Ting-Ting Chang | Medicine and Dentistry | Best Researcher Award

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Assoc Prof Dr. Ting-Ting Chang l Medicine and Dentistry l Best Researcher Award

Associate Professor at National Yang Ming Chiao Tung University, Taiwan

Dr. Ting-Ting Chang is an Associate Professor at National Yang Ming Chiao Tung University, specializing in vascular medicine, kidney disease, diabetes, and new drug development. With a Ph.D. from National Yang-Ming University, Dr. Chang has a robust publication record in high-impact journals, including Science Translational Medicine and Angiogenesis. Recognized with awards such as the Young Scientists Award and the Young Investigator Fellowship, Dr. Chang is also a full member of Sigma Xi and other prestigious societies. Their research is notable for its innovation and significant contributions to understanding and treating complex diseases.

Profile:

Education

Ting-Ting Chang, Ph.D., earned her Ph.D. in Pharmacology from National Yang-Ming University in Taipei, Taiwan, in 2015. Her educational journey is distinguished by her continued academic and research excellence, which laid a strong foundation for her current role as an Associate Professor in the Department and Institute of Pharmacology at National Yang Ming Chiao Tung University. Prior to this, Dr. Chang completed her post-doctoral research at the same institution, further solidifying her expertise in pharmacology and related fields.

Professional Experience

Ting-Ting Chang, Ph.D., is an accomplished researcher and academic with extensive experience in the field of pharmacology. Currently serving as an Associate Professor at the Department and Institute of Pharmacology, National Yang Ming Chiao Tung University, Dr. Chang has previously held roles as an Assistant Professor and Post-doctoral Researcher at the same institution. Their career spans significant contributions to vascular medicine, kidney disease, diabetes, and new drug development, with a track record of high-impact research and numerous publications in leading scientific journals.

Research Interest

Ting-Ting Chang’s research interests encompass a broad range of topics within vascular medicine and molecular biology, focusing on the mechanisms underlying vascular dysfunction, kidney disease, and diabetes mellitus. Her work includes experimental animal model design and new drug development, aiming to uncover novel therapeutic targets and strategies for these critical health issues. Dr. Chang’s research integrates molecular and cellular approaches to address complex pathological conditions, contributing significantly to advancements in understanding and treating vascular and metabolic disorders.

Research Skills

Ting-Ting Chang, Ph.D., demonstrates exceptional research skills through a robust portfolio of high-impact publications and significant contributions to fields such as vascular medicine, kidney disease, and diabetes. With a strong academic background and extensive experience as both an Associate Professor and Post-doctoral Researcher, Dr. Chang excels in designing and conducting innovative studies, particularly in identifying novel therapeutic targets and mechanisms. Their proficiency in experimental animal model design and new drug development further highlights their expertise, while their membership in prestigious scientific societies and receipt of notable awards underscore their recognition and influence in the research community.

Award and Recognition

Ting-Ting Chang, Ph.D., has garnered significant awards and recognition throughout their career, underscoring their outstanding contributions to research. Notably, Dr. Chang received the Young Scientists Award at the 55th Annual Scientific Meeting of the Japan Atherosclerosis Society in 2023 and the Young Investigator Fellowship Award at the 88th European Atherosclerosis Society Congress in 2020. In addition, Dr. Chang was awarded full membership of Sigma Xi in 2023, reflecting their esteemed position in the scientific community and their impactful research in vascular medicine, kidney disease, and diabetes.

Conclusion

Ting-Ting Chang, Ph.D., is a highly qualified candidate for the Best Researcher Award. Their exceptional contributions to vascular medicine, kidney disease, and diabetes, along with a strong publication record and recognition in the scientific community, underscore their suitability for this award. Addressing areas for improvement, such as expanding research applications and increasing public engagement, could further enhance their profile as a leading researcher. Overall, Dr. Chang’s dedication, innovative research, and professional achievements make them an excellent contender for the Best Researcher Award.

Publication Top Notes

  • Association between vitiligo and risk of retinal detachment: a population-based cohort study in Taiwan
    • Authors: Chen, C.-L., Wu, C.-Y., Chen, Y.-L., Chang, Y.-T., Wu, C.-Y.
    • Year: 2024
    • Citations: 0
  • Rejuvenation of the dorsal hand by injectable poly-D, L-lactic acid: A pilot study
    • Authors: Ma, S.-H., Lin, C.-Y., Lin, J.-Y., Chang, Y.-T., Chen, C.-C.
    • Year: 2024
    • Citations: 0
  • Correlation of Disease Severity, Proinflammatory Cytokines, and Reduced Brain Gray Matter Volumes in Patients with Atopic Dermatitis
    • Authors: Li, C.-Y., Chang, W.-C., Chen, M.-H., Chen, Y.-Y., Bai, Y.-M.
    • Year: 2024
    • Citations: 0
  • Risk of Type 1 Diabetes Mellitus in Patients with Atopic Dermatitis: A Nationwide Population-Based Cohort Study
    • Authors: Li, M.-C., Wu, C.-Y., Chang, Y.-T., Lyu, Y.-S., Wu, C.-Y.
    • Year: 2023
    • Citations: 0
  • Assoziation zwischen chronischer Nierenerkrankung und dem Risiko für bullöses Pemphigoid: eine nationale bevölkerungsbasierte Kohortenstudie
    • Authors: Yu, W.-T., Ma, S.-H., Wu, C.-Y., Chang, Y.-T., Wu, C.-Y.
    • Year: 2023
    • Citations: 1

Hyun-Soo Choi | Medical Domain | Best Researcher Award

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Prof Dr. Hyun-Soo Choi | Medical Domain | Best Researcher Award

Assistant Professor at Seoul National University of Science and Technology, South Korea

Dr. Hyun-Soo Choi is an Assistant Professor in the Department of Computer Science and Engineering at Seoul National University of Science and Technology. He holds a Ph.D. in Electrical and Computer Engineering from Seoul National University. His research focuses on artificial intelligence, machine learning, deep learning, biomedical data learning, and causal inference. With significant contributions to the field, Dr. Choi has published extensively in renowned journals, including IEEE Transactions on Neural Networks and Learning Systems and the Journal of Clinical Medicine. His work on deep learning-based medical diagnostics and imbalanced data classification has garnered attention for its innovative approaches and practical applications. In addition to his academic role, he serves as the Chief Technical Officer at Ziovision and has previously worked as a researcher at SK Telecom. Dr. Choi has received accolades such as the Annual Excellence Award from Seoul National University, recognizing his impactful research and academic achievements.

Profile

Education

Dr. Hyun-Soo Choi’s educational journey is marked by distinguished achievements and a solid foundation in engineering and computer science. He earned his Bachelor of Science degree in Computer and Communication Engineering from Korea University in February 2013, where he developed a strong base in computing principles. He then pursued advanced studies at Seoul National University, completing his Ph.D. in Electrical and Computer Engineering in February 2020. During his doctoral studies, he was supervised by Prof. Sungroh Yoon and focused on “Imbalanced Data Learning: Advances in Techniques and Applications,” contributing significant advancements to the field of artificial intelligence and machine learning. This academic background not only reflects his expertise in data analysis and bio-medical data learning but also highlights his commitment to advancing knowledge through innovative research.

Professional Experience

Dr. Hyun-Soo Choi has accumulated a diverse range of professional experiences across academia and industry. Currently, he serves as an Assistant Professor in the Department of Computer Science and Engineering at Seoul National University of Science and Technology since February 2023. In this role, he teaches advanced courses in programming, natural language processing, and deep learning. Concurrently, Dr. Choi is the Chief Technical Officer at Ziovision, overseeing technological innovations and developments since October 2021. Previously, he was an Assistant Professor at Kangwon National University from March 2021 to February 2023, where he contributed to various courses on data analysis and machine learning. Dr. Choi also has experience as a researcher at SK Telecom’s T-brain, focusing on advanced artificial intelligence applications from February 2020 to February 2021. His academic background includes a Ph.D. from Seoul National University, where he was mentored by Prof. Sungroh Yoon.

 Research Interest

Dr. Hyun-Soo Choi’s research focuses on advanced artificial intelligence (AI) and machine learning techniques, with a particular emphasis on deep learning, universal learning machines, and causal inference. His work addresses the challenges of bio-medical data learning, aiming to enhance the accuracy and efficiency of data-driven healthcare solutions. Dr. Choi’s research contributions include developing innovative algorithms for imbalanced data learning and applying deep learning methods to various medical fields, such as organ localization and ECG analysis. His recent projects explore novel approaches in facial fracture detection, drug monitoring, and real-time health monitoring, underscoring his commitment to translating AI advancements into practical medical applications. By integrating interdisciplinary methodologies, Dr. Choi strives to push the boundaries of AI research, improving diagnostic and predictive capabilities in healthcare and beyond.

 Research Skills

Dr. Hyun-Soo Choi exhibits a broad and advanced skill set in artificial intelligence and machine learning, particularly in deep learning, causal inference, and bio-medical data analysis. His expertise spans a range of research techniques, including the development of advanced algorithms for imbalanced data learning and generative adversarial networks (GANs). Dr. Choi is proficient in employing deep learning models for diverse applications, such as facial fracture detection, organ localization in wireless capsule endoscopy, and electrocardiography analysis. His ability to integrate machine learning methods with real-world medical data demonstrates a strong aptitude for translating complex theoretical models into practical solutions. Additionally, Dr. Choi’s experience with causal inference methods and universal learning machines highlights his skill in handling intricate data structures and extracting meaningful insights. His comprehensive understanding of these areas is evident through his numerous high-impact publications and contributions to cutting-edge research in his field.

Conclusion

Dr. Hyun-Soo Choi is a strong candidate for the “Research for Best Researcher Award” due to his prolific research output, interdisciplinary expertise, and leadership roles in both academia and industry. However, to further strengthen his application, it would be beneficial to highlight his success in securing research funding, previous awards or recognitions, mentorship activities, and the broader societal impact of his research. With these additions, Dr. Choi would present a well-rounded profile that exemplifies excellence in research and its application to solving real-world challenges.

 

Publications Top Notes

  • A Comprehensive Study on a Deep-Learning-Based Electrocardiography Analysis for Estimating the Apnea-Hypopnea Index
    • Authors: Kim, S., Choi, H.-S., Kim, D., … Kim, Y., Lee, W.H.
    • Year: 2024
  • A Deep Learning–Based Approach for Prediction of Vancomycin Treatment Monitoring: Retrospective Study Among Patients With Critical Illness
    • Authors: Kim, D., Choi, H.-S., Lee, D., … Park, J.-H., Park, J.
    • Year: 2024
    • Citations: 1
  • Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study
    • Authors: Park, S.W., Yeo, N.Y., Kang, S., … Lim, C.-M., Heo, J.
    • Year: 2024
    • Citations: 2
  • Explicit Feature Interaction-Aware Graph Neural Network
    • Authors: Kim, M., Choi, H.-S., Kim, J.
    • Year: 2024
    • Citations: 1
  • In-Advance Prediction of Pressure Ulcers via Deep-Learning-Based Robust Missing Value Imputation on Real-Time Intensive Care Variables
    • Authors: Kim, M., Kim, T.-H., Kim, D., … Han, S.-S., Choi, H.-S.
    • Year: 2024
  • Improving Generalization Performance of Electrocardiogram Classification Models
    • Authors: Han, H., Park, S., Min, S., … Choi, H.-S., Yoon, S.
    • Year: 2023
    • Citations: 3
  • On the Impact of Knowledge Distillation for Model Interpretability
    • Authors: Han, H., Siwon, K., Choi, H.-S., Yoon, S.
    • Year: 2023
    • Citations: 1
  • Multi-View Computed Tomography Network for Osteoporosis Classification
    • Authors: Hwang, D.H., Bak, S.H., Ha, T.-J., … Kim, W.J., Choi, H.-S.
    • Year: 2023
    • Citations: 1
  • PixelSteganalysis: Pixel-Wise Hidden Information Removal With Low Visual Degradation
    • Authors: Jung, D., Bae, H., Choi, H.-S., Yoon, S.
    • Year: 2023
    • Citations: 3
  • ConBERT: A Concatenation of Bidirectional Transformers for Standardization of Operative Reports from Electronic Medical Records
    • Authors: Park, S., Bong, J.-W., Park, I., … Choi, H.-S., Kang, S.
    • Year: 2022
    • Citations: 1