Yayang Duan | Deep learning | Best Researcher Award

Dr. Yayang Duan | Deep learning | Best Researcher Award

Dr. Yayang Duan, Affiliated First Hospital of Anhui University, China.

Dr. Yayang Duan , an accomplished physician and medical researcher, specializes in ultrasound diagnostics and AI applications in liver disease imaging. With a Doctorate in Imaging and Nuclear Medicine from Anhui Medical University, he has published 8+ SCI papers πŸ“„ and reviewed for top journals like European Radiology πŸ”. A recipient of the 2024 Wiley China High Contribution Author Award πŸ†, he currently serves at the First Affiliated Hospital of Anhui Medical University, combining clinical excellence with impactful research.

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πŸŽ“ Early Academic Pursuits

Dr. Yayang Duan embarked on an impressive academic journey rooted in medical imaging. She completed her Bachelor’s degree in Medical Imaging from Bengbu Medical College (2012–2017), followed by a Master’s in Imaging and Nuclear Medicine at Dalian Medical University (2017–2020). Her academic trajectory culminated in a Professional Doctorate in Imaging and Nuclear Medicine from Anhui Medical University (2020–2023), reflecting her unwavering commitment to advanced medical education. πŸŽ“πŸ“š

πŸ’Ό Professional Endeavors

Since July 2023, Dr. Duan has served as a Physician in the Department of Ultrasound Medicine at the First Affiliated Hospital of Anhui Medical University. Her clinical practice centers on medical ultrasound diagnosis across various body systems. Her solid educational background seamlessly integrates with her hands-on clinical skills, enabling her to contribute significantly to patient care and medical research. πŸ₯🩺

πŸ”¬ Contributions and Research Focus On Deep learning

Dr. Duan’s research primarily focuses on liver diseases and the integration of artificial intelligence in clinical diagnostics. She has authored eight SCI-indexed papers as the first or corresponding author, along with one paper in a Chinese core journal, and contributed to ten additional SCI publications. Her expertise bridges the gap between diagnostic imaging and cutting-edge AI applications, driving forward the capabilities of non-invasive diagnostics. πŸ§¬πŸ“Š

🌍 Impact and Influence

With more than 15 expert peer reviews for prestigious journals such as European Radiology, European Journal of Nuclear Medicine and Molecular Imaging, and iScience, Dr. Duan plays an integral role in shaping the scientific discourse in medical imaging. Her influence extends beyond her own publications, reflecting a trusted voice within the global academic community. πŸŒπŸ“

🧠 Research Skills

Dr. Duan is highly proficient in medical ultrasound diagnostics, particularly in abdominal and soft tissue applications. She combines this clinical acumen with technical research expertise in AI-driven imaging analysis, liver pathology, and nuclear medicine. Her skills span both laboratory-based research and real-time patient diagnostics. πŸ–₯οΈπŸ”

πŸ… Awards and Honors

In recognition of her scholarly impact, Dr. Duan was awarded the 2024 Q1 Wiley China High Contribution Author Award πŸ†β€”a testament to her dedication, high-quality publications, and thought leadership in medical research.

πŸ›οΈ Legacy and Future Contributions

With a promising career ahead, Dr. Duan is poised to make lasting contributions to ultrasound medicine, AI-integrated diagnostics, and clinical education. As a rising star in medical imaging, she embodies a unique blend of academic excellence, clinical dedication, and innovation that will shape the future of diagnostic medicine. πŸš€πŸ“Œ

Publications Top Notes

  • πŸ“„ Title: Performance of a generative adversarial network using ultrasound images to stage liver fibrosis and predict cirrhosis based on a deep-learning radiomics nomogram
    πŸ“˜ Journal: Clinical Radiology
    πŸ“Š Citations: 16
    πŸ“… Year: 2022

  • πŸ“„ Title: Clinical value of hemodynamic changes in diagnosis of hepatic encephalopathy after transjugular intrahepatic portosystemic shunt
    πŸ“˜ Journal: Scandinavian Journal of Gastroenterology
    πŸ“Š Citations: 14
    πŸ“… Year: 2022

  • πŸ“„ Title: Development of a machine learning-based model to predict prognosis of alpha-fetoprotein-positive hepatocellular carcinoma
    πŸ“˜ Journal: Journal of Translational Medicine
    πŸ“Š Citations: 11
    πŸ“… Year: 2024

  • πŸ“„ Title: Radiomics analysis of breast lesions in combination with coronal plane of ABVS and strain elastography
    πŸ“˜ Journal: Breast Cancer: Targets and Therapy
    πŸ“Š Citations: 7
    πŸ“… Year: 2023

  • πŸ“„ Title: Performance of two-dimensional shear wave elastography for detecting advanced liver fibrosis and cirrhosis in patients with biliary atresia: a systematic review and meta-analysis
    πŸ“˜ Journal: Pediatric Radiology
    πŸ“Š Citations: 6
    πŸ“… Year: 2023

  • πŸ“„ Title: A sonogram radiomics model for differentiating granulomatous lobular mastitis from invasive breast cancer: A multicenter study
    πŸ“˜ Journal: La Radiologia Medica
    πŸ“Š Citations: 6
    πŸ“… Year: 2023

  • πŸ“„ Title: An overview of ultrasound-derived radiomics and deep learning in liver
    πŸ“˜ Journal: Medical Ultrasonography
    πŸ“Š Citations: 5
    πŸ“… Year: 2023

  • πŸ“„ Title: Multimodal radiomics and nomogram‐based prediction of axillary lymph node metastasis in breast cancer: An analysis considering optimal peritumoral region
    πŸ“˜ Journal: Journal of Clinical Ultrasound
    πŸ“Š Citations: 5
    πŸ“… Year: 2023

  • πŸ“„ Title: Diagnostic accuracy of contrast-enhanced ultrasound for detecting clinically significant portal hypertension and severe portal hypertension in chronic liver disease: a meta-analysis
    πŸ“˜ Journal: Expert Review of Gastroenterology & Hepatology
    πŸ“Š Citations: 3
    πŸ“… Year: 2023

  • πŸ“„ Title: Ultrasound-based deep learning radiomics nomogram for the assessment of lymphovascular invasion in invasive breast cancer: a multicenter study
    πŸ“˜ Journal: Academic Radiology
    πŸ“Š Citations: 2
    πŸ“… Year: 2024

  • πŸ“„ Title: Enhancing malignancy prediction in thyroid nodules: A multimodal ultrasound radiomics approach in TI‐RADS category 4 lesions
    πŸ“˜ Journal: Journal of Clinical Ultrasound
    πŸ“Š Citations: 2
    πŸ“… Year: 2024

 

 

Ghulam Mohi-ud-din | Computer Science | Excellence in Innovation Award

Prof. Ghulam Mohi-ud-din | Computer Science | Excellence in Innovation Award

Prof. Ghulam Mohi-ud-din, Nanchang University, China.

Prof. Ghulam Mohi-ud-din is an experienced Product Coordinator 🧠 with 7+ years of expertise in software engineering, research, and IT strategy πŸ’‘. He excels in risk mitigation, quality assurance, and infrastructure development πŸ› οΈ. Currently pursuing a PhD in Software Engineering, Ghulam has also worked with top firms like IBM and Oracle 🌐. A certified PMP, CCIE, and OCP πŸŽ“, he is passionate about driving innovation, leading cross-functional teams, and delivering impactful tech solutions πŸš€.

πŸŽ“ Early Academic Pursuits

Ghulam Mohi-ud-din began his academic journey with a Bachelor’s degree in Software Engineering from the University of Engineering and Technology, Lahore, graduating with an impressive GPA of 3.6. He further honed his technical skills through a Master of Science in Computer Systems Networking and Telecommunications at the University of Florida, maintaining a strong GPA of 3.85. Currently pursuing a PhD in Software Engineering at Northwestern Polytechnical University, Xi’an, Ghulam’s commitment to lifelong learning sets a solid foundation for his professional achievements. πŸ“˜πŸ’»

πŸ’Ό Professional Endeavors

With over 17 years of extensive experience, Ghulam has held pivotal roles across multiple continents. His current position as a Product Coordinator at ResearchEX Ltd, London, involves project leadership, strategic implementation, and cross-functional team management. Past roles include Project Consultant at IBM, Visiting Faculty at LUMS, Assistant DBA at Oracle, and Network Administrator at OGDCL, each enriching his skill set in IT infrastructure, data management, teaching, and network security. πŸŒπŸ“Š

πŸ”¬ Contributions and Research Focus On Computer Science Β 

Ghulam’s research spans across software engineering, machine learning, and infrastructure development. His time as a faculty member at LUMS saw him guiding students in computer science research, securing funding, and authoring significant research publications. His doctoral research aligns with modern software methodologies, ensuring real-world applicability and innovation. πŸ§ πŸ“ˆ

🌍 Impact and Influence

From enhancing cloud infrastructure at Oracle to leading agile methodologies in the UK tech sector, Ghulam’s influence extends to policy development, training programs for thousands of employees, and optimizing technical workflows that reduce costs and increase operational performance. His leadership style promotes team unity, performance recognition, and long-term organizational success. πŸ’‘πŸ€

πŸ† Awards and Honors

Ghulam holds a rich collection of certifications from globally recognized institutions including Cisco (CCNA, CCNP, CCIE), Oracle (OCA, OCP, OCE), Red Hat (RHCE, RHCT), and Project Management Professional (PMP). These validate his authority in system architecture, project management, and enterprise-level IT strategy. πŸŽ–οΈπŸ“œ

πŸš€ Legacy and Future Contributions

Poised at the intersection of academia and industry, Ghulam’s future goals involve leading transformational IT initiatives, mentoring the next generation of technologists, and contributing groundbreaking research in AI and software systems. His vision includes bridging academic theory with business innovation, leaving a legacy of empowered teams and streamlined technology infrastructures. πŸŒπŸš€

πŸ“šPublications Top Notes

  • Click-level supervision for online action detection extended from SCOAD

    • Journal: Future Generation Computer Systems

    • Year: 2025

  • Deciphering TON-IoT threats: Meta-heuristic and deep learning for attack classification

    • Journal: Expert Systems with Applications

    • Year: 2025

  • A wireless sensor network for coal mine safety powered by modified localization algorithm

    • Authors: H.Z. ul Hassan, A. Wang, G. Mohi-ud-din

    • Journal: Heliyon

    • Year: 2025

  • ML-Driven Audit Risk Assessment with Differential Privacy

    • Authors: Dr. Ghulam Mohi-ud-din

    • Conference: 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI)

    • Year: 2024

  • Unmanned aerial vehicle intrusion detection: Deep-meta-heuristic system

    • Authors: Shangting Miao, Quan Pan, Dongxiao Zheng, Ghulam Mohi-ud-din

    • Journal: Vehicular Communications

    • Year: 20

  • Real-time portrait image retouching extended from DualBLN

    • Journal: Expert Systems with Applications

    • Year: 2024

  • Intrusion Detection Using Hybrid Enhanced CSA-PSO and Multivariate WLS Random-Forest Technique

    • Journal: IEEE Transactions on Network and Service Management
    • Year: 2023​

  • Intrusion Detection using hybridized Meta-heuristic techniques with Weighted XGBoost Classifier

    • Authors: Ghulam Mohi-ud-din, Zhijun Lin, Jiangbin Zheng, Junsheng Wu, Weigang Li, Yifan Fang, Sifei Wang, Jiajun Chen, Xinyu Zeng

    • Journal: Expert Systems with Applications

    • Year: 2023

  • Intrusion detection in wireless sensor network using enhanced empirical based component analysis

    • Authors: Liu Zhiqiang, Ghulam Mohi-ud-din, Jiangbin Zheng, Sifei Wang, Asim Muhammad

    • Journal: Future Generation Computer Systems

    • Year: 2022

Israt Jahan Payel | Artificial Intelligence | Best Researcher Award

Ms. Israt Jahan Payel | Β Artificial Intelligence | Best Researcher Award

Ms. Israt Jahan Payel , Daffodil International University, Bangladesh.

Ms. Israt Jahan Payel is a dedicated researcher specializing in Artificial Intelligence, machine learning, and healthcare applications. She has developed groundbreaking solutions such as the “Grape Guard” mobile app for grape leaf disease detection, achieving remarkable precision and accuracy. Her innovative work includes a novel Graph Neural Network approach for breast cancer diagnosis and the integration of federated learning with explainable AI for privacy-preserving healthcare. With multiple publications in high-impact journals, including the Journal of Cancer Research and Clinical Oncology, and significant contributions to medical image classification, Payel exemplifies excellence in advancing AI-driven healthcare innovations

Professional Profile:

Google Scholar

Suitability for Best Researcher AwardΒ 

Ms. Israt Jahan Payel is a highly accomplished researcher specializing in Artificial Intelligence, machine learning, and healthcare applications. With a proven track record in groundbreaking research, she has developed innovative solutions such as the YOLOv8-based mobile app “Grape Guard” for grape leaf disease detection, achieving remarkable precision and recall rates. Her work has been published in high-impact journals like the Journal of Cancer Research and Clinical Oncology, and she has proposed novel approaches for breast cancer diagnosis using Graph Neural Networks and federated learning for privacy-preserving healthcare.

Israt’s extensive experience as a Research Associate at both the Health Information Research Lab (HIRL) and 4IR Research Cell at Daffodil International University demonstrates her commitment to advancing research in healthcare and AI. Her research and publication list highlight her deep expertise and innovative approach, making her an exceptional candidate for the Best Researcher Award.

πŸŽ“Β Education Background:

Ms. Israt Jahan Payel has an exemplary academic background in Computer Science and Engineering. She is currently pursuing her Master’s degree at Daffodil International University (DIU), Dhaka, Bangladesh, with a stellar CGPA of 4.00. She completed her Bachelor’s degree in the same discipline from DIU in 2023, achieving an impressive CGPA of 3.87. Payel also excelled in her earlier education, securing a CGPA of 4.42 in her Higher Secondary Certificate (HSC) from Savar Model College, Dhaka, and a perfect CGPA of 5.00 in her Secondary School Certificate (SSC) from ACED School, Dhaka. Her academic journey reflects dedication and excellence.

πŸ’Ό ProfessionalΒ Experience:

Ms. Israt Jahan Payel has been actively engaged in research as a Research Associate at the Health Information Research Lab (HIRL) and the 4IR Research Cell at Daffodil International University since 2022. Her work focuses on artificial intelligence, machine learning, and healthcare applications. She has led impactful projects, including developing mobile applications and machine learning models for disease detection and diagnosis. Payel’s expertise spans medical image classification, federated learning, and graph neural networks. Her hands-on experience in research and innovation highlights her ability to address real-world challenges and contribute significantly to advancements in AI and healthcare technologies.

🌍Research Contributions On Artificial Intelligence

Ms. Israt Jahan Payel has made significant contributions to artificial intelligence and healthcare research. Her innovative projects include developing the “Grape Guard” app for grape leaf disease detection, achieving exceptional precision and accuracy. She proposed a Graph Neural Network approach for breast cancer diagnosis and integrated federated learning with explainable AI for privacy-preserving healthcare solutions. Her work on multi-modality medical image classification combines X-ray, MRI, and CT modalities for advanced disease detection. With publications in high-impact journals and ongoing research in deep learning, medical imaging, and data analytics, Payel’s contributions address critical healthcare challenges with real-world impact.

πŸ₯‡Award and Recognition

Ms. Israt Jahan Payel has been widely recognized for her outstanding contributions to artificial intelligence and healthcare applications. Her innovative project, “Grape Guard,” earned acclaim for achieving exceptional precision in grape leaf disease detection. She has published in high-impact journals such as the Journal of Cancer Research and Clinical Oncology, reflecting her excellence in academic research. Her work on Graph Neural Networks for breast cancer diagnosis and federated learning in healthcare has set benchmarks in the field. A consistent achiever, Payel has been honored for her research excellence and dedication to advancing AI-driven solutions for real-world problems.

πŸ“šPublication Top Notes

Graph Neural Network-Based Breast Cancer Diagnosis Using Ultrasound Images with Optimized Graph Construction Integrating the Medically Significant Features
πŸ“– Journal of Cancer Research and Clinical Oncology
πŸ“… 2023 | πŸ‘₯ Cited by: 3

DVS: Blood Cancer Detection Using Novel CNN-Based Ensemble Approach
πŸ“„ arXiv preprint arXiv:2410.05272
πŸ“… 2024 | πŸ‘₯ Cited by: 1

Grape Guard: A YOLO-Based Mobile Application for Detecting Grape Leaf Diseases
πŸ“œ Journal of Electronic Science and Technology
πŸ“… 2025 | ✨ New Publication

A Low Complexity Efficient Deep Learning Model for Automated Retinal Disease Diagnosis
πŸ“š Journal of Healthcare Informatics Research
πŸ“… 2024