Dennis Ocholla | Information Science | Research Excellence Award

Published on by Electrical Engineering

Prof. Dennis Ocholla | Information Science | Research Excellence Award

Senior Professor | Univerasity of Zululand | South Africa

Professor Dennis N. Ocholla is a distinguished Professor of Information Studies at the University of Zululand, specializing in Library and Information Science with expertise in information seeking, knowledge management, applied bibliometrics, ICT4D, and information ethics. He holds advanced degrees in library and information studies, forming the foundation of a prolific academic career marked by senior professorial appointments, departmental leadership, research mentorship, and international scholarly engagement. His research addresses LIS education, indigenous knowledge, research visibility, information ethics, and digital transformation, with an extensive record of high-impact publications that have shaped scholarship and policy in Africa and globally. His academic influence is evidenced by 4,371 citations, an h-index of 37, and an i10-index of 96. His contributions are further recognized through prestigious research awards, professional honors, editorial leadership of leading journals, and active membership in prominent national and international scholarly bodies.

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Featured Publications

Marginalized Knowledge: An Agenda for Indigenous Knowledge Development and Integration with Other Forms of Knowledge
D. N. Ocholla
The International Review of Information Ethics · Citations: 204

Information Seeking Behavior of the Informal Sector Entrepreneurs: The Uganda Experience
R. Ikoja-Odongo, D. N. Ocholla
Library & Information Science Research · Citations: 112

Lei Guan | Machine Learning | Research Excellence Award

Published on by Electrical Engineering

Mr. Lei Guan | Machine Learning | Research Excellence Award

Director | China Academy of Safety Science and Technology | China

Lei Guan is a Director and Professor at the Risk Monitoring and Early Warning Center, China Academy of Safety Science and Technology, with expertise in risk monitoring, early warning systems, artificial intelligence, and industrial safety engineering. He holds a Bachelor’s degree in Materials Science and Master’s and Doctoral degrees in Mechanical Engineering with specialization in precision instruments and safety-related systems. He has led major national and ministerial research programs, directed key laboratories and professional committees, supervised graduate researchers, and provided technical leadership for large-scale industrial and governmental safety initiatives. His research focuses on intelligent work safety systems, industrial internet applications, digital twins, data-driven risk modeling, and emergency management, with sustained contributions through peer-reviewed publications, patents, and standards development. His scholarly impact is reflected in 18 citations, an h-index of 3, and 13 published articles.

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Featured Publications

Numerical simulation of the double pits stress concentration in a curved casing inner surface
W. Yan, L. Guan, Y. Xu, J.G. Deng – Advances in Mechanical Engineering, 9(1) (3 citations)

Safety monitoring and management system for fluid catalytic cracking (FCC) process
L. Fang, Z. Wu, L. Wei, R. Kang, L. Guan – International Conference on Information and Automation (3 citations)

Study on SVM-based Flame Recognition and Fire Warning for Cotton and Linen Warehouses
X. Zhao, S. Hao, L. Guan, Y. Wang, Q. Zhao, D. Lv – IEEE Conference on Advances in Electrical Engineering (2 citations)

Industrial Internet of Things (IIoT) Identity Resolution Techniques: A Review
C. Dai, H. Li, L. Guan, M. Chi – IEEE BigDataSecurity (1 citation)

Soodeh Hosseini | Machine Learning | Research Excellence Award

Published on by Electrical Engineering

Prof. Dr. Soodeh Hosseini | Machine Learning | Research Excellence Award

Corresponding Author | Shahid Bahonar University of Kerman | Iran

Dr. Soodeh Hosseini is an Associate Professor of Computer Science at the Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, specializing in artificial intelligence, machine learning, cybersecurity, and complex networks. She holds a bachelor’s degree in Computer Science, a master’s degree in Computer Engineering with a specialization in software, and a doctorate in Computer Engineering with a focus on software engineering. Her professional experience encompasses extensive academic teaching, supervision of advanced research projects, leadership as head of academic and research units, and active involvement in technology growth centers and science parks, alongside advisory and executive roles in scholarly and innovation-driven initiatives. Her scholarly impact is evidenced by 1,426 citations, an h-index of 23, and an i10-index of 34.

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Featured Publications

A hybrid sine–cosine and golden ratio optimization algorithm for feature selection in intrusion detection systems
M. Maazalahi, S. Hosseini – International Journal of System Assurance Engineering and Management

Analytics and measuring the vulnerability of communities for complex network security
M. Jouyban, S. Hosseini – International Journal of Data Science and Analytics

An Improved Binary Slime Mold Algorithm for Intrusion Detection Systems
M. Khorashadizade, S. Hosseini, M. Jouyban – Concurrency and Computation: Practice and Experience

Aseel Basheer | Machine Learning | Excellence in Research Award

Published on by Electrical Engineering

Dr. Aseel Basheer | Machine Learning | Excellence in Research Award

Postdoc | University of Oklahoma | United States

Aseel Basheer is a Graduate Research Assistant and Ph.D. candidate in Computer Science at the University of Oklahoma, with expertise in machine learning, data science, and large-scale data analytics. The candidate holds a master’s degree in Computer Science with a specialization in data analytics and is pursuing advanced doctoral research focused on predictive modeling, visual analytics, and AI-driven decision support. Professionally, Aseel has contributed to interdisciplinary research projects in public health intelligence and pandemic surveillance, developing AI/ML models, data-driven forecasting systems, and visualization platforms, while also demonstrating academic leadership through teaching, mentoring, and curriculum support in higher education. The candidate’s professional profile is further strengthened by recognized certifications in data analytics, machine learning, healthcare data science, and research rigor, alongside active engagement in scholarly communities. The scholarly impact is reflected through 22 citations, an h-index of 2, and an i10-index of 1.

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