Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

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Ms. Elahe Rahmani Samani | Artificial Intelligence | Young Researcher Award

Ms. Elahe Rahmani Samani, Undergraduate Researcher, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Ms. Elahe Rahmani Samani is a dedicated undergraduate researcher in Healthcare Management at Shahid Sadoughi University of Medical Sciences, Yazd, Iran. With a strong commitment to advancing health systems through innovative technologies, she has emerged as a promising young voice in the intersection of healthcare and artificial intelligence. As the corresponding author of a high-impact study published in the International Journal of Medical Informatics, she has already gained visibility on an international platform. Elahe is also an editorial board member of a university-affiliated journal and actively engages in research collaboration, demonstrating leadership and academic excellence early in her career.

Publication Profile

ORCID

🎓 Education Background

Ms. Elahe Rahmani Samani is currently pursuing her undergraduate degree in Healthcare Management at Shahid Sadoughi University of Medical Sciences in Yazd, Iran. Her academic journey has been marked by an early passion for healthcare innovation and policy development. As a student member of the Health Policy and Management Research Center, she has access to extensive research mentorship and academic resources, which support her pursuits in AI integration in health systems. Her education equips her with both practical management knowledge and technical understanding essential for modern health leadership. She continues to excel academically, contributing meaningfully to her institution’s research mission.

💼 Professional Experience

Although still an undergraduate student, Ms. Rahmani Samani has demonstrated remarkable initiative by leading and collaborating on several research projects. Her standout experience includes serving as the primary researcher and corresponding author for a study on AI adoption in hospital settings, presented at the International Congress on Artificial Intelligence in Health. She also serves on the editorial board of a university-affiliated journal, where she helps shape academic content for peer learning. Elahe’s active involvement in health systems projects, poster sessions, and ongoing collaborations reflect her deep engagement with practical and theoretical aspects of healthcare management.

🏆 Awards and Honors

While formal awards are yet to be recorded due to her early stage in academia, Ms. Elahe Rahmani Samani has achieved significant recognition by publishing in a Scopus-indexed journal and presenting at an international congress. She earned certificates of participation from the International Congress on Artificial Intelligence in Health and is continuously contributing to scholarly work in health systems. Her selection for the editorial board role and involvement in a university-level book project highlight the academic community’s acknowledgment of her talents. Her publication is already accessible through global platforms and is poised to gain academic citations in the near future.

🔬 Research Focus

Elahe Rahmani Samani’s research interests revolve around hospital and healthcare management, particularly in leveraging artificial intelligence to optimize health systems for both patients and staff. She has successfully completed one major research project that analyzes hospital managers’ perspectives on AI integration—an innovative topic reflecting current global trends. Her work aims to influence strategic decision-making within health institutions by promoting the adoption of intelligent systems. She is also contributing to an ongoing book project in healthcare management and continues to work on four other health-related research studies, exploring themes of efficiency, technology adoption, and patient-centered care in health policy.

🧭 Conclusion

Ms. Elahe Rahmani Samani exemplifies the drive and intellect of a next-generation healthcare researcher. Her early publication in a high-impact journal and involvement in both local and international academic platforms underscore her potential to become a leader in the field. With a unique blend of management insight and technological perspective, she aims to transform how healthcare institutions approach innovation. Her commitment to research excellence, combined with her growing professional network and academic contributions, positions her as a strong contender for the Young Researcher Award. Her journey is only beginning, and she is already contributing to global discussions in health innovation.

📚 Top Publication Note

Title: Managers’ perceptions and attitudes toward the use of artificial intelligence technology in selected hospital settings
Authors: Mousavi SM, RahmaniSamani E, Raadabadi M, DehghaniTafti A
Journal: International Journal of Medical Informatics
Year: 2025

Wai Yie Leong | Data Science | Best Researcher Award

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Prof. Dr. Wai Yie Leong | Data Science | Best Researcher Award

Senior Professor at INTI International University, Malaysia

IR. Prof. Dr. Leong Wai Yie is a distinguished researcher and academic leader in electrical engineering, with a Ph.D. from The University of Queensland, Australia. She specializes in smart sensor networks, AI, big data analytics, and sustainable city technologies. A Fellow of IET (UK) and IEM, she has held senior positions at top Malaysian universities and contributed significantly to research excellence, program accreditation, and innovation. She has secured international research grants, published widely in high-impact journals, and received multiple Best Paper Awards. Her work bridges academia and industry, advancing cutting-edge solutions in healthcare, engineering, and Industry 4.0 systems.

📚Professional Profile

Orcid

Scopus

Google Scholar

🎓Academic Background

IR. Prof. Dr. Leong Wai Yie holds a strong academic foundation in electrical engineering. She earned her Bachelor’s degree with First Class Honours in Electrical Engineering from The University of Queensland, Australia, in 2001. Continuing her academic excellence, she completed her Ph.D. in Electrical Engineering at the same institution in 2005. Her educational journey provided a solid basis for her specialization in smart sensor systems, artificial intelligence, and data analytics. The rigorous training and research exposure during her studies laid the groundwork for her influential career in academia, research leadership, and multidisciplinary engineering innovation across international platforms.

💼Professional Experience

IR. Prof. Dr. Leong Wai Yie has over two decades of academic and research experience, holding senior roles in top institutions such as INTI International University, Perdana University, MAHSA University, and Taylors University. She has served as Dean, Director of Research Excellence, and Head of Department, contributing to academic program development, accreditation, and research strategy. Her earlier roles include project management at SIMTech, A*STAR Singapore, and lecturer positions at Imperial College London and The University of Queensland. Her experience bridges academia and industry, focusing on innovation, research commercialization, and the advancement of smart technologies and engineering education.

🏅Awards and Honors

IR. Prof. Dr. Leong Wai Yie has received numerous prestigious awards recognizing her research excellence and innovation. In 2024 alone, she earned multiple Best Paper Awards at international IEEE conferences in Taiwan, Thailand, Vietnam, and Japan. She also received the 2024 Travel Grant Award from the Institution of Engineering and Technology (UK). These accolades reflect her contributions to smart technologies, biomedical engineering, and sustainable systems. Her work has been consistently recognized for its originality, societal relevance, and technical impact, solidifying her reputation as a leading figure in engineering research both regionally and globally.

🔬Research Focus

IR. Prof. Dr. Leong Wai Yie’s research centers on emerging technologies with strong societal and industrial impact. Her primary areas include smart sensor networks, big data analytics, artificial intelligence, remote sensing, and sustainable city development. She is actively involved in advancing Industry 4.0 applications and international standards for engineering systems. Her interdisciplinary approach bridges biomedical engineering, environmental monitoring, and intelligent systems design. Through extensive collaboration with global institutions, she has developed innovative solutions in health diagnostics, aerospace tracking, and smart infrastructure. Her research aims to enhance quality of life through data-driven, intelligent, and sustainable technological advancements.

Citations:

📚 Citations: 1,022 (by 431 documents)
📄 Publications: 189 documents
📊 h-index: 16

📖Publication Top Notes

Potential and utilization of thermophiles and thermostable enzymes in biorefining
📅 Year: 2007 | Cited by: 781

Using indirect protein–protein interactions for protein complex prediction
📅 Year: 2008 | Cited by: 202

Endoglucanases: insights into thermostability for biofuel applications
📅 Year: 2013 | Cited by: 162

B-MYB is essential for normal cell cycle progression and chromosomal stability of embryonic stem cells
📅 Year: 2008 | Cited by: 123

Signal processing techniques for knowledge extraction and information fusion
📅 Year: 2008 | Cited by: 122

Current state and challenges of natural fibre-reinforced polymer composites as feeder in FDM-based 3D printing
📅 Year: 2021 | Cited by: 88

Markers of dengue severity: a systematic review of cytokines and chemokines
📅 Year: 2016 | Cited by: 67

A review of localization techniques in wireless sensor networks
📅 Year: 2023 | Cited by: 60

Convergence of IoT, Blockchain, and Computational Intelligence in Smart Cities
📅 Year: 2024 | Cited by: 51

The nine pillars of technologies for Industry 4.0
📅 Year: 2020 | Cited by: 50

✨Conclusion

Based on her exceptional academic credentials, interdisciplinary research expertise, international recognition, and sustained leadership in engineering innovation, IR. Prof. Dr. Leong Wai Yie stands out as a highly deserving candidate for the Best Researcher Award. With a Ph.D. from The University of Queensland and prestigious fellowships from IET, IEM, and IEEE, she has contributed significantly to cutting-edge fields such as smart sensor networks, AI, and sustainable technologies. Her impactful publications, global collaborations, extensive grant portfolio, and multiple Best Paper Awards in 2024 reflect ongoing excellence. She exemplifies the qualities of a world-class researcher with tangible societal and academic impact.

 

 

Assoc. Prof. Dr. Feng Xie | intelligence systems | Best Researcher Award

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Assoc. Prof. Dr. Feng Xie | intelligence systems | Best Researcher Award

School of Information Science and Technology / Sanda University, China

Dr. Feng Xie is an accomplished Associate Professor at the School of Information Science and Technology, Sanda University, China . With a career that bridges academia and industry, he has been at the forefront of intelligent transportation systems, urban mobility, and smart city innovations. As a tech entrepreneur and researcher, he has led over 500 consultancy projects globally and holds numerous patents and software copyrights. His expertise spans traffic management, AI applications, IoT, and big data analytics, with significant contributions that have earned him prestigious awards and talent program recognitions.

Publication Profile

ORCID

🎓 Education Background:

Dr. Xie earned his Ph.D. from Nanyang Technological University, Singapore , in 2002 and completed his postdoctoral research at Tongji University, China , in 2005. His academic foundation is rooted in transportation engineering, computer science, and intelligent systems, providing the basis for his interdisciplinary approach to research and technology deployment.

💼 Professional Experience:

Currently serving as an Associate Professor at Shanghai Shanda University, Dr. Xie has also been the founder of Shanghai Van-Chance Trans. Technologies (2010–2022), where he led large-scale smart transportation projects across Asia. He worked extensively with government and industry partners, such as Singapore’s Land Transport Authority and IKEA, and directed projects like the world’s largest underground parking facility. He has also held leadership roles in cross-border technology associations and has developed systems used in cities like Beijing, Hangzhou, and Wuhan.

🏆 Awards and Honors:

Dr. Feng Xie has been recognized with several prestigious awards, including the IES Engineering Achievement Award in 2004 for his contributions to Singapore’s i-Transport project and the Shanghai Science Progress Award in 2013. He has also been selected for elite talent programs such as the Shanghai “3310” Overseas High-level Talent Program and Nanjing “321” Leading Technology Entrepreneurship Talent Program. His innovative work has resulted in 5 patents and 9 software copyrights, solidifying his impact in both academic and applied research domains.

🧠 Research Focus:

Dr. Xie’s research is centered on Intelligent Transportation Systems (ITS), AI-driven traffic management, smart parking, indoor positioning, urban planning, and emerging tech applications in IoT and quantitative finance. His efforts in traffic simulation, traveler behavior modeling, and data-driven urban development have influenced policies and technologies in smart mobility across multiple major cities. He has collaborated with Tongji University, published in Transportation Research Board journals, and contributed to key projects with global relevance.

✅ Conclusion:

With a unique blend of academic rigor and entrepreneurial innovation, Dr. Feng Xie exemplifies leadership in intelligent systems and sustainable urban technology 🌍. His work has profoundly shaped how modern cities approach mobility, data analytics, and smart infrastructure development. He continues to push the boundaries of AI, transportation science, and cross-border collaboration, earning him a rightful nomination for the Best Researcher Award.

📚 Top Publications :

PDCG-Enhanced CNN for Pattern Recognition in Time Series Data
Journal: Elsevier – Expert Systems with Applications
Year: 2022 | Cited by: 38 articles

Modeling Traveler Behavior Using Hybrid RP/SP Data and Path-Size Logit Models
Journal: Transportation Research Record: Journal of the Transportation Research Board
Year: 2012 | Cited by: 65 articles

AI-Based Traffic Incident Management Systems: A Case Study of Singapore’s i-Transport Project
Journal: IEEE Transactions on Intelligent Transportation Systems
Year: 2014 | Cited by: 79 articles

Urban Traffic Simulation Using GPS Data Fusion and Adaptive Signal Optimization
Journal: Journal of Transportation Engineering, ASCE
Year: 2016 | Cited by: 45 articles

Smart Parking Systems Powered by IoT and AI: A Case Study of Guinness Record Facility
Journal: Sensors (MDPI)
Year: 2020 | Cited by: 54 articles

Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

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Dr. Saikat Gochhait | Artificial Intelligence | Best Researcher Award

Assistant Professor, Symbiosis International (Deemed to be University), India

Dr. Saikat Gochhait is an accomplished Indian academic, researcher, and innovator, currently serving as an Assistant Professor at Symbiosis International Deemed University, Pune. With a strong background in management, information technology, and behavioral sciences, he also contributes as a Research Team Member at the Symbiosis Centre for Behavioral Sciences and Adjunct Faculty at the Neuroscience Research Institute, Samara State Medical University, Russia. He is a prolific inventor with several published patents and has been recognized for his contributions to interdisciplinary research in artificial intelligence, neuroscience, and optimization algorithms.

Publication Profile

🎓 Education Background

Dr. Gochhait earned his Doctor of Philosophy (Ph.D.) in Management from Sambalpur University in 2014 🧠, a Master’s in Business Management from the same university in 2009 📊, and a Master’s in Information Technology from Sikkim Manipal University in 2017 💻. His diverse academic training has laid a multidisciplinary foundation that supports his cross-functional research across business, IT, and neuroscience domains.

💼 Professional Experience

With over two decades of experience spanning academia and industry, Dr. Gochhait has held key roles such as Assistant Professor at ASBM University, Khalikote University, and HOD at Sambhram Institute of Technology. His industry experience includes strategic roles at IFGL Refractories Ltd. and Tata Krosaki Refractories Ltd. Currently, at Symbiosis International University, he mentors postgraduate and doctoral students, manages AI-centric research projects, and continues collaborative ventures with prestigious institutions including IIT Roorkee and international universities 🌏.

🏆 Awards and Honors

Dr. Gochhait has been honored as a Senior Member of IEEE in 2019 and recognized by the Alpha Network of the Federation of European Neuroscience Societies in 2024 🌟. His academic excellence has earned him international research fellowships from leading institutions, including the Natural Sciences and Engineering Research Council of Canada, Samara State Medical University (Russia), National Dong Hwa University (Taiwan), and the University of Deusto (Spain), with total grants exceeding USD 20,000 💰.

🔬 Research Focus

Dr. Gochhait’s research is rooted in artificial intelligence, behavioral science, energy prediction, bio-inspired optimization algorithms, and neuroscience-enhanced technology applications 🧬. He is a principal investigator of high-impact government-funded projects such as AI-based load forecasting for dispatch centers and BCI-integrated neurofeedback games. His innovations also extend to smart agriculture and transport systems, reflecting his dedication to societal improvement through technology 🤖🌱.

✅ Conclusion

Blending visionary academic pursuit with innovative problem-solving, Dr. Saikat Gochhait continues to drive global research collaborations, mentor emerging scholars, and contribute meaningful technological solutions to real-world challenges 📚🌍. His evolving body of work bridges disciplines, industries, and nations, making him a respected figure in AI, management, and neuroscience research.

📚 Top Publications

Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Biomimetics, 2024 – Indexed in Scopus/WoS
Cited by: 12 articles

Dollmaker Optimization Algorithm: A Novel Human-Inspired Optimizer for Solving Optimization Problems
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 9 articles

Addax Optimization Algorithm: A Novel Nature-Inspired Optimizer for Solving Engineering Applications
International Journal of Intelligent Engineering and Systems, 2024 – Indexed in Scopus
Cited by: 7 articles

Enhancing Household Energy Consumption Predictions Through Explainable AI Frameworks
IEEE Access, 2024 – Indexed in Scopus/WoS
Cited by: 15 articles

URL Shortener for Web Consumption: An Extensive and Impressive Security Algorithm
 Indonesian Journal of Electrical Engineering and Computer Science, 2024 – Indexed in Scopus
 Cited by: 6 articles

Dr. Uddalak Mitra | Machine learning | Best Researcher Award

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Dr. Uddalak Mitra | Machine learning | Best Researcher Award

Assistant Professor, JIS College of Engineering, India

Dr. Uddalak Mitra is an esteemed Assistant Professor at JIS College of Engineering, specializing in bioinformatics, machine learning, and deep learning 🧬🤖. With a strong academic foundation and a passion for research, he has significantly contributed to the intersection of computational intelligence and biological sciences. His expertise lies in decoding DNA, RNA, and protein sequences using cutting-edge AI techniques, paving the way for advancements in healthcare and genomics. Dr. Mitra’s work seamlessly blends theoretical knowledge with real-world applications, making impactful strides in both academia and industry.

Publication Profile

Google Scholar

🎓 Education:

Dr. Mitra has built a solid academic background in computational sciences, equipping himself with the expertise required to address complex biological challenges. His educational journey has provided him with the technical prowess to integrate artificial intelligence into biomedical research.

💼 Experience:

As an Assistant Professor at JIS College of Engineering, Dr. Mitra actively engages in research and mentoring, shaping the next generation of scientists. His work focuses on applying machine learning models to analyze biological data, improving early disease detection methodologies. Additionally, he has authored several research papers and contributed to the academic community through his innovative studies.

🏆 Awards and Honors:

Dr. Mitra has made commendable contributions to scientific research, earning recognition for his published works. He holds 9 patents, showcasing his dedication to innovation. His memberships in esteemed organizations like IFERP and ISTE reflect his commitment to professional development and research excellence.

🔬 Research Focus:

His research primarily revolves around bioinformatics, machine learning, and deep learning. He explores information-theoretic tools for biological sequence analysis, integrating artificial intelligence to derive meaningful insights from genomic data. His recent studies focus on clinical applications of AI, particularly in disease diagnosis and personalized medicine.

🔍 Conclusion:

Dr. Uddalak Mitra is a pioneering researcher dedicated to bridging the gap between bioinformatics and artificial intelligence. His contributions to genomic research, coupled with his expertise in AI-driven disease diagnosis, make him a valuable asset to the scientific community. With a strong foundation in computational biology, he continues to push the boundaries of research, striving for innovations that benefit both medicine and technology.

📚 Publications:

Leveraging AI and Machine Learning for Next-Generation Clinical Decision Support Systems (CDSS) – Published in AI-Driven Innovation in Healthcare Data Analytics, 2025.

Cognitive Handwriting Insights for Alzheimer’s Diagnosis: A Hybrid Framework – Information, 2025

Integrated System for Disease Detection Using Semiconductor-Based Gas Sensors and AI/ML – IN Patent A61B0005080000, 2025

Significance of AI/ML Wearable Technologies for Education and Teaching – Wearable Devices and Smart Technology for Educational Teaching Assistance, 2025

Integrating AI/ML With Wearable Devices for Monitoring Student Mental Health – Wearable Devices and Smart Technology for Educational Teaching Assistance, 2025

The Evolution of Entrepreneurship in the Age of AI – Advanced Intelligence Systems and Innovation in Entrepreneurship, 2024

A Novel Algorithm for Genomic STR Mining: Application to Phylogeny Reconstruction and Taxa Identification – International Journal of Bioinformatics Research and Applications, 2024

Zeshan Khan | Artificial Intelligence| Best Researcher Award

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Assoc. Prof. Dr. Zeshan Khan |Artificial Intelligence| Best Researcher Award

Associate Professor, National Yunlin University of Science and Technology, Taiwan

Dr. Zeshan Aslam Khan is an esteemed Associate Professor at the International Graduate School of Artificial Intelligence, National Yunlin University of Engineering Sciences and Technology. With a strong background in Artificial Intelligence, Image Analysis, and Recommender Systems, he has made significant contributions to academia and industry. As the Director of the PRISM Lab, he actively supervises cutting-edge AI research, fostering innovation in Smart Metering, Fingerprint Recognition, and Alzheimer’s Detection. His work is recognized globally, with prestigious awards, high-impact publications, and collaborations with leading research institutions in the UK, Ireland, Taiwan, and Pakistan. 🌍📚

Publication Profile

Scopus

🎓 Education

Dr. Khan holds a Ph.D. in Electronic Engineering (2020) with a specialization in Learning Machines for Recommender Systems. His academic journey includes an M.Sc. in Computer Systems Engineering from Halmstad University, Sweden (2010), and a B.Sc. in Computer Information Systems Engineering from UET Peshawar, Pakistan (2005). His extensive educational background has laid a strong foundation for his expertise in AI-driven systems and computational intelligence. 🎓🔬

💼 Experience

With over a decade of experience, Dr. Khan has established himself as a leading researcher and educator in Artificial Intelligence. He has served as a Visiting Researcher at the University of Birmingham (UK) and the University of Galway (Ireland). His industry collaborations include partnerships with the National Radio Telecommunication Corporation (NRTC), Pakistan, and the Future Technology Research Center, Taiwan. As an Associate Editor of the Journal of Innovative Technologies (JIT) and a reviewer for top-tier journals like IEEE Transactions on AI, he plays a crucial role in shaping AI research globally. 🌟🔍

🏆 Awards and Honors

Dr. Khan’s excellence in research and academia has been recognized through numerous accolades. He was awarded the prestigious Ph.D. Gold Medal (2020) and the Faculty Research Brilliance Award (2022). In 2023, he received the Productive Researcher Award for his outstanding publications and graduate supervisions. His work has also secured significant research grants, including the Pakistan Engineering Council (PEC) Grant and the Higher Education Commission (HEC) Grant, enabling advancements in AI and IoT applications. 🏅🔬

🔬 Research Focus

Dr. Khan’s research revolves around Artificial Intelligence, Image Classification/Segmentation, Recommender Systems, Embedded Systems, and Fractional Calculus. His groundbreaking work in explainable AI, fractional optimization, and chaotic heuristics has been widely published in high-impact Q1 journals. His innovative contributions include developing AI-powered solutions for healthcare, smart metering, and signature verification, bridging the gap between academia and industry through real-world applications. 🤖📈

📝 Conclusion

Dr. Zeshan Aslam Khan stands as a prominent figure in the field of Artificial Intelligence, with a profound impact on research, education, and industry collaborations. His dedication to AI-driven solutions, student mentorship, and high-impact publications solidifies his reputation as a leader in predictive intelligence and systems modeling. With a global research footprint and numerous accolades, he continues to drive technological advancements that shape the future of AI. 🌍🚀

📚 Publications 

Generalized fractional optimization-based explainable lightweight CNN model for malaria disease classification – Computers in Biology and Medicine, 2025 (Q1, IF: 7.0) [Link] 📖🔬

Fractional Gradient Optimized Explainable CNN for Alzheimer’s Disease Diagnosis – Heliyon, 2024 (Q1, IF: 3.4) [Link] 🧠📊

Design of chaotic Young’s double slit experiment optimization heuristics for nonlinear muscle model identification – Chaos, Solitons & Fractals, 2024 (Q1, IF: 5.3) [Link] 🎯💡

A gazelle optimization expedition for key term separated fractional nonlinear systems applied to muscle modeling – Chaos, Solitons & Fractals, 2024 (Q1, IF: 5.3) [Link] 📉⚙️

Generalized fractional strategy for recommender systems with chaotic ratings behavior – Chaos, Solitons & Fractals, 2022 (Q1, IF: 5.3) [Link] ⭐🔍

Lianbo Ma | Artificial Intelligence | Best Researcher Award

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Prof. Lianbo Ma | Artificial Intelligence | Best Researcher Award

Professor, Northeastern University, China

Dr. Lianbo Ma is a distinguished professor at Northeastern University, China, with expertise in computational intelligence, machine learning optimization, big data analysis, and natural language processing. With a Ph.D. from the University of Chinese Academy of Sciences, he has significantly contributed to bio-inspired computing, multi-objective optimization, and cloud computing resource allocation. As a prolific researcher, Dr. Ma has published over 90 papers in high-impact journals and conferences, earning global recognition for his work. His research has been widely cited, and he has received numerous prestigious awards, making him a key figure in artificial intelligence and optimization.

Publication Profile

Google Scholar

🎓 Education

Dr. Ma holds a Doctorate in Machine-Electronic Engineering from the University of Chinese Academy of Sciences (2014). He earned his Master’s degree (2007) and Bachelor’s degree (2004) in Information Science and Engineering from Northeastern University, China. His academic journey has provided a solid foundation in AI-driven optimization, neural networks, and computational intelligence.

💼 Experience

Dr. Ma has held various esteemed positions in academia and research institutions. Since 2017, he has been a professor at Northeastern University, China, specializing in software engineering and AI. He previously served as an associate professor (2016-2017) and assistant research fellow at the Shenyang Institute of Automation, Chinese Academy of Sciences (2007-2015). His international experience includes a visiting scholar position at Surrey University, UK (2019-2020), under the mentorship of Prof. Yaochu Jin. His extensive professional journey highlights his contributions to AI-driven industrial applications and large-scale optimization.

🏆 Awards and Honors

Dr. Ma has been recognized among the World’s Top 2% Scientists (Elsevier & Stanford, 2022-2023) and has received several prestigious accolades, including the IEEE Best Paper Runner-Up Award (2023), the Best Student Paper Award at the International Conference on Swarm Intelligence (2021), and the Outstanding Reviewer Awards from Elsevier (2016, 2018). His achievements extend to the Liaoning Province Natural Science Academic Award and the BaiQianWan Talents Project Award. His dedication to research and mentorship is further evident in his recognition as an Excellent Master’s Thesis Instructor.

🔬 Research Focus

Dr. Ma’s research spans computational intelligence, large-scale multi-objective optimization, and bio-inspired computing. His expertise extends to cloud computing, edge computing, and social network analysis, where he has worked on cloud resource allocation and influence maximization. He is also actively engaged in multi-modal data processing, focusing on knowledge graphs, entity extraction, and text mining. His research integrates AI with industrial applications, advancing neural architecture search and intelligent data analysis.

🔍 Conclusion

Dr. Lianbo Ma is a pioneering researcher in artificial intelligence, computational intelligence, and machine learning optimization. His contributions to big data analytics, neural architecture search, and evolutionary computation have positioned him as a leading figure in the field. With numerous accolades, high-impact publications, and extensive academic service, Dr. Ma continues to shape the future of AI-driven optimization and intelligent computing. 🚀

📖 Publications

A Hybrid Neural Architecture Search Algorithm Optimized via Lifespan Particle Swarm Optimization for Coal Mine Image Recognition

Truthful Combinatorial Double Auctions for Mobile Edge Computing in Industrial IoT. IEEE Transactions on Mobile Computing, 21(11), 4125-4138. DOI

Single-Domain Generalized Predictor for Neural Architecture Search System. IEEE Transactions on Computers. DOI

One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training. AAAI-24 Conference Proceedings.

Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search. IEEE Transactions on Evolutionary Computation. DOI

An Adaptive Localized Decision Variable Analysis Approach to Large-Scale Multiobjective and Many-objective Optimization. IEEE Transactions on Cybernetics, 52(7), 6684-6696. DOI

Enhancing Learning Efficiency of Brain Storm Optimization via Orthogonal Learning Design. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(11), 6723-6742. DOI

 

QIANG QU | Artificial Intelligence Award | Best Researcher Award

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Prof. QIANG QU | Artificial Intelligence Award | Best Researcher Award

PROFESSOR, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Dr. Qiang Qu is a distinguished professor and a leading researcher in blockchain, data intelligence, and decentralized systems. He serves as the Director of the Guangdong Provincial R&D Center of Blockchain and Distributed IoT Security at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS). Additionally, he holds a professorship at Shenzhen University of Advanced Technology and has previously served as a guest professor at The Chinese University of Hong Kong (Shenzhen). Dr. Qu has also contributed as the Director and Chief Scientist of Huawei Blockchain Lab. With a strong international academic presence, he has held research positions at renowned institutions such as ETH Zurich, Carnegie Mellon University, and Nanyang Technological University. His pioneering work focuses on scalable algorithm design, data sense-making, and blockchain technologies, making significant contributions to AI, data systems, and interdisciplinary studies.

Publication Profile

🎓 Education

Dr. Qiang Qu earned his Ph.D. in Computer Science from Aarhus University, Denmark, under the supervision of Prof. Christian S. Jensen. His doctoral research was supported by the prestigious GEOCrowd project under Marie Skłodowska-Curie Actions. He further enriched his academic journey as a Ph.D. exchange student at Carnegie Mellon University, USA. He holds an M.Sc. in Computer Science from Peking University, China, and a B.S. in Management Information Systems from Dalian University of Technology.

💼 Experience

Dr. Qu has a diverse professional background, reflecting his global expertise. Since 2016, he has been a professor at SIAT, leading groundbreaking research in blockchain and distributed IoT security. He also served as Vice Director of Hangzhou Institutes of Advanced Technology (SIAT’s Hangzhou branch). Prior to this, he was an Assistant Professor and the Director of Dainfos Lab at Innopolis University, Russia. His research journey includes being a visiting scientist at ETH Zurich, a visiting scholar at Nanyang Technological University, and a research fellow at Singapore Management University. He also gained industry experience as an engineer at IBM China Research Lab.

🏅 Awards and Honors

Dr. Qu has received several national and international research grants, recognizing his impactful contributions to blockchain and AI-driven data intelligence. He is a prominent editorial board member of the Future Internet Journal and serves as a guest editor for multiple high-impact journals. As an active contributor to the research community, he has been a TPC (Technical Program Committee) member for prestigious conferences and regularly reviews top-tier AI and data systems journals.

🔬 Research Focus

Dr. Qu’s research interests revolve around data intelligence and decentralized systems, with a strong focus on blockchain, scalable algorithm design, and data-driven decision-making. His work has been instrumental in developing efficient data parallel approaches, AI-driven network analysis, and cross-blockchain data migration techniques. His interdisciplinary contributions bridge AI, IoT security, and geospatial analytics, driving innovation in secure and intelligent computing.

🔚 Conclusion

Dr. Qiang Qu stands as a thought leader in blockchain and data intelligence, combining academic excellence with real-world impact. His contributions to AI-driven decentralized systems and scalable data solutions continue to shape the fields of computer science and IoT security. His extensive research collaborations, editorial roles, and international experience make him a key figure in advancing secure and intelligent computing technologies. 🚀

📚 Publications

SNCA: Semi-supervised Node Classification for Evolving Large Attributed Graphs – IEEE Big Data Mining and Analytics (2024). Cited in IEEE 📖

CIC-SIoT: Clean-Slate Information-Centric Software-Defined Content Discovery and Distribution for IoT – IEEE Internet of Things Journal (2024). Cited in IEEE 📖

Blockchain-Empowered Collaborative Task Offloading for Cloud-Edge-Device Computing – IEEE Journal on Selected Areas in Communications (2022). Cited in IEEE 📖

On Time-Aware Cross-Blockchain Data Migration– Tsinghua Science and Technology (2024). Cited in Tsinghua University 📖

Few-Shot Relation Extraction With Automatically Generated Prompts – IEEE Transactions on Neural Networks and Learning Systems (2024). Cited in IEEE 📖

Opinion Leader Detection: A Methodological Review – Expert Systems with Applications (2019). Cited in Elsevier 📖

Neural Attentive Network for Cross-Domain Aspect-Level Sentiment Classification– IEEE Transactions on Affective Computing (2021). Cited in IEEE 📖

Efficient Online Summarization of Large-Scale Dynamic Networks –  IEEE Transactions on Knowledge and Data Engineering (2016). Cited in IEEE 📖

Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

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Dr. Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Postdoc Fellow, Inje University, South Korea

🎓 Sikandar Ali is a passionate AI researcher and educator specializing in Artificial Intelligence applications in healthcare. Currently pursuing a PhD at Inje University, South Korea, he has a strong academic background and extensive research experience in digital pathology, medical imaging, and machine learning. As a team leader of the digital pathology project, he develops innovative AI algorithms for cancer diagnosis while collaborating with a global team of researchers. Sikandar is a recipient of prestigious scholarships, accolades, and recognition for his contributions to AI and healthcare innovation.

Publication Profile

Google Scholar

Education

📘 Sikandar Ali holds a PhD in Artificial Intelligence in Healthcare (CGPA: 4.46/4.5) from Inje University, South Korea, where his thesis focuses on integrating pathology foundation models with weakly supervised learning for gastric and breast cancer diagnosis. He earned an MS in Computer Science from Chungbuk National University, South Korea (GPA: 4.35/4.5), with research on AI-based clinical decision support systems for cardiovascular diseases. His undergraduate degree is a Bachelor of Engineering in Computer Systems Engineering from Mehran University of Engineering and Technology, Pakistan, with a CGPA of 3.5/4.0.

Experience

💻 Sikandar is an experienced researcher and AI specialist. Currently working as an AI Research Assistant at Inje University, he focuses on cutting-edge projects in digital pathology, cancer detection, and medical imaging. Previously, he worked as a Research Assistant at Chungbuk National University, focusing on cardiovascular disease diagnosis using AI. His industry experience includes roles such as Search Expert at PROGOS Tech Company and Software Developer Intern at Hidaya Institute of Science and Technology.

Awards and Honors

🏆 Sikandar has received multiple awards, including the Brain Korean Scholarship, European Accreditation Council for Continuing Medical Education (EACCME) Certificate, and recognition as an outstanding Teaching Assistant at Inje University. He has also earned full travel grants for international conferences, extra allowances for R&D industry projects, and certificates for reviewing research papers in leading journals. Additionally, he is a Guest Editor at Frontiers in Digital Health.

Research Focus

🔬 Sikandar’s research focuses on developing AI algorithms for medical imaging, with expertise in weakly supervised learning, self-supervised learning, and digital pathology. His projects include designing AI systems for cancer detection, COVID-19 prediction, and IPF severity classification. He also works on object detection applications using YOLO models and wearable sensor-based activity detection for pets. His commitment to explainability and interpretability in AI models ensures their practical utility in healthcare.

Conclusion

🌟 Sikandar Ali is a dedicated AI researcher driving innovation in healthcare through artificial intelligence. With his strong educational foundation, diverse research experience, and impactful contributions, he aims to bridge the gap between AI and medicine, making healthcare more efficient and accessible.

Publications

Detection of COVID-19 in X-ray Images Using DCSCNN
Sensors 2022, IF: 3.4

A Soft Voting Ensemble-Based Model for IPF Severity Prediction
Life 2021, IF: 3.2

Metaverse in Healthcare Integrated with Explainable AI and Blockchain
Sensors 2023, IF: 3.4

Weakly Supervised Learning for Gastric Cancer Classification Using WSIs
Springer 2023

Classifying Gastric Cancer Stages with Deep Semantic and Texture Features
ICACT 2024

Computer Vision-Based Military Tank Recognition Using YOLO Framework
ICAISC 2023

Activity Detection for Dog Well-being Using Wearable Sensors
IEEE Access 2022

Cat Activity Monitoring Using Wearable Sensors
IEEE Sensors Journal 2023, IF: 4.3

Deep Learning for Algae Species Detection Using Microscopic Images
Water 2022, IF: 2.9

Comprehensive Review on Multiple Instance Learning
Electronics 2023

Hybrid Model for Face Shape Classification Using Ensemble Methods
Springer 2021

Cervical Spine Fracture Detection Using Two-Stage Deep Learning
IEEE Access 2024

 

Yunhyung LEE | Computer science| Best Researcher Award

Published on by Computer Scientists Awards

Prof. Dr. Yunhyung LEE | Computer Science | Best Researcher Award

Professor, Korea Institute of Maritime and Fisheries Technology, South Korea

Dr. Yunhyung Lee is a distinguished professor at the Korea Institute of Maritime and Fisheries Technology and an adjunct professor at Korea Maritime and Ocean University. With an academic journey spanning nearly two decades, Dr. Lee has made significant contributions to marine systems engineering, control systems, and maritime research. A prolific researcher and academician, he is known for his innovative approaches in marine electric systems, fuzzy control, and genetic algorithms. His commitment to fostering maritime education and cutting-edge research has earned him several accolades and a global reputation in his field. 🌐✨

Publication Profile

ORCID

Education 🎓

Dr. Lee graduated summa cum laude with a Bachelor’s degree in Marine System Engineering from Korea Maritime and Ocean University in 2002. He further earned his Master’s degree in 2004 and completed his Ph.D. in Mechatronics Engineering in 2007. His academic excellence is reflected in multiple awards, including the President’s Award for graduating with the highest honors. 🏆📚

Professional Experience 💼

Dr. Lee began his academic career as a part-time lecturer at Korea Maritime and Ocean University and Youngsan University. From 2008 to 2014, he served as a professor at the Korea Port Training Institute before joining the Korea Institute of Maritime and Fisheries Technology in 2014. Simultaneously, he has been an adjunct professor at Korea Maritime and Ocean University since 2015. His practical experience includes spearheading innovative research projects and consulting for industry collaborations. ⚙️🛳️

Awards and Honors 🏅

Dr. Lee’s outstanding achievements have been recognized through numerous awards, including the Albert Nelson Marquis Lifetime Achievement Award (2018) and the Young Researcher Award from the Korean Society of Marine Engineering (2015). He has also been honored for his contributions to education and research with awards such as the Best Paper Award by the Korean Federation of Science and Technology Societies (2006) and the Citation for Excellence in Lecturing by Korea Maritime and Ocean University (2008). 🌟🎖️

Research Focus 🔬

Dr. Lee’s research encompasses control engineering, marine electric systems, genetic algorithms, fuzzy control, and PID control. His studies aim to enhance the safety, efficiency, and reliability of marine propulsion systems and other maritime technologies. Through numerous research projects and innovative solutions, he has significantly advanced the field of marine and fisheries technology. 🌊⚡

Conclusion 🌟

Dr. Yunhyung Lee’s exceptional career reflects his dedication to advancing marine and maritime technology through research, education, and industry collaboration. His passion for innovation and his unwavering commitment to excellence make him a leading figure in his field. 🌏✨

Publications 📚

Application of Real-Coded Genetic Algorithm–PID Cascade Speed Controller to Marine Gas Turbine Engine Based on Sensitivity Function Analysis
Mathematics, 2025 – Cited by: 5

Development of Hull Care for Warships Based on a Manned-Unmanned Hybrid System: Focusing on the Underwater Hull Plate
Journal of the KNST, 2024 – Cited by: 3

Modeling and Parameter Estimation of a 2DOF Ball Balancer System
Journal of the Korea Academia-Industrial Cooperation Society, 2024 – Cited by: 4

Ground-Fault Recognition in Low-Voltage Ships Based on Variation Analysis of Phase-to-Ground Voltage and Neutral-Point Voltage
IEEE Access, 2024 – Cited by: 8

Speed Control for Low Voltage Propulsion Electric Motor of Green Ship through DTC Application
Journal of the Korea Academia-Industrial Cooperation Society, 2023 – Cited by: 6

RCGA-PID Controller Based on ITAE for Gas Turbine Engine in the Marine Field
The Journal of Fisheries and Marine Sciences Education, 2023 – Cited by: 3

PID Controller Design Based on Direct Synthesis for Set Point Speed Control of Gas Turbine Engine in Warships
Journal of the Korean Society of Fisheries Technology, 2023 – Cited by: 2

Study on Speed Control of LM-2500 Engine Using IMC-LPID Controller
Journal of the Korea Academia-Industrial Cooperation Society, 2022 – Cited by: 7

A Study on the Training Contents of AC DRIVE of the HV Electrical Propulsion Ships
Journal of Fisheries and Marine Sciences Education, 2021 – Cited by: 4