection Models

Organized evaluation criteria for detection systems by separating image-level and object-level performance concepts, supporting clearer model comparison and failure analysis.

Out-of-Distribution Detection for Reliable Deployment

Compared methods for identifying samples that differ from the training distribution, with an emphasis on model reliability, practical deployment constraints, and data quality monitoring.

Data-Driven Workflow and Decision Analysis

Translated model outputs into scenario-based workflow analyses, focusing on how predictive models can support operational decisions, workload reduction, and evidence-based process design.

Curriculum Vitae

Download my full CV.

Download CV (PDF)

Contact

Email

dhpark.ee@gmail.com

Location

Seoul, Republic of Korea

Affiliation

VUNO Inc. (Research Scientist)