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

Posted on by sciencefather

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.

 

Abdulkareem Alzahrani | Computational Intelligence | Best Researcher Award

Posted on by sciencefather

Assoc. Prof. Dr. Abdulkareem Alzahrani | Computational Intelligence | Best Researcher Award

Associate Professor of Artificial Intelligence at CS Dept. and Vice-Dean for Postgraduate Studies, Research, Innovation, and Quality, Saudi Arabia

🎓 Dr. Abdulkareem Aodah Alzahrani is an Associate Professor in Computer Science specializing in Artificial Intelligence at Al-Baha University, Saudi Arabia. He currently serves as the Vice Dean for Postgraduate Studies, Research, Innovation, and Quality at the Faculty of Computing and Information. With a career spanning over 16 years, Dr. Alzahrani has held several leadership roles, including Head of the Computer Information Systems and IT Departments. He is a founding member of multiple research and innovation committees, contributing significantly to the advancement of AI and machine learning applications. 🌟

Publication Profile

Google Scholar

Education

📚 Dr. Alzahrani earned his Ph.D. in Computer Science from the University of Essex, UK, in 2017, specializing in Artificial Intelligence. He also holds an MSc in Advanced Web Engineering from the University of Essex (2011) and a BEd in Computer Science from Abha Teacher College, Saudi Arabia (2007). His academic journey reflects his passion for advancing AI and computational research. 🌍

Experience

💼 Dr. Alzahrani has held pivotal roles at Al-Baha University, including Vice Dean (2023–present), Member of the Standing Committee for Scientific Research and Innovation (2024–present), and Head of the Computer Information Systems Department (2020–2023). He was instrumental in establishing a cooperative computer research lab between Al-Baha University and the Research, Development, and Innovation Authority. With extensive teaching and administrative experience, he has significantly contributed to enhancing the university’s academic and research environment. 🌐

Awards and Honors

🏅 Dr. Alzahrani has received the Reward for Excellence four times during his Ph.D. studies, awarded by the Saudi Arabian Cultural Bureau in London. Additionally, he was honored with the Abha Award of Excellence in IT in 2006, recognizing his contributions to the field. His accolades underscore his commitment to academic and technological excellence. 🏆

Research Focus

🔍 Dr. Alzahrani’s research focuses on Artificial Intelligence, Machine Learning, and their applications in healthcare, tourism, and security. His work includes developing robust machine learning models, sentiment analysis for multimedia, and AI-driven solutions for real-world challenges. He is particularly interested in hybrid frameworks and innovative methodologies for enhancing computational efficiency. 🤖

Conclusion

🌟 Dr. Abdulkareem Aodah Alzahrani is a distinguished academic and researcher dedicated to advancing AI and computing. His extensive experience, impactful research, and leadership roles make him a prominent figure in Saudi Arabia’s academic and technological landscape. 🚀

Publications

AI-Driven Innovations in Tourism: Developing a Hybrid Framework for the Saudi Tourism Sector (2025) – AI, 6.1, DOI:10.3390/ai6010007.
Cited by: 7.

A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Based on Hassanat Distance Metric (2024) – DOI:10.21203/rs.3.rs-4492948/v1.
Cited by: 10.

A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Using a Non-Convex Distance Metric (2024) – Mathematics, 12.22, DOI:10.3390/math12223623.
Cited by: 15.

Advanced CKD Detection through Optimized Metaheuristic Modeling in Healthcare Informatics (2024) – Scientific Reports, 14.1, DOI:10.1038/s41598-024-63292-5.
Cited by: 20.

DeepSVDNet: A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images (2024) – Computer Systems Science and Engineering, 48.2, DOI:10.32604/csse.2023.039672.
Cited by: 25.

Improved Support Vector Machine Based on CNN-SVD for Vision-Threatening Diabetic Retinopathy Detection and Classification (2024) – PLOS ONE, 19.1, DOI:10.1371/journal.pone.0295951.
Cited by: 18.

Aspect-Based Sentiment Analysis for Social Multimedia: A Hybrid Computational Framework (2023) – Computer Systems Science and Engineering, 46.2, DOI:10.32604/csse.2023.035149.
Cited by: 30.

Harnessing Machine Learning for Arabic COVID-19 Omicron News Classification: A Comparative Study (2023) – International Journal of Advances in Soft Computing & Its Applications, 15.2.

A Comparative Study for SDN Security Based on Machine Learning (2023) – International Journal of Interactive Mobile Technologies, 17.11, DOI:10.3991/ijim.v17i11.39065.
Cited by: 12.

Cloud Intrusion Detection System Based on SVM  (2023) – International Journal of Interactive Mobile Technologies, 17.11, DOI:10.3991/ijim.v17i11.39063.
Cited by: 14.

 

Gia SIRBILADZE | Fuzyt Dynamic Systems | Best Researcher Award

Posted on by sciencefather

Prof. Gia SIRBILADZE | Fuzyt Dynamic Systems | Best Researcher Award

Prof., Ivane Javakhishvili Tbilisi State University (Georgia), Georgia

🌟 Professor Gia Sirbiladze is a prominent figure in intelligent simulation modeling and decision-making in uncertain environments, with over 40 years of teaching and research experience. Currently, he serves as a Professor of Applied Informatics at the Department of Computer Sciences at Iv. Javakhishvili Tbilisi State University (JTSU) in Georgia. 📘 As an author and editor of more than 150 papers and two monographs, he has made significant contributions to expert knowledge engineering and fuzzy technologies in decision-support systems. Additionally, Professor Sirbiladze is a member of several international computer science societies, including IEEE, WSEAS, IFSR, and MCDM, and sits on the editorial boards of multiple international journals. 🌐

Publication Profile

ORCID

Education

🎓 Professor Sirbiladze holds a deep-rooted academic background in computer science and applied informatics, specializing in systems science, fuzzy technologies, and decision-making.

Experience

📚 With over four decades of experience at JTSU, Professor Sirbiladze has shaped research and teaching in applied informatics and computer sciences, especially within intelligent modeling and complex decision-making problems.

Research Interests

🔍 His research interests span several advanced areas of computer science, including systems science and engineering, fuzzy technologies, decision-support systems, control and filtration of extreme dynamic systems, and fuzzy discrete optimization in management.

Awards

🏅 Professor Sirbiladze has been recognized for his exceptional contributions to intelligent systems and decision-making, earning honors in his field and serving on editorial boards of international journals.

Publications

“Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities”
Published in: Axioms – 2024-11-09
DOI: 10.3390/axioms13110776

“Associated Probabilities in Insufficient Expert Data Analysis”
Published in: Mathematics – 2024-02-07
DOI: 10.3390/math12040518

“Possibilistic Simulation-Based Interactive Fuzzy MAGDM Under Discrimination q-Rung Picture Linguistic Information: Application in Educational Programs Efficiency Evaluation”
Published in: Engineering Applications of Artificial Intelligence – 2023-08
DOI: 10.1016/j.engappai.2023.106278

“Associated Probabilities Aggregations in Multistage Investment Decision-Making”
Published in: Kybernetes – 2023-03-24
DOI: 10.1108/K-09-2021-0908

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Posted on by sciencefather

Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.