Assist. Prof. Dr. Manolis Adamakis | Technologies | Best Researcher Award

Published on by Computer Scientists Awards

Assist. Prof. Dr. Manolis Adamakis | Technologies | Best Researcher Award

Assist. Prof. Dr. Manolis Adamakis | National and Kapodistrian University of Athens | Greece

Dr. Manolis Adamakis is an accomplished Assistant Professor and Researcher specializing in Physical Education, Physical Activity, Health, and Wellbeing. His scholarly work bridges theoretical and experimental perspectives, with strong expertise in new technologies applied to physical activity and in-depth data analysis using both quantitative and qualitative approaches. His research explores the intersections of physical activity, education, mental health, and digital innovation, contributing significantly to European physical education and public health. Dr. Adamakis is recognized for his leadership in designing, validating, and implementing innovative instruments and methodologies that enhance educational practice and research quality. A highly cited researcher, he has authored 32 documents indexed in Scopus, accumulating 440 citations from 412 sources, and holds an h-index of 10. His Google Scholar record reflects 1,025 citations, an h-index of 16, and an i10-index of 22, highlighting his global academic impact. His collaborative work with international teams has advanced knowledge in teacher education, child motor development, and mental well-being through physical activity. Dr. Adamakis’s commitment to interdisciplinary and evidence-based research underlines his contribution to shaping the future of physical education and health promotion.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications 

O’Brien, W., Adamakis, M., O’Brien, N., Onofre, M., Martins, J., & Dania, A. (2020). Implications for European physical education teacher education during the COVID-19 pandemic: A cross-institutional SWOT analysis. European Journal of Teacher Education, 43(4), 503–522.

Lopes, L., Santos, R., Coelho-e-Silva, M., Draper, C., Mota, J., Jidovtseff, B., & Adamakis, M. (2021). A narrative review of motor competence in children and adolescents: What we know and what we need to find out. International Journal of Environmental Research and Public Health, 18(1), 18.

Adamakis, M., & Zounhia, K. (2016). The impact of occupational socialization on physical education pre-service teachers’ beliefs about four important curricular outcomes: A cross-sectional study. European Physical Education Review, 22(3), 279–297.

Rocliffe, P., Adamakis, M., O’Keeffe, B. T., Walsh, L., & Bannon, A. (2024). The impact of school physical activity provision on adolescent mental health and well-being: A systematic literature review. Adolescent Research Review, 9(2), 339–364.

Wälti, M., Sallen, J., Adamakis, M., Ennigkeit, F., & Gerlach, E. (2022). Basic motor competencies of 6-to-8-year-old primary school children in 10 European countries: A cross-sectional study. Frontiers in Psychology, 13, 804753.*

Prof. Dr. Cesar Hernando Valencia Niño | Evolutionary Computation | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Dr. Cesar Hernando Valencia Niño | Evolutionary Computation | Best Researcher Award

Prof. Dr. Cesar Hernando Valencia Niño | Director of Master on Data Analytics and Intelligent Systems | Santo Tomas University Bucaramanga | Colombia

Cesar Hernando Valencia Niño is a distinguished researcher in artificial intelligence, robotics, mechatronics, and intelligent control systems. His work integrates machine learning algorithms with mechanical and electrical engineering to develop predictive, inferential, and adaptive systems applied to robotics, biomedical devices, industrial automation, and human–machine interaction. As leader of a Category A research group, he has contributed significantly to interdisciplinary applications of AI in areas such as prosthetics, echo state networks, autonomous systems, and biomedical forecasting. His portfolio includes contributions to the advancement of industrial robotics, machine design, neuroevolutionary computation, magnetorheological systems, and control architectures for UAVs and prosthetics. With active participation in 25 research and innovation projects, he has produced 17 peer-reviewed journal articles, 5 book chapters, 12 industrial prototypes, 7 documented innovations, and 5 patents. He is also a recognized reviewer of top-tier indexed journals and has directed theses across undergraduate to doctoral levels. Valencia Niño has presented his work in more than 30 knowledge dissemination events, demonstrating strong engagement in academic and scientific communities. His citation impact reflects growing international recognition: Scopus reports 45 citations from 44 documents with 17 indexed publications and an h-index of 4, while Google Scholar attributes 96 citations, an h-index of 6, and an i10-index of 2. His research continues to bridge artificial intelligence with engineering solutions for complex, real-world challenges, emphasizing innovation, automation, and intelligent system design.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

  • Valencia, C. H., Vellasco, M. M. B. R., & Figueiredo, K. (2023). Echo State Networks: Novel reservoir selection and hyperparameter optimization model for time series forecasting. Neurocomputing, 545, 126317.

  • Valencia Niño, C. H. (2011). Modelo de optimización en la gestión de inventarios mediante algoritmos genéticos. ITECKNE: Innovación e Investigación en Ingeniería, 8(2), 156–162.

  • Valencia, C. H., Vellasco, M. M. B. R., & Figueiredo, K. T. (2014). Trajectory tracking control using echo state networks for the CoroBot’s arm. In Robot Intelligence Technology and Applications 2.

  • Valencia, C. H., Vellasco, M., Tanscheit, R., & Figueiredo, K. T. (2015). Magnetorheological damper control in a leg prosthesis mechanical. In Robot Intelligence Technology and Applications 3.

  • Valencia Niño, C. H., & Dutra, M. S. (2010). Estado del arte de los vehículos autónomos sumergibles alimentados por energía solar. ITECKNE, 7(1), 46–53.

 

Cha Joowon | Artificial Intelligence | Best Researcher Award

Published on by Computer Scientists Awards

Mr. Cha Joowon | Artificial Intelligence | Best Researcher Award

Korea Atomic Energy Research Institute | South Korea

Mr. Cha Joowon is a dedicated researcher in the field of artificial intelligence with a particular focus on its application to nuclear energy systems. He is currently part of the Applied Artificial Intelligence Section at the Korea Atomic Energy Research Institute in Daejeon, South Korea, where he contributes to advancing AI-driven solutions for safe and efficient reactor operations. His academic and research journey reflects a strong commitment to combining computer science with nuclear engineering challenges, working on innovative methods to improve decision-making and system reliability within complex technological environments.

Publication Profile

Scopus

Education Background

Mr. Cha Joowon began his academic path in computer engineering at Korea University of Technology and Education, where he developed a strong foundation in computational methods, algorithms, and systems design. After completing his undergraduate studies, he advanced his pursuit of specialized knowledge by enrolling in the integrated M.S.-Ph.D. program at the University of Science and Technology in Daejeon. His focus within this program is artificial intelligence, where he combines theoretical learning with practical applications in the nuclear energy domain, emphasizing innovation in both academic and applied research contexts.

Professional Experience

Building on his academic background, Mr. Cha Joowon joined the Korea Atomic Energy Research Institute in Daejeon, where he works within the Applied Artificial Intelligence Section. His role centers on exploring how artificial intelligence can enhance reactor safety, operational efficiency, and predictive maintenance in nuclear facilities. His current research integrates advanced machine learning and large language models with engineering systems, demonstrating his ability to bridge computational intelligence with real-world industrial applications. This combination of skills reflects both his technical expertise and his ambition to contribute meaningful solutions to complex engineering challenges.

Awards and Honors

While Mr. Cha Joowon is still early in his professional journey, his commitment to excellence and research potential is evident through his academic trajectory and institutional affiliations. His enrollment in a highly competitive integrated doctoral program at the University of Science and Technology highlights his recognition as a promising scholar. Additionally, his affiliation with the Korea Atomic Energy Research Institute places him in an environment of high-level scientific contributions, offering him opportunities to showcase his growing expertise. His ongoing projects signal the potential for future recognition through awards and professional honors.

Research Focus

Mr. Cha Joowon’s research is centered on applying artificial intelligence to nuclear engineering, with particular attention to developing intelligent systems for reactor operation support. His focus includes integrating large language models and advanced computational techniques to enhance operator decision-making, predictive diagnostics, and system optimization. By combining AI innovation with the unique requirements of nuclear technologies, his research aims to provide reliable and practical solutions for the safe and effective operation of reactors. This interdisciplinary approach reflects his dedication to bridging artificial intelligence with one of the most critical areas of energy research.

Publication Notes

  • Large language model agent for nuclear reactor operation assistance
    Published Year: 2025

Conclusion

In summary, Mr. Cha Joowon represents a new generation of researchers working at the intersection of artificial intelligence and nuclear engineering. His academic foundation in computer engineering, advanced studies in AI, and practical contributions at the Korea Atomic Energy Research Institute mark him as an emerging talent with strong potential to shape the future of intelligent nuclear systems. As he continues to publish and contribute to research, his work is expected to influence both academic communities and industrial applications, solidifying his role as a researcher dedicated to innovation and safety in energy technologies.

Assist. Prof. Dr. Joaquim Casaca | Artificial Intelligence | Best Researcher Award

Published on by Computer Scientists Awards

Assist. Prof. Dr. Joaquim Casaca | Artificial Intelligence | Best Researcher Award

Prof, IADE, European University, Portugal

Joaquim António A. Casaca is an accomplished academic and professional in management, specializing in information security and marketing. He currently serves as an Assistant Professor at IADE, European University, Lisbon. Known for his expertise in management and economics, Joaquim has contributed extensively to research in areas such as entrepreneurial competence, marketing, and information security.

Publication Profile

Scopus

ORCID

🎓 Education Background

Joaquim Casaca holds a PhD in Management (2010) from Universidade Lusíada de Lisboa, with a thesis focusing on information security management in Portuguese SMEs. He earned a Master’s in Management (1999) and an MBA (1997) from ISEG – Lisbon School of Economics and Management, University of Lisbon. Additionally, he completed a Postgraduate degree in Information Sciences and Technologies for Organizations (1996) from ISEG, and holds a BSc in Economics (1982) from the same institution.

💼 Professional Experience

Since 2010, Joaquim has been an Assistant Professor at IADE, European University (Lisbon). Previously, he held academic roles at the University of Lisbon and Lusófona University, and financial positions in notable companies such as PT Multimédia, Portugal Telecom, and Companhia Portuguesa Rádio Marconi. His broad experience spans academia, finance, and management consultancy.

🏆 Awards and Honors

Joaquim received the Banco Espírito Santo Award in 1999 at ISEG for his outstanding Master’s thesis. This recognition highlights his early excellence and research capability in management.

🔍 Research Focus

His research interests center on management, information security, entrepreneurial competence, and marketing. Recent work includes studies on game-based learning’s effect on entrepreneurial skills and the role of neuroscience in economics and marketing. Joaquim’s interdisciplinary approach integrates management theory with emerging technologies and consumer behavior.

🔚 Conclusion

With a strong academic foundation and a versatile professional background, Joaquim A. Casaca is a respected figure in management and information security education. His ongoing contributions advance the understanding of how technology and management intersect in organizational contexts.

📚 Top Publications

  • The effect of game-based learning on the development of entrepreneurial competence among higher education students
    Daniel, A. D., Negre, Y., Casaca, J. A., Patricio, R., & Tsvetcoff, R. (2024). Education + Training.
    DOI: 10.1108/ET-10-2023-0448 — Cited by 3 articles

  • Neuroscience Applied to Economics and Marketing: A bibliometric Review of the Literature
    Casaca, J. A. (2024). International Journal of Business Innovation and Research.
    DOI: 10.1504/ijbir.2024.10066189

  • The determinants of non-consumption of disposable plastic: application of an extended theory of planned behaviour
    Casaca, J. A. (2024). International Journal of Business Environment.
    DOI: 10.1504/IJBE.2024.135693

  • Relational Marketing and Customer Satisfaction: A Systematic Literature Review
    Casaca, J. A. (2023). Estudios Gerenciales.
    DOI: 10.18046/j.estger.2023.169.6218

  • Relationship Marketing and Customer Retention – A Systematic Literature Review
    Casaca, J. A. (2023). Studies in Business and Economics.
    DOI: 10.2478/sbe-2023-0044

 

Prof. Tao Ye | AI Accelerator | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Tao Ye | AI Accelerator | Best Researcher Award

Prof, The Chinese University of Hong Kong, China

Dr. Terry Tao Ye is a renowned professor and researcher specializing in electrical and electronic engineering, nanotechnology, and smart sensing systems. Currently affiliated with the School of Science and Engineering at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), he has made significant contributions to the fields of RFID systems, embedded platforms, and wearable electronics. With a rich career spanning academia and industry, Dr. Ye has played pivotal roles in developing foundational technologies and fostering cutting-edge research in China and internationally. 🌏🔬

Publication Profile

Summary of Suitability for Best Researcher Award – Prof. Tao Ye

Dr. Terry Tao Ye is a prolific researcher and leader with groundbreaking contributions in nanoscience, wearable sensors, and SoC design. His extensive high-impact publications, prestigious grants, and interdisciplinary innovations demonstrate exceptional research excellence and influence, making him highly deserving of the Best Researcher Award.

🎓 Education Background

Dr. Ye holds a Ph.D. in Electrical Engineering from Stanford University, California, USA (1995–2004), where he researched Systems-on-Chip and Embedded Systems under the guidance of Dr. Giovanni De Micheli. He earned his B.Eng. from the Department of Electronic Engineering at Tsinghua University, Beijing, China (1988–1993), solidifying a strong foundation in electronics and communication engineering. 📘🎓

💼 Professional Experience

Dr. Ye has held multiple esteemed academic and industrial positions. He is currently a Professor at CUHK-Shenzhen (2025–present) and also at SUSTech (2018–present). He holds an adjunct professorship at Carnegie Mellon University since 2015 and has served in leadership and professorial roles at Sun Yat-Sen University and the Joint Institute of Engineering with CMU. His industry experience includes significant roles at Impinj Inc. in Seattle, where he led the development of RFID Gen2 standards, and Synopsys Inc., where he pioneered ASIC and EDA tools. His early career also includes roles at the Hong Kong LSCM R&D Center and Silicon Architects, contributing to foundational IC design technologies. 🧑‍🏫💻📡

🏅 Awards and Honors

Dr. Ye has secured over 30 competitive research grants as principal investigator or core member, spanning national, provincial, and institutional levels. Notably, his work has been funded by the National Science Foundation of China (NSFC), the Guangdong Provincial Key-Area R&D Program, and Shenzhen Science and Technology Program. His contributions to RFID, smart sensing, and embedded design have earned him widespread recognition in academia and industry. 🏆📑

🔬 Research Focus

Dr. Ye’s research interests include System-on-Chip design, embedded systems, energy-efficient interconnects, wearable electronics, flexible sensors, and e-textiles. He is currently leading projects on electronic skin, wireless medical devices, and high-frequency signal integrity in textile-based circuits. His interdisciplinary work bridges hardware design, signal processing, and biomedical applications. 🧠⚙️📲

🔚 Conclusion

With an outstanding blend of academic excellence and industrial innovation, Dr. Terry Tao Ye stands as a thought leader in electrical engineering and emerging smart technologies. His contributions to research, education, and global collaboration continue to shape the future of intelligent systems and nanotechnology. 🌟📡🔋

📚 Top Publications with Details

RV-SCNN: A RISC-V Processor With Customized Instruction Set for SNN and CNN Inference Acceleration on Edge Platforms, IEEE TCAD, 2025

Cited by: 12

Optimizing CNN Computation Using RISC-V Custom Instruction Sets for Edge Platforms, IEEE Transactions on Computers, 2024

Cited by: 2

Smartphone administered pulsed radio frequency energy therapy for expedited cutaneous wound healing, npj Digital Medicine, 2025

Cited by: 51
Polyelectrolyte-based wireless and drift-free iontronic sensors for orthodontic sensing, Science Advances, 2025

Cited by: 4

Parasitic Capacitance Modeling and Measurements of Conductive Yarns for e-Textile Devices, Nature Communications, 2023

Cited by: 8

Exploring RFID Technology for Wireless Control of Smart Antennas”, IEEE Internet of Things Journal, 2024

Cited by: 24

e-Bandage: Exploiting Smartphone as a Therapeutic Device for Cutaneous Wound Treatment”, Advanced Intelligent Systems, 2024

Cited by: 39

Prof. Daniela BURUIANA | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Daniela BURUIANA | Computer Science | Best Researcher Award

Vice-rector, Dunarea de Jos University of Galati, Romania

Prof. Dr. Buruiana Daniela Laura is a prominent academic leader and innovative researcher currently serving as the Vice-Rector at Dunarea de Jos University of Galati . With over two decades of experience in industrial and materials engineering, she holds two habilitations—one in Industrial Engineering and another in Materials Engineering. She leads multiple interdisciplinary initiatives and is the Head of the Department of Materials and Environmental Engineering and the Interdisciplinary Research Centre in Eco-Nano Technology and Advanced Materials (CC-ITI). Her prolific contributions include over 40 ISI-indexed publications, six patents, and leadership in 18 national and international research projects, establishing her as a vital contributor to the advancement of eco-innovative and sustainable technologies 🌱.

Publication Profile

🎓 Education Background

Prof. Buruiana has completed her doctoral studies in Engineering, specializing in the domains of materials and industrial engineering 🏗️. She later earned two habilitations—significant academic milestones that qualify her as a doctoral advisor and research leader in both Industrial Engineering and Materials Engineering. Her academic formation has been deeply rooted in sustainability, biomaterials, and the valorization of industrial and biomedical waste, reflecting her interdisciplinary educational trajectory.

💼 Professional Experience

Currently serving as Vice-Rector, she has held several pivotal academic and research leadership roles, including Head of the Department of Materials and Environmental Engineering since 2020 and Director of CC-ITI. She has directed over 10 competitive research projects, collaborated with global institutions like the University of Burgos (Spain), Universidade de Estado do Rio de Janeiro (Brazil), and The University of Sheffield (UK) 🌍. Her consultancy experience spans five industrial projects, further bridging academia with industry applications. With 14 books published, she also demonstrates a strong commitment to education and scientific communication 📚.

🏅 Awards and Honors

Prof. Buruiana has been honored with 17 awards at conferences and scientific projects, recognizing her innovative research contributions 🏆. She is an active member of the Romanian Society of Biomaterials, the National Register of Teaching Staff Evaluators, and the Romanian Environmental Association. Furthermore, she serves on the Certification Commission for Environmental Study Elaborators and contributes to national education standards through ARACIS. Her professional stature continues to rise due to her impactful research and dedication to excellence.

🔍 Research Focus

Her main research areas include materials engineering, environmental protection, biomaterials, circular economy, and the valorization of waste 🌐. She has significantly contributed to the understanding of eco-friendly nanomaterials and corrosion resistance in harsh environments, while also exploring biomaterial applications for sustainability and CO₂ sequestration. Under her guidance, many young researchers are being trained to implement advanced materials and environmental solutions at an industrial level 🧪.

🧾 Conclusion

Prof. Dr. Daniela Laura Buruiana is a distinguished scholar whose groundbreaking research in industrial and environmental engineering continues to influence scientific innovation and sustainable development worldwide 🌟. Her dynamic leadership, dedication to education, and international collaborations make her a deserving candidate for the Best Researcher Award 🥇.

📚 Top Notable Publications

Evaluating the Impact of Artificial Saliva Formulations on Stainless Steel Integrity (2025) – Applied Sciences
📈 Cited by: 2 articles (Crossref)

Assessment of the Effectiveness of Protective Coatings in Preventing Steel Corrosion in the Marine Environment (2025) – Polymers
📈 Cited by: 3 articles (Crossref)

Advanced Recycling of Modified EDPM Rubber in Bituminous Asphalt Paving (2024) – Buildings
📈 Cited by: 4 articles (Web of Science)

Corrosion Tendency of S235 Steel in 3.5% NaCl Solution and Drinking Water During Six Months of Exposure (2024) – Materials
📈 Cited by: 1 article (Crossref)

Detection of Reed Using CNN Method and Analysis of the Dry Reed (Phragmites Australis) for a Sustainable Lake Area (2023) – Plant Methods
📈 Cited by: 6 articles (Scopus)

Seyed Abolfazl Aghili | Deep Learning | Best Review Paper Award

Published on by Computer Scientists Awards

Dr. Seyed Abolfazl Aghili | Deep Learning | Best Review Paper Award

lecturer, iran university of science and technology, Iran

Seyed Abolfazl Aghili is a passionate civil engineer with a strong focus on construction engineering and management. With a Ph.D. in Civil Engineering from the prestigious Iran University of Science and Technology (IUST), he specializes in using artificial intelligence for enhancing the resilience of HVAC systems in hospitals. His research integrates cutting-edge technologies such as machine learning and deep learning to optimize building systems and improve decision-making in construction projects. Seyed’s dedication to his field has earned him a reputation as a driven academic and professional in the civil engineering community. 🏗️🤖

Publication Profile

ORCID

Education Background

Seyed Abolfazl Aghili completed his Ph.D. in Civil Engineering with a specialization in Construction Engineering and Management from Iran University of Science and Technology (IUST) between 2019 and 2024. His doctoral thesis focused on developing a framework to assess the long-term resilience of hospital air conditioning systems using artificial intelligence. Prior to that, he earned his M.Sc. in Civil Engineering with a focus on Construction Engineering and Management at IUST, where he investigated employee selection methods in construction firms. He also holds a B.Sc. in Civil Engineering from Isfahan University of Technology (IUT). 🎓📚

Professional Experience

Seyed Abolfazl Aghili has extensive experience in both academic research and practical applications of civil engineering, particularly in construction management. He has worked on various projects involving energy management, risk management, and resilience within the construction industry. His academic journey has seen him contribute significantly to the research community, particularly in the areas of AI in construction systems and HVAC performance. Furthermore, he has been an integral part of various conferences and publications, sharing his insights on improving construction management processes through technology. 💼🏢

Awards and Honors

Seyed Abolfazl Aghili has earned several prestigious awards throughout his academic journey. He was ranked 5th among 2200 participants in the Nationwide University Entrance Exam for the Ph.D. program in Iran in 2019. Additionally, he ranked 2nd among all construction management students at Iran University of Science and Technology during his M.Sc. studies. He was also ranked in the top 1% (220th out of 32,663) in the Nationwide University Entrance Exam for the M.Sc. program in Iran in 2013. 🏆🥇

Research Focus

Seyed’s primary research interests lie in the application of machine learning and deep learning techniques in construction engineering. His work focuses on enhancing the resilience of building systems, especially HVAC systems in healthcare settings. He also explores risk management, sustainability, lean construction, and decision-making systems for project managers. His interdisciplinary research combines civil engineering with advanced AI methodologies, driving innovations in construction management and systems optimization. 🔍💡

Conclusion

Seyed Abolfazl Aghili’s academic and professional journey reflects his commitment to advancing civil engineering through innovative solutions. His focus on integrating artificial intelligence into construction systems is helping to create smarter, more sustainable, and resilient built environments. Through his work, he continues to contribute valuable insights to both the academic world and the practical sector of construction engineering. 🌍🔧

Publications Top Notes

Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review. Journal of Buildings, 15.7 (2025).

Data-driven approach to fault detection for hospital HVAC system. Journals of Smart and Sustainable Built Environment, ahead-of-print (2024).

Feasibility Study of Using BIM in Construction Site Decision Making in Iran. International Conference on Civil Engineering, Architecture and Urban Infrastructure, July 2015.

Review of digital imaging technology in safety management in the construction industry. 1st National Conference on Development of Civil Engineering, Architecture, Electricity and Mechanical in Iran (December, 2014).

The role of insurance companies in managing the crisis after earthquake. 1st National Congress of Engineering, Construction, and Evaluation of Development Projects, May 2013.

The need for a new approach to pre-crisis and post-crisis management of earthquake. 1st National Conference on Seismology and Earthquake, February 2013.

Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

Professor, National Ilan University/EE, Taiwan

Dr. Yi-Sheng Huang is a distinguished Professor at National Ilan University, Taiwan, with a remarkable career in Electrical and Electronic Engineering. Holding a Ph.D. from National Taiwan University of Science and Technology (NTUST), he has significantly contributed to Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). Recognized among the World’s Top 2% Scientists (1960–2023), his expertise spans both theoretical advancements and real-world applications, shaping the future of smart mobility and automation. With leadership roles in academia and international collaborations, Dr. Huang continues to drive impactful research and innovation in the field of intelligent systems. 🚀

Publication Profile

📚 Academic Background

Dr. Yi-Sheng Huang earned his Ph.D. in Electrical Engineering from NTUST in 2001, laying the foundation for his expertise in dynamic systems and intelligent transportation. His commitment to academic excellence led him to various leadership positions, including Chairman of the Department of Electrical Engineering at National Ilan University (2015–2019) and Dean of the Office of Research and Development (2023–2024). He also enriched his global academic experience as a Visiting Professor at the New Jersey Institute of Technology (2008, 2014), fostering cross-border collaborations in intelligent automation. 🎓

🏢 Professional Experience

With over two decades of academic and research contributions, Dr. Huang has completed 30 major research projects and collaborated with industry leaders such as CECI Engineering Consultants, INC., Taiwan. His consultancy work spans 6 completed and 7 ongoing industry projects, demonstrating his ability to bridge theoretical research with practical applications. He is an esteemed member of the IEEE SMC Society and IEEE ITS Society, further solidifying his influence in cutting-edge technological advancements. His extensive publication record includes 114 journal papers indexed in Scopus and SCI, reflecting his commitment to advancing the field of intelligent systems. ⚡

🏆 Awards and Honors

Dr. Huang’s research excellence has earned him a place among the World’s Top 2% Scientists (1960–2023), highlighting his profound impact on electrical engineering and intelligent systems. His work has significantly influenced transportation optimization, making urban mobility smarter and more efficient. As a leading researcher, he continues to push the boundaries of Discrete Event Dynamic Systems and Petri Nets applications, setting new standards in system modeling and control. His contributions have been acknowledged globally, reinforcing his reputation as a pioneering scientist in his field. 🏅

🔬 Research Focus

Dr. Huang’s research revolves around Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). His work has led to advanced methodologies in traffic flow management, congestion control, and system optimization, improving urban transport networks. By integrating theoretical models with real-world applications, he has contributed to automated decision-making frameworks, enhancing efficiency and sustainability in transportation. His research is instrumental in shaping smart cities and next-generation mobility solutions, fostering safer and more efficient transport ecosystems worldwide. 🚦

🔍 Conclusion

Dr. Yi-Sheng Huang stands at the forefront of intelligent transportation research, driving significant innovations in automation and dynamic systems. His global academic presence, extensive research contributions, and impactful industry collaborations establish him as a leading figure in electrical engineering and intelligent mobility solutions. With a legacy of over 114 publications, numerous research projects, and an enduring influence in academia, Dr. Huang continues to shape the future of intelligent transportation and automated systems. 🌍🚀

📝 Top Publications

A Petri net-based model for real-time traffic control in urban networks.

Optimization of discrete event systems using hybrid Petri nets.

Modeling and performance analysis of ITS using dynamic Petri nets.

Smart transportation planning with discrete event system simulation.

Enhancing automated transport systems using intelligent Petri nets.

 

Zeshan Khan | Artificial Intelligence| Best Researcher Award

Published on by Computer Scientists Awards

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] ⭐🔍

Mrs. Edna Rocio Bernal Monroy | Machine Learning | Best Researcher Award

Published on by Computer Scientists Awards

Mrs. Edna Rocio Bernal Monroy | Machine Learning | Best Researcher Award

UNAD, Colombia

Dr. Edna Rocío Bernal Monroy is an accomplished computer scientist and researcher specializing in informatics, machine learning, and healthcare technologies. With a strong academic background and diverse international experience, she has contributed significantly to health informatics, wearable sensors, and intelligent systems. Dr. Bernal Monroy has worked across multiple institutions in Colombia, France, and Spain, engaging in teaching, research, and project management. Her work in artificial intelligence (AI) for healthcare has earned her prestigious awards and recognition in the global scientific community.

Publication Profile

🎓 Education

Dr. Bernal Monroy holds a Ph.D. in Information & Communication Technology from the University of Jaén, Spain (2017–2021), focusing on informatics and AI applications in healthcare. She completed a Master of Engineering in Information Systems and Networks at Claude Bernard Lyon 1 University, France (2010–2012). Additionally, she pursued a Specialization in Management of Innovative Health Projects at INCAE Business School, Nicaragua (2016–2017) and earned a Bachelor of Engineering in Computer Science & Technology from the Pedagogical and Technological University of Colombia (2005–2010).

💼 Experience

Dr. Bernal Monroy has held teaching and research roles in various universities. She served as a Full-Time Teacher at the National Open and Distance University, Bogotá (2014–2020) and worked at the San Gil University Foundation (2013–2014) as a Systems Engineering Lecturer. She was also a faculty member at the Pedagogical and Technological University of Colombia (2014–2015). Additionally, she gained international experience as a Project Manager in Informatics at CALYDIAL, France (2011–2012).

🏆 Awards and Honors

Dr. Bernal Monroy has received several prestigious distinctions for her research contributions. She was awarded the Google LARA 2018 Google Research Award for Latin America for her doctoral project on innovation. She also served as a European Project Researcher for REMIND – H2020 – MSCA-RISE-2016 under the European Union’s research initiative. Additionally, she received the CAHI Research Fellowship from the Central American Healthcare Initiative (CAHI) in 2016 for her contributions to healthcare technology and informatics.

🔬 Research Focus

Dr. Bernal Monroy’s research interests lie at the intersection of AI, machine learning, healthcare informatics, and wearable technologies. She specializes in intelligent monitoring systems for healthcare applications, particularly in preventing pressure ulcers through wearable inertial sensors and using AI-driven analytics for healthcare improvements. Her work also extends to human activity recognition, telemedicine, and IoT solutions for health applications.

🏁 Conclusion

Dr. Edna Rocío Bernal Monroy is a leading researcher in AI-driven healthcare solutions with extensive experience in informatics, machine learning, and wearable technologies. Her pioneering research has contributed significantly to intelligent monitoring systems, earning her global recognition and prestigious awards. Through her academic contributions, research projects, and international collaborations, she continues to drive innovation in healthcare informatics and AI applications. 🚀

📚 Publications

Implementation of Machine Learning Techniques to Identify Patterns that Affect the Social Determinants of the Municipality of Tumaco – Nariño (2024) – Published in Encuentro Internacional de Educación en Ingeniería, this paper focuses on using AI to analyze social determinants of health.

Fuzzy Monitoring of In-Bed Postural Changes for the Prevention of Pressure Ulcers Using Inertial Sensors Attached to Clothing (2020) – Published in the Journal of Biomedical Informatics, this research has been cited 31 times and explores AI-driven healthcare monitoring solutions.

Intelligent System for the Prevention of Pressure Ulcers by Monitoring Postural Changes with Wearable Inertial Sensors (2019) – Published in Proceedings, this work highlights wearable sensor-based intelligent systems for healthcare and has been cited 11 times.

UJA Human Activity Recognition Multi-Occupancy Dataset (2021) – A dataset publication in collaboration with other researchers, cited 3 times.

Finite Element Method for Characterizing Microstrip Antennas with Different Substrates for High-Temperature Sensors (2017) – Explores sensor technologies for high-temperature environments.

Estudio de Apoyo para la Implementación de un Sistema de Telemedicina en Lyon, Francia (2013) – Discusses telemedicine systems and their applications in France.