Yinfeng Yang | Artificial Intelligence |Young Scientist Award

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Assoc. Prof. Dr. Yinfeng Yang | Artificial Intelligence | Young Scientist Award

Anhui University of Chinese Medicine | China

Assoc. Prof. Dr. Yinfeng Yang is an Associate Professor and emerging research leader at the intersection of artificial intelligence and traditional Chinese medicine, with a strong focus on biomedical big data analytics and AI-driven drug discovery. With a publication record of 45 documents and a citation impact exceeding 5,738 citations from 5,599 citing documents, alongside an h-index of 18, her research demonstrates significant international influence. Her work integrates bioinformatics, machine learning, molecular simulation, and systems biology to uncover key biomarkers, elucidate disease mechanisms, and accelerate the development of innovative therapeutic strategies. She has made notable contributions to multi-omics data mining, virtual screening, quantitative structure–activity relationship modeling, and mechanistic analysis of natural products and traditional prescriptions, particularly in oncology, immunology, cardiovascular disorders, and neurological diseases. Her research advances include AI-powered ADMET prediction, graph neural network–based drug-target discovery, and multiscale modeling of herbal medicine mechanisms. She has authored more than sixty publications, including first- and corresponding-author papers in high-impact journals such as Journal of Advanced Research, Phytomedicine, Drug Discovery Today, International Journal of Surgery, and ACS Omega, contributing influential and highly cited work. In addition to her scientific output, she has edited scholarly works, holds an authorized patent, and has received provincial recognition for scientific achievements. She also serves on editorial boards and contributes extensively as a reviewer for numerous international journals across pharmacology, bioinformatics, natural product research, and integrative medicine. Her expertise spans molecular dynamics, docking, high-throughput virtual screening, AI algorithms, multi-omics integration, and experimental pharmacology, positioning her at the forefront of intelligent medicine and translational research in traditional Chinese medicine.

Featured Publications

  • Fan, N. N., Chen, J., Wang, J. H., Chen, Z. S., & Yang, Y. F. (2025). Bridging data and drug development: Machine learning approaches for next-generation ADMET prediction. Drug Discovery Today, Article 104487.

  • Han, Z. J., Liu, Q. W., Yang, J. H., Wang, X. Y., Song, W. C., Wang, J. H., & Yang, Y. F. (2025). Exploration of the mechanism of Ginkgo biloba leaves targeted angiogenesis against gastric cancer. ACS Omega, 10, 40460–40476.

  • Yang, P. Z., Wang, X. Y., Yang, J. H., Yan, B. B., Sheng, H. Y., Li, Y., Yang, Y. F., & Wang, J. H. (2025). AI-driven multiscale study on the mechanism of Polygonati Rhizoma in regulating immune function in STAD. ACS Omega, 10(19), 19770–19796.

  • Li, H., Fu, S. F., Shen, P., Zhang, X., Yang, Y. F., & Guo, J. C. (2025). Mitochondrial pathways in rheumatoid arthritis: Therapeutic roles of traditional Chinese medicine and natural products. Phytomedicine, Article 157106.

  • Zhang, H. R., Xu, Q., Kan, H. X., Yang, Y. F., & Cai, Y. Q. (2025). Exploration of the clinicopathological and prognostic significance of BRCA1 in gastric cancer. Discover Oncology, 16(1), 381.

 

Wei Huang | Computer Science | Best Researcher Award

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Dr. Wei Huang | Computer Science | Best Researcher Award

Jingdezhen University | China

Dr. Wei Huang is a distinguished researcher and academician specializing in the integration of computer science and artificial intelligence in civil aviation. Currently serving at the School of Information Engineering, Jingdezhen University, Dr. Huang has made significant contributions to advancing aviation technology, with a strong focus on aircraft landing systems, runway marking recognition, and low-altitude economic applications. With extensive experience in both academia and industry, Dr. Huang has collaborated with aviation companies and government institutions, leading groundbreaking projects aimed at enhancing aviation safety and operational efficiency. His research combines deep learning, computer vision, and cutting-edge AI models to address real-world aviation challenges. As an expert evaluator for several scientific and technology associations, Dr. Huang actively supports innovation and knowledge exchange in the aviation sector. With numerous publications in high-impact journals and patents to his credit, he stands as a thought leader driving forward the future of intelligent aviation systems and technologies.

Profile

 Orcid

Education 

Dr. Wei Huang pursued his academic training with a focus on advanced computing and aviation systems, culminating in a PhD in Computer Science from the Russian Academy of Sciences, one of the most prestigious research institutions known for producing leading scientists in computational and engineering disciplines. Alongside his doctoral studies, Dr. Huang earned an Air Traffic Control License from the Civil Aviation Administration of China, a credential that demonstrates his expertise in aviation operations and his commitment to integrating theoretical knowledge with practical application. His educational journey reflects a multidisciplinary foundation, blending advanced computer science principles, artificial intelligence algorithms, and aviation system design. This unique academic background has enabled him to bridge the gap between cutting-edge computing innovations and their direct application in civil aviation. Dr. Huang’s education has provided him with a strong platform to pioneer technologies in intelligent aviation, low-altitude airspace research, and safety-driven innovations through data-driven approaches.

Experience 

Dr. Wei Huang’s professional journey reflects a distinguished career in research, teaching, and industry collaborations. At Jingdezhen University’s School of Information Engineering, he has been instrumental in shaping research initiatives that focus on artificial intelligence applications in aviation safety and low-altitude economic development. His work bridges academic theory and industrial needs, demonstrated through his collaboration with Jiangxi Helicopter Co., Ltd. on helicopter technology advancements and his leadership in AI-powered aviation marking recognition systems. As an expert reviewer and project evaluator for the Jiangxi Association for Science and Technology and other leading organizations, Dr. Huang contributes to national and regional scientific innovation assessments. His experience spans the supervision of projects funded by governmental bodies, the publication of high-impact research papers, and the development of patents that advance civil aviation. He has also built strong academic-industry partnerships, positioning himself as a leading expert at the intersection of computing and aviation engineering, innovation, and technology.

Awards and Honors

Dr. Wei Huang has received recognition for his pioneering work in computer science applications for civil aviation. His innovations, including AI-powered runway marking recognition systems, have contributed to improved aviation safety and operational efficiency, earning him respect in both academic and industrial spheres. He serves as an expert reviewer for academic journals, including the Journal of Jingdezhen University, showcasing his expertise in evaluating high-level research. Additionally, his role as a project evaluator for the Jiangxi Association for Science and Technology and the Low Altitude Leading Alliance highlights his contributions to guiding strategic research initiatives and fostering technology development. His patents and publications have further established his influence in advancing aviation-focused AI technologies. Through his efforts, Dr. Huang has become a valued leader in shaping aviation innovation policies, inspiring researchers, and contributing to China’s growing expertise in AI-driven aerospace technology. His achievements reflect excellence in interdisciplinary research and scientific innovation.

Research Focus 

Dr. Wei Huang’s research focuses on integrating computer science and artificial intelligence into aviation systems, with particular emphasis on improving low-altitude flight safety and efficiency. He specializes in computer vision, deep learning, and intelligent detection algorithms applied to aircraft landing systems. One of his major contributions is the development of an enhanced YOLOv5s-based detection model that improves accuracy in runway marking recognition, demonstrating measurable advancements in precision and reliability. His research combines techniques such as convolutional neural networks, attention mechanisms, deformable convolution, and data augmentation to create innovative solutions for real-world aviation challenges. Beyond algorithm development, Dr. Huang’s work extends to helicopter system optimization, aviation operations, and low-altitude economic growth strategies, making his contributions both technically robust and highly practical. His projects, patents, and publications underscore his leadership in AI applications for civil aviation. By bridging academia and industry, he is shaping future trends in intelligent aviation systems and aeronautical safety engineering.

Publication

Title: Research on Optimized YOLOv5s Algorithm for Detecting Aircraft Landing Runway Markings
Year: 2025

Conclusion

Dr. Huang is an outstanding researcher whose work reflects excellence, originality, and dedication to innovation in civil aviation technology. His ability to bridge advanced research with practical applications positions him as a strong candidate for the Best Researcher Award. With continued efforts to expand global recognition and collaborative impact, he is poised to make even greater contributions to the scientific community.

Mohsen Ghorbian | Data Sience | Best Researcher Award

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Dr. Mohsen Ghorbian | Data Sience | Best Researcher Award

Data Sience, Islamic Azad University of Qom Iran

Mohsen Ghorbian  is a forward-thinking computer scientist and researcher recognized for his impactful work in AI, machine learning, IoT, and blockchain within the biomedical and healthcare domain  With a robust portfolio of peer-reviewed publications  from 2020 to 2025, he has contributed to enhancing clinical decision-making and real-time health monitoring systems ⚙️. His interdisciplinary collaborations and leadership in intelligent systems development showcase his commitment to addressing real-world problems through innovative computational methods . He is widely cited and active in the global research community, holding both a Web of Science ResearcherID and ORCiD . Mohsen’s contributions bridge academic research and applied technology , making him a valuable thought leader in modern healthcare computing and serverless architectures.

Profile

Scholar

🎓 Education 

Mohsen Ghorbian has pursued a solid academic background in computer science and engineering , focusing on AI-driven health systems and intelligent computing . He holds advanced degrees, likely including a Ph.D.  with specialization in biomedical informatics, cloud computing, and IoT systems, although precise university details are not publicly listed . His educational journey is evident from his deep engagement in scholarly activities, high-level publication venues , and his active role in bridging computer science with clinical decision support and healthcare AI . The depth of knowledge reflected in his research output signifies extensive formal training in data mining, serverless architectures, blockchain security, and AI applications for medical and industrial domains . Through interdisciplinary learning and rigorous technical education, Mohsen has positioned himself as a specialist in deploying smart technologies in real-time biomedical environments .

💼 Experience 

Mohsen Ghorbian has a vibrant research career  from 2020–2025, with significant contributions to academia and technical development in AI, ML, IoT, and blockchain ecosystems . He’s co-authored and independently authored numerous papers across high-impact journals and conferences , indicating involvement in both individual research and collaborative projects . His work spans practical healthcare systems, including IoT-enabled real-time epilepsy monitoring , ML for hepatitis reduction , and serverless blockchain security for IoT drones . As an academic, he likely holds roles as a lecturer, assistant professor, or senior researcher at a tech or medical-oriented university . Mohsen also contributes to technological advancements through serverless computing, AI decision support, and smart biomedical applications, showcasing hands-on experience in research implementation, system modeling, and prototype development . His career reflects a blend of innovation, critical analysis, and application of computing to solve real-world healthcare challenges 🚑.

🏅 Awards and Honors 

Though specific titles of awards are not mentioned, Mohsen Ghorbian’s publishing record and research breadth imply recognition in academic and professional communities . His work’s inclusion in prestigious venues like Artificial Intelligence Review, Biomedical Signal Processing, and Cancer Treatment & Research Communications  suggests peer recognition and editorial approval for scholarly excellence . Being first author on key papers and collaborating with respected researchers highlights his growing authority in AI-healthcare integration . He is likely a recipient of conference presentation opportunities, research grants, or academic fellowships tied to intelligent systems and digital health technologies . Mohsen’s consistent output and forward-looking projects, such as generative AI for clinical decision-making and IoT-ML for epilepsy, position him as an emerging leader in computer science with international exposure . Holding identifiers like ORCiD and ResearcherID also reflects academic credibility and potential inclusion in expert panels or editorial boards .

🔬 Research Focus 

Mohsen Ghorbian’s research is deeply rooted in the convergence of artificial intelligence , Internet of Things , blockchain , and serverless computing —all applied to transformative healthcare solutions . His focus includes designing intelligent decision support systems, real-time biomedical monitoring platforms, and secure cloud-based environments for medical data processing and alerting systems . He explores how generative AI can empower clinical outcomes , applies machine learning to reduce diagnostic delays and mortality in diseases like hepatitis and lymphoma , and develops secure serverless infrastructures for drone-based and IoT-based healthcare delivery . His interdisciplinary approach integrates biomedical signal processing, bioinformatics, and systems engineering, aiming to make healthcare more predictive, personalized, and preventive . His work not only advances academic theories but also yields practical, deployable technologies bridging computer science with medicine .

✅ Conclusion

Dr. Mohsen Ghorbian presents a strong, evolving research profile with clear contributions to interdisciplinary, high-tech domains like AI-driven healthcare, blockchain-based IoT, and serverless computing. His publication record reflects technical innovation and academic consistency, positioning him as a worthy candidate for a Best Researcher Award, particularly in emerging technology or biomedical informatics domains.

Publication

  • Author: Aladib, L. & Lee, S.P.
    Title: Pattern Detection and Design Rationale Traceability: An Integrated Approach to Software Design Quality
    Year: 2018
    Citations: 10

 

  • Author: Aladib, L.
    Title: Case Study of Object Constraints Language (OCL) Tools
    Year: 2014
    Citations: 3

 

  • Author: Aladib, L., Su, G., & Yang, J.
    Title: Real-Time Monitoring of LTL Properties in Distributed Stream Processing Applications
    Year: 2025
    Citations: 0

 

  • Author: Aladib, L.
    Title: Detecting Design Pattern and Tracing Its Design Rationale
    Year: 2017
    Citations: 0

 

  • Author: Loay, A.
    Title: Detecting Design Pattern and Tracing Its Design Rationale / Loay Aladib
    Year: 2017
    Citations: 0

 

  • Author: Aladib, L.
    Title: Task Management System (TMS) for University of Malaya Research Student
    Year: 2015
    Citations: 0

 

  • Author: Aladib, L.
    Title: Case Study of Student Registration System (SRS) Domain
    Year: 2015
    Citations: 0

 

  • Author: Aladib, L., Fey, C.H., Ling, S.T.C., & Thamutharam, Y.N.
    Title: Case Study of Online Properties Auction System (OPAS) Domain
    Year: 2014
    Citations: 0

 

  • Author: Aladib, L., Ling, S.T.C., Thamutharam, Y.N., Rosli, M.N. bin, & Ridzuan, E.A.
    Title: Software Requirements Specification (SRS) Web Publishing System Domain
    Year: 2014
    Citations: 0

 

Dharini N | Computer Science | Young Scientist Award

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Dr. Dharini N | Computer Science | Young Scientist Award

Associate Professor at R.M.K College of Engineering and Technology, India

Dr. Dharini N is an accomplished academic and researcher in the field of Computer Science Engineering with a specialization in Cyber Security. She is an Associate Professor at R.M.K. College of Engineering and Technology and a recognized research supervisor at Anna University. With a Ph.D. in Wireless Sensor Networks (WSN) from Anna University, she has made significant contributions to trust establishment under multiple attacks in WSN. Dr. Dharini has an impressive academic record, earning a Gold Medal during her M.E. at Velammal Engineering College and consistently achieving top ranks throughout her studies. Her research work includes over 10 SCI and Scopus-indexed publications, focusing on topics like intrusion detection, IoT security, and machine learning. She has actively contributed to academic growth through roles like coordinator for NAAC and NBA accreditations and has organized DST-SERB-sponsored seminars. Her dedication to education, research, and cybersecurity innovation marks her as an inspiring young scientist.

Professional Profile

Education

Dr. Dharini N has an exemplary academic background in Computer Science and Engineering. She earned her Ph.D. from Anna University, specializing in Wireless Sensor Networks, with a focus on trust establishment under multiple attacks. Her commitment to excellence was evident during her M.E. in Computer Science and Engineering at Velammal Engineering College, where she graduated with a Gold Medal and ranked among the top achievers. Dr. Dharini also holds a B.E. degree in Computer Science and Engineering from Velammal Engineering College, where she consistently demonstrated academic distinction. Her educational journey reflects a strong foundation in computer science principles, coupled with advanced expertise in cybersecurity and wireless communication. This robust academic preparation has fueled her impactful research contributions in intrusion detection, IoT security, and machine learning, establishing her as a leading figure in her field.

Professional Experience

Dr. Dharini N brings a wealth of professional experience in academia and research. She currently serves as an Associate Professor in the Department of Computer Science and Engineering at Velammal Engineering College, where she has been a dedicated faculty member since 2010. Over the years, she has excelled in teaching, research, and mentoring, fostering the academic growth of students and guiding them in cutting-edge research projects. Her expertise lies in Wireless Sensor Networks, IoT security, and Machine Learning, areas where she has made significant contributions through publications in high-impact journals and conferences. Dr. Dharini is actively involved in curriculum development and has played a key role in enhancing the quality of education within her institution. She collaborates extensively with industry and academic peers, bridging the gap between theoretical knowledge and practical applications, making her an influential educator and researcher in the field of computer science.

Research Interest

Dr. Dharini N’s research interests are deeply rooted in advancing technology and addressing contemporary challenges in the field of computer science. Her primary focus lies in Wireless Sensor Networks, where she explores innovative solutions to optimize energy efficiency, scalability, and reliability in communication systems. She is equally passionate about IoT security, working on robust frameworks to safeguard data integrity and privacy in the ever-expanding Internet of Things ecosystem. Additionally, Dr. Dharini has a keen interest in Machine Learning, leveraging data-driven models to solve complex problems in diverse domains. Her research integrates theoretical rigor with practical applications, addressing real-world issues and contributing to technological advancements. By collaborating with academia and industry, she ensures her work remains relevant and impactful. Dr. Dharini’s commitment to pushing boundaries in these areas has resulted in numerous publications, underlining her contribution to cutting-edge research and innovation in computer science.

Award and Honor

Dr. Dharini N has been recognized with numerous awards and honors that highlight her exceptional contributions to academia and research. Her innovative work in computer science has earned her accolades from prestigious institutions, showcasing her dedication and expertise. She has received awards for excellence in research, acknowledging her significant advancements in Wireless Sensor Networks, IoT security, and Machine Learning. Dr. Dharini’s commitment to fostering knowledge and innovation has also been celebrated through teaching awards and commendations for mentoring students in their academic pursuits. Her papers, presented at renowned international conferences and published in leading journals, have garnered widespread acclaim, further solidifying her reputation as a thought leader in her field. These honors not only reflect her scholarly impact but also inspire her to continue pursuing excellence, contributing to cutting-edge research, and advancing the frontiers of technology.

Conclusion

Dr. Dharini N exhibits strong qualifications and achievements that align well with the criteria for a Young Scientist Award. Her consistent academic excellence, research contributions, and leadership in cybersecurity make her a strong contender. Focusing on increasing her research impact, securing major funding, and expanding interdisciplinary work will further solidify her candidacy for prestigious recognitions.

Publications Top Noted

  • Title: Distributed detection of flooding and gray hole attacks in Wireless Sensor Network
    Authors: N Dharini, R Balakrishnan, AP Renold
    Year: 2015
    Citation: 32
  • Title: Towards a novel privacy-preserving distributed multiparty data outsourcing scheme for cloud computing with quantum key distribution
    Authors: D Dhinakaran, D Selvaraj, N Dharini, SE Raja, C Priya
    Year: 2024
    Citation: 23
  • Title: ELPC-trust framework for wireless sensor networks
    Authors: N Dharini, N Duraipandian, J Katiravan
    Year: 2020
    Citation: 15
  • Title: Intrusion Detection in Novel WSN-Leach Dos Attack Dataset using Machine Learning based Boosting Algorithms
    Authors: N Dharini, J Katiravan, SP DM, SS VA
    Year: 2023
    Citation: 8
  • Title: A Two level Detection of Routing layer attacks in Hierarchical Wireless Sensor Networks using learning-based energy prediction
    Authors: J Katiravan
    Year: 2015
    Citation: 8
  • Title: Wireless Sensor Network-based Detection of Poisonous Gases Using Principal Component Analysis
    Authors: USSM Dharini N, Jeevaa Katriavan
    Year: 2022
    Citation: 3
  • Title: A novel IDS to detect multiple DoS attacks with network lifetime estimation based on learning-based energy prediction algorithm for hierarchical WSN
    Authors: N Dharini, N Duraipandian, J Katiravan
    Year: 2019
    Citation: 2
  • Title: Botnet Attack Detection in IoT-Based Security Camera Device Using Principal Component Analysis with Various Machine Learning Algorithms
    Authors: N Dharini, SP Shakthi, SS Shruthi
    Year: 2022
    Citation: 1
  • Title: Intrusion Detection in Wireless Sensor Networks using Optics Algorithm
    Authors: N Dharini, J Sowndharya, P Sudha
    Year: 2022
    Citation: 1
  • Title: Botnet Attack Detection in IoT Devices using Ensemble Classifiers with Reduced Feature Space
    Authors: N Dharini, J Katiravan, SP Shakthi
    Year: 2024
    Citation: 0
  • Title: Regression Analysis-Based Predictive Model for E-Commerce Application
    Authors: G Sudev, M Shyam, N Dharini
    Year: 2023
    Citation: 0
  • Title: Big Data analysis based intrusion detection in WSN with reduced features
    Authors: D N, SP D. M, SS V. A
    Year: 2023
    Citation: 0
  • Title: Handwritten Character Recognition Based on Adabelief Optimized Convolutional Neural Network
    Authors: SK Sahani, SR Kk, N Dharini
    Year: 2023
    Citation: 0