Serkan Yigitkan | Pharmaceutical Science | Best Researcher Award

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Assist. Prof. Dr. Serkan Yigitkan | Pharmaceutical Science | Best Researcher Award

Dicle University, Turkey

Dr. Serkan Yiğitkan is a distinguished pharmacognosist affiliated with Dicle University’s Institute of Health Sciences in Diyarbakır, Turkey. His academic journey is marked by a profound dedication to the study of medicinal plants and their applications in healthcare. With a robust portfolio of 18 publications and a significant number of citations, Dr. Yiğitkan has established himself as a leading figure in his field. His research primarily focuses on the pharmacological properties of natural products, aiming to bridge the gap between traditional herbal remedies and modern medicine. Through his work, he seeks to validate and harness the therapeutic potentials of phytochemicals, contributing to the development of novel treatments for various ailments.

Professional Profile

Education

Dr. Yiğitkan completed his doctoral studies in pharmacognosy at Dicle University, where he delved into the chemical and biological properties of medicinal plants. His education provided a solid foundation in understanding the complexities of plant-based compounds and their interactions within biological systems. This academic background has been instrumental in shaping his research trajectory, allowing him to explore the vast potential of phytochemicals in therapeutic applications. His commitment to continuous learning and research is evident in his contributions to the scientific community, particularly in the realm of natural product pharmacology.

Professional Experience

Throughout his career, Dr. Yiğitkan has been actively involved in various research projects and academic collaborations. His role at Dicle University encompasses both teaching and research, where he mentors students and leads studies on the pharmacological effects of medicinal plants. His professional journey is characterized by a dedication to advancing the understanding of natural products and their potential therapeutic benefits. Through his involvement in numerous studies and publications, he has contributed significantly to the field of pharmacognosy, particularly in exploring the antimicrobial and antioxidant properties of plant extracts.

Research Interests

Dr. Yiğitkan’s research interests are centered around the pharmacological evaluation of medicinal plants, with a particular focus on their antimicrobial and antioxidant properties. He is keenly interested in identifying bioactive compounds that can serve as potential therapeutic agents. His work often involves the extraction and characterization of phytochemicals, aiming to discover novel compounds with significant health benefits. By investigating the traditional uses of plants and validating their efficacy through scientific methods, he contributes to the integration of herbal medicine into modern therapeutic practices.

Research Skills

Dr. Yiğitkan possesses a diverse set of research skills, including expertise in chromatographic techniques, bioassay-guided fractionation, and the evaluation of biological activities of natural products. His proficiency in these methodologies enables him to isolate and identify active compounds from complex plant matrices effectively. Additionally, his skills in designing and conducting experiments related to antimicrobial and antioxidant assays have been pivotal in advancing his research objectives. His methodological approach ensures the reliability and reproducibility of his findings, contributing to the broader scientific understanding of medicinal plants.

Awards and Honors

While specific awards and honors are not detailed in the available information, Dr. Yiğitkan’s contributions to the field of pharmacognosy are evident through his extensive publication record and the impact of his research. His work has garnered attention within the scientific community, reflecting his commitment to advancing knowledge in natural product research. The recognition of his studies by peers and the inclusion of his research in reputable journals underscore his standing as a respected scientist in his field.

Conclusion

Dr. Serkan Yiğitkan’s dedication to exploring the medicinal properties of plants has significantly enriched the field of pharmacognosy. His research endeavors have not only advanced scientific understanding but also paved the way for the development of novel therapeutic agents derived from natural sources. Through his meticulous studies and commitment to integrating traditional knowledge with modern science, Dr. Yiğitkan exemplifies the vital role of researchers in bridging cultural heritage and contemporary medicine. His ongoing efforts continue to inspire and contribute to the global appreciation of plant-based therapeutics.

Publications Top Notes

  1. Title: Assessment of the Anti-Acne Properties of Some Medicinal Plants and Development of an Herbal Anti-Acne Formulation
    Authors: F. Sezer Senol Deniz, Ozlem Oyardı, Cagla Bozkurt Guzel, Tahir Emre Yalcın, Serkan Yiğitkan, Yuksel Kan, Nurver Ulger Toprak, Ilkay Erdogan Orhan
    Year: 2025

  2. Title: LC-MS/MS Analysis and Biological Activities of Different Parts of Ziziphora capitate L.
    Authors: Serkan Yiğitkan, Mehmet Çavuşoğlu, Mehmet Veysi Çağlayan, İsmail Yener, Mehmet Fırat, Eda Çavuş Kaya, Mustafa Abdullah Yılmaz, Abdulselam Ertaş
    Year: 2024

  3. Title: Ziziphora clinopodioides Lam. Türünün Kültür İle Doğal Ortamlarda Yetişen Örneklerinin Kimyasal ve Biyolojik Yönden Detaylı İncelenmesi
    Authors: Mehmet Çavuşoğlu, Serkan Yiğitkan, İsmail Yener, Mehmet Veysi Çağlayan, Barış Reşitoğlu, Mehmet Akdeniz, Eda Çavuş Kaya, Fethullah Tekin, Mustafa Abdullah Yılmaz, Abdulselam Ertaş
    Year: 2024

  4. Title: A Comprehensive Study on Chemical and Biological Investigation of Thymus Brachychilus Jalas: A Rich Source of Ursolic and Oleanolic Acids
    Authors: Mehmet Akdeniz, Serkan Yiğitkan, Mustafa Abdullah Yılmaz, İsmail Yener, Elif Varhan Oral, Mehmet Fırat, Ilkay Erdogan Orhan, Ufuk Kolak, Abdulselam Ertaş
    Year: 2024

  5. Title: Essential Oil Contents and Biological Activities of Thymus Canoviridis Jalas and Thymus Sipyleus Boiss.
    Authors: Serkan Yiğitkan, Mehmet Fırat
    Year: 2024

  6. Title: An Investigation of the ACE Inhibitory Activity, Antioxidant Capacity, and Phytochemical Constituents of Polar and Non-Polar Extracts of Ziziphus Jujuba Fruit: Statistical Screening of the Main Components Responsible for Bioactivity
    Authors: Bahar Fındık, Hilal Yıldız, Esma Birişçi, Serkan Yiğitkan, Pelin Köseoğlu Yılmaz, Abdulselam Ertaş
    Year: 2024

  7. Title: Comprehensive Study of Chemical Composition and Biological Activity of Thymus pubescens Boiss. et Kotschy ex Čelak.
    Authors: Serkan Yiğitkan, Mehmet Akdeniz, İsmail Yener, Zeki Seker, Mustafa Abdullah Yılmaz, Mehmet Fırat, Deniz Evrim Kavak, Pelin Yılmaz Köseoğlu, Abdulselam Ertaş, Ufuk Kolak
    Year: 2022

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