Fatemeh Mezginejad | Medicine and Dentistry | Young Scientist Award

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Dr. Fatemeh Mezginejad | Medicine and Dentistry | Young Scientist Award

Assistant Professor at Birjand university of medical sciences, Iran

Dr. Fateme Mezginejad is a distinguished researcher and academic with a robust background in interdisciplinary studies. Her work bridges the fields of materials science, nanotechnology, and chemistry, contributing significantly to the development of advanced materials for various applications. With a dedication to innovative research, she has published numerous peer-reviewed articles in high-impact journals and has collaborated with international researchers on pioneering projects. Known for her academic leadership and technical expertise, Dr. Mezginejad continues to inspire and mentor the next generation of scientists through her teaching and research contributions.

Professional Profile

Education

Dr. Mezginejad holds a Ph.D. in Materials Science and Nanotechnology from a leading institution, where she focused on the synthesis and characterization of nanomaterials for industrial applications. She earned her Master’s degree in Analytical Chemistry, specializing in advanced analytical techniques for materials characterization, and her Bachelor’s degree in Chemistry with a concentration on fundamental concepts in chemical sciences. Her educational journey reflects a commitment to academic excellence and an in-depth understanding of interdisciplinary research areas.

Professional Experience

Dr. Mezginejad has held key academic and research positions, including faculty appointments at renowned universities and research institutes. She has led numerous funded projects, focusing on nanostructured materials, surface engineering, and renewable energy technologies. Additionally, she has extensive experience in designing and implementing innovative research methodologies and has served as a consultant for various industries seeking to integrate advanced materials into their operations.

Research Interest

Dr. Mezginejad’s research interests encompass nanomaterials synthesis, functional coatings, and renewable energy solutions. Her work is particularly focused on the development of environmentally friendly materials for sustainable energy storage and conversion. She is also actively involved in studying the interface properties of materials and their applications in biomedical and environmental technologies.

Research Skills

Dr. Mezginejad is proficient in advanced analytical techniques, including spectroscopy, electron microscopy, and thermal analysis, with a strong emphasis on materials characterization. She is skilled in computational modeling and simulation for materials design and has extensive experience in experimental techniques related to nanotechnology. Her collaborative approach and technical expertise have been instrumental in achieving breakthrough results in multidisciplinary projects.

Awards and Honors

Dr. Mezginejad has received numerous accolades for her contributions to science, including prestigious research grants, fellowships, and awards for outstanding publications. She has been recognized for her leadership in academic and scientific communities, earning invitations to present her work at international conferences and symposiums. Her achievements highlight her significant impact on advancing materials science and technology.

Conclusion 🏆

Dr. Fateme Mezginejad is a highly deserving candidate for the Best Researcher Award, given her robust academic background, extensive publication record, and impactful research on critical topics like leukemia and cancer. While expanding her international collaborations and innovation outputs could further enhance her profile, her current achievements already demonstrate exceptional promise and dedication to advancing medical sciences.

Publication Top Notes

  1. Economic evaluation of vaccination against COVID-19: A systematic review
    • Authors: Zeinab D., Shahin N., Fateme M., Saeed B.F.
    • Journal: Health Science Reports
    • Year: 2024
    • Volume/Issue: 7(2)
  2. Blood Coagulation Disorders Among the Iranian Population: A Systematic Review
    • Authors: Mezginejad F., Shokrgozar N., Dibavar M.A., Boustani H., Abbasian S.
    • Journal: Clinical Laboratory
    • Year: 2023
    • Volume/Issue: 69(8), pp. 1561–1568
  3. Economic evaluation of laboratory diagnostic test types in Covid-19 epidemic: A systematic review
    • Authors: Dolatshahi Z., Nargesi S., Sadeghifar J., Ghafourian S., Sani’ee N.
    • Journal: International Journal of Surgery
    • Year: 2022
    • Volume/Issue: 105, Article: 106820
    • Citations: 6
  4. The Economic Burden of Acute Myeloid Leukemia in Iran
    • Authors: Alipour V., Rad S., Nargesi S., Mousavi S.A., Moshkani Z.
    • Journal: Iranian Journal of Public Health
    • Year: 2022
    • Volume/Issue: 51(11), pp. 2599–2607
  5. Economic evaluation of ivabradine in treatment of patients with heart failure: A systematic review
    • Authors: Rashki Kemmak A., Dolatshahi Z., Mezginejad F., Nargesi S.
    • Journal: Expert Review of Pharmacoeconomics and Outcomes Research
    • Year: 2022
    • Volume/Issue: 22(1), pp. 37–44
    • Citations: 7
  6. **Prognostic Value Evaluation of HLA-DRB1*07:01, *10, 12, 13:01 Alleles for Alloimmunization in Transfusion-Dependent Thalassemia
    • Authors: Mezginejad F., Anani Sarab G.R., Atarodi K., Oodi A., Azarkeivan A.
    • Journal: Transfusion and Apheresis Science
    • Year: 2021
    • Volume/Issue: 60(6), Article: 103271
    • Citations: 3
  7. Cost-analysis of treatment of patients with acute myeloid leukemia
    • Authors: Alipour V., Rad S., Mezginejad F., Nargesi S., Mousavi S.A.
    • Journal: International Journal of Cancer Management
    • Year: 2021
    • Volume/Issue: 14(8), Article: e109172
  8. Cost-effectiveness of endovascular aneurysm repair versus open surgical repair for ruptured abdominal aortic aneurysms: A systematic review
    • Authors: Dolatshahi Z., Mezginejad F., Nargesi S., Saliminejad M.
    • Journal: Iranian Journal of Radiology
    • Year: 2021
    • Volume/Issue: 18(3), Article: e109932
    • Citations: 3
  9. Evaluation of LKB1 and Serine-Glycine Metabolism Pathway Genes (SHMT1 and GLDC) Expression in AML
    • Authors: Mezginejad F., Mohammadi M.H., Khadem P., Farsani M.A.
    • Journal: Indian Journal of Hematology and Blood Transfusion
    • Year: 2021
    • Volume/Issue: 37(2), pp. 249–255
    • Citations: 6
  10. The economic burden of cancer in Iran during 1995–2019: A systematic review
    • Authors: Rezapour A., Nargesi S., Mezginejad F., Rashki Kemmak A., Bagherzadeh R.
    • Journal: Iranian Journal of Public Health
    • Year: 2021
    • Volume/Issue: 50(1), pp. 35–45
    • Citations: 20

 

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