Doohyun Park | Computer Science | Best Researcher Award

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Dr. Doohyun Park | Computer Science | Best Researcher Award

VUNO Inc. | South Korea

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Early Academic Pursuits 🎓

Dr. Doohyun Park embarked on his academic journey at Yonsei University, where he earned his Bachelor's degree in Electrical and Electronic Engineering (2012-2016). His deep interest in medical applications of technology led him to pursue a Ph.D. at the same institution. His doctoral thesis focused on artificial intelligence-based preoperative prediction of axillary lymph node metastasis in breast cancer using whole slide images, which showcases his commitment to integrating AI in healthcare. His academic path laid the foundation for his future contributions to biomedical research and medical image analysis.

Professional Endeavors 💼

Dr. Park’s professional career is marked by his significant role at VUNO Inc., where he is part of the Lung Vision AI team. His work involves the development of computer-aided detection and diagnosis (CADe/CADx) on lung CT, focusing on innovative solutions for lung health. He has also worked on projects assessing the severity of COVID-19 and anomaly detection in spine CT. His expertise in the intersection of AI and healthcare has positioned him as a key contributor to advanced diagnostic technologies, reflecting his ability to bridge academia and industry.

Contributions and Research Focus 🔬

Dr. Park's research interests are centered around biomedical and clinical research, with a particular emphasis on computer-aided detection, diagnosis, and medical image analysis. He has published numerous papers on topics ranging from deep learning-based joint effusion classification to the development of AI models for lung cancer screening. His research has garnered recognition in top-tier journals, reinforcing his role in advancing AI applications in healthcare. He also holds multiple international and domestic patents related to prognosis prediction using image features, underscoring his contributions to the global research community.

Accolades and Recognition 🏆

Dr. Park’s outstanding contributions to medical image analysis have earned him several prestigious awards. Notably, he won the Best Paper Award at the 2023 MICCAI Grand Challenge for Aorta Segmentation and secured third place in the competition. His academic excellence has also been recognized through scholarships, including the Brain Korea 21 Scholarship and various research and teaching assistant scholarships during his time at Yonsei University. His consistent track record of achievements highlights his dedication to both research and education.

Impact and Influence 🌍

Dr. Park's work has had a profound impact on the field of medical AI, particularly in improving diagnostic tools for lung and breast cancer. His development of cutting-edge algorithms for image analysis has the potential to revolutionize early detection and prognosis in clinical settings. His invited talks at high-profile forums like the Global Engagement & Empowerment Forum on Sustainable Development (GEEF) further showcase his influence on global health initiatives, particularly in the context of the United Nations' Sustainable Development Goals.

Legacy and Future Contributions ✨

As Dr. Park continues his career, his legacy is being built on the foundations of innovation, interdisciplinary collaboration, and a commitment to improving healthcare outcomes. His ongoing projects, including AI-based lung cancer screening and prognosis prediction for adenocarcinoma, promise to shape the future of diagnostic medicine. With a robust portfolio of patents, publications, and collaborative research, Dr. Park is poised to make lasting contributions to both academic and clinical communities, further solidifying his role as a pioneer in medical AI.

 

Publications

📝 Deep Learning-Based Joint Effusion Classification in Adult Knee Radiographs: A Multi-Center Prospective Study
Authors: Hyeyeon Won, Hye Sang Lee, Daemyung Youn, Doohyun Park, Taejoon Eo, Wooju Kim, Dosik Hwang
Journal: Diagnostics
Year: 2024

📝 M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography
Authors: Yunsu Byeon, Hyeseong Kim, Kyungwon Kim, Doohyun Park, Euijoon Choi, Dosik Hwang
Journal: Book Chapter
Year: 2024

📝 Weakly Supervised Deep Learning for Diagnosis of Multiple Vertebral Compression Fractures in CT
Authors: Euijoon Choi, Doohyun Park, Geonhui Son, Seongwon Bak, Taejoon Eo, Daemyung Youn, Dosik Hwang
Journal: European Radiology
Year: 2023

📝 Development and Validation of a Hybrid Deep Learning–Machine Learning Approach for Severity Assessment of COVID-19 and Other Pneumonias
Authors: Doohyun Park, Ryoungwoo Jang, Myung Jin Chung, Hyun Joon An, Seongwon Bak, Euijoon Choi, Dosik Hwang
Journal: Scientific Reports
Year: 2023

📝 Importance of CT Image Normalization in Radiomics Analysis: Prediction of 3-Year Recurrence-Free Survival in Non-Small Cell Lung Cancer
Authors: Doohyun Park, Daejoong Oh, MyungHoon Lee, Shin Yup Lee, Kyung Min Shin, Johnson SG Jun, Dosik Hwang
Journal: European Radiology
Year: 2022

 

Soopil Kim | Computer Science | Best Researcher Award

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Dr. Soopil Kim | Computer Science | Best Researcher Award

Daegu Gyeongbuk Institute of Science and Technology | South Korea

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Early Academic Pursuits 🎓

Dr. Soopil Kim's academic journey began with a Bachelor of Engineering in Robotics and Mechatronics Engineering from Daegu Gyeongbuk Institute of Science & Technology (DGIST), where he graduated Cum Laude. He continued his studies at DGIST, pursuing a Master’s and Ph.D. in the same field, focusing on medical image segmentation. His research during these years emphasized label-efficient segmentation models and limited pixel-level annotation, laying a strong foundation for his future work in deep learning and computer vision.

Professional Endeavors 💼

Dr. Kim's career has seen significant milestones, including a role as a Visiting Student at Stanford University's CNSLAB under the supervision of Prof. Kilian M. Pohl and Ehsan Adeli. Currently, he is a Post-Doctoral Research Fellow at the Medical Image & Signal Processing Lab (MISPL) at DGIST, where he works under Prof. Sang Hyun Park. His professional trajectory reflects a commitment to advancing the field of computer vision through innovative research and collaboration.

Contributions and Research Focus 🔬

Dr. Kim’s research is at the forefront of deep learning and computer vision. His work addresses the challenges of image segmentation with partially labeled datasets by developing federated learning strategies and few-shot segmentation techniques. His notable contributions include the creation of a medical image segmentation model that integrates meta-learning and bi-directional recurrent neural networks, a semi-supervised segmentation model based on uncertainty estimation, and a transductive segmentation model for industrial imaging. These advancements aim to improve the efficiency and accuracy of image segmentation processes.

Accolades and Recognition 🏆

Dr. Kim has received several awards that highlight his exceptional contributions to the field. Notably, he was ranked 3rd among 40 teams in the SNUH Sleep AI Challenge in 2021 and was honored with the Outstanding Student Award from the Department of Robotics and Mechatronics Engineering at DGIST in 2022. In 2024, he was recognized at the KCCV Oral/Poster Presentation Doctoral Colloquium for his work on label-efficient segmentation models.

Impact and Influence 🌍

Dr. Kim's research has made a significant impact on the field of computer vision, particularly in the area of image segmentation. His innovative approaches to handling partially labeled datasets and federated learning have the potential to advance both academic research and practical applications in medical imaging and beyond. His work on few-shot learning and uncertainty-aware models addresses critical challenges in the field, contributing to more robust and adaptable segmentation solutions.

Legacy and Future Contributions 🚀

As Dr. Kim continues his research, his focus on improving segmentation models and developing new methodologies promises to shape the future of computer vision. His commitment to exploring federated learning and few-shot learning techniques will likely drive further innovations in the field, offering solutions to complex challenges and enhancing the accuracy of image analysis across various applications.

 

Publications 📘

📄Few-shot anomaly detection using positive unlabeled learning with cycle consistency and co-occurrence features
Authors: Sion An, Soopil Kim, Philip Chikontwe, Jiwook Jung, Hyejeong Jeon, Jaehong Kim, Sang Hyun Park
Journal: Expert Systems with Applications
Year: 2024

📄Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets
Authors: Soopil Kim, Haejun Park, Myeongju Kang, Kilian M. Pohl, Sang Hyun Park
Journal: Medical Image Analysis
Year: 2024

📄FedNN: Federated learning on concept drift data using weight and adaptive group normalizations
Authors: Myeongju Kang, Soopil Kim, Kwang-Hyun Jin, Kilian M. Pohl, Sang Hyun Park
Journal: Pattern Recognition
Year: 2024

📄Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection
Authors: Soopil Kim, Sion An, Philip Chikontwe, Kilian M. Pohl, Sang Hyun Park
Conference: Proceedings of the AAAI Conference on Artificial Intelligence
Year: 2024

📄Uncertainty-aware semi-supervised few shot segmentation
Authors: Soopil Kim, Philip Chikontwe, Sion An, Sang Hyun Park
Journal: Pattern Recognition
Year: 2023

 

Van Bo Nguyen | Engineering | Excellence in Research Award

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Van Bo Nguyen |  Excellence in Research Award -  Award Winner 2023

Van Bo Nguyen | Engineering

Van Bo Nguyen, congratulations on receiving the prestigious Excellence in Research Award! Your dedication and brilliance in the realm of computational engineering, particularly in fluid dynamics and advanced manufacturing, have set an unparalleled standard. Your innovative research endeavors, spanning pulse detonation engines, erosion analysis, and AI-assisted process optimization, have not only advanced scientific understanding but have also paved the way for groundbreaking applications across industries. Your commitment to mentorship and academic excellence further underscores the impact of your contributions, inspiring the next generation of computational engineers.

Your exceptional achievements, marked by a prolific publication record and leadership in pioneering projects, exemplify a relentless pursuit of knowledge and innovation. Your legacy as a trailblazer in computational engineering is not just a testament to your exceptional skills, but also to your profound impact on reshaping the boundaries of fluid dynamics and computational modeling. This award rightfully recognizes your unparalleled dedication and marks yet another milestone in your illustrious career. Here's to celebrating your exceptional achievements and the continued brilliance you bring to the field! Congratulations once again on this well-deserved honor!

Early Academic Pursuits

Van Bo Nguyen's academic journey commenced with a Bachelor of Engineering in Aerodynamics, Fluid Mechanics, Hydraulic Machinery, and Automation from the Hanoi University of Science and Technology in Vietnam, securing First Class Honors. He furthered his studies, attaining a Master's in Aeronautical and Astronautical Engineering from the Institute of Technology Bandung in Indonesia. His academic prowess culminated in a Doctor of Philosophy in Computational Engineering from the joint program between the National University of Singapore and the Massachusetts Institute of Technology through the Singapore-MIT Alliance.

Professional Endeavors & Research Focus

His professional trajectory showcases a remarkable focus on computational engineering, particularly in the realm of fluid dynamics and its applications across diverse sectors. His roles at the Institute of High-Performance Computing, A*STAR Singapore, and the Temasek Laboratories at the National University of Singapore highlight his expertise in spearheading research projects related to Flow System Integration, Pulse Detonation Engines, Chemical Processing, Shot Peening, and more. His contributions have been pivotal in developing AI/ML-assisted modeling, process optimization platforms, and advanced control systems for various industries, including aerospace, manufacturing, and marine engineering.

Contributions and Research Impact

Van Bo Nguyen's contributions extend beyond academia, with a prolific publication record that illuminates his extensive research in aerospace propulsion systems, mathematical modeling, AI, and advanced manufacturing processes. His papers in renowned journals and presentations at international conferences underscore his expertise in detonation waves, reacting flow applications, erosion characteristics, and shot peening process optimization.

Notable Publication

Slurry erosion characteristics and erosion mechanisms of stainless steel  November 2014

Effect of impact angle and testing time on erosion of stainless steel at higher velocities 30 December 2014

A numerical study on the effect of particle shape on the erosion of ductile materials  15 May 2014

Predicting shot peening coverage using multiphase computational fluid dynamics simulations  April 2014

A study of detonation re-initiation through multiple reflections in a 90-degree bifurcation channel  June 2017

Modeling transient fluid simulations with proper orthogonal decomposition and machine learning  30 June 2020

Accolades and Recognition

His journey is adorned with accolades such as the Best Researcher Award and numerous project lead roles, indicating his profound impact on the scientific community. His involvement as a mentor for students and his role in guiding numerical modeling aspects for rotating and pulse detonation engines at Temasek Laboratories signify his commitment to nurturing future talent in computational engineering.

Legacy and Future Contributions

Van Bo Nguyen's legacy lies in his multifaceted contributions to computational engineering, notably in revolutionizing fluid dynamics applications across industries. His pioneering research in pulse detonation engines, erosion analysis, and shot peening process optimization forms a strong foundation for future advancements in aerospace, manufacturing, and energy sectors. His enduring commitment to innovative research, mentorship, and academic excellence ensures a continued legacy of groundbreaking contributions to the field of computational engineering.

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