Information and engineering sciences | Online ISSN 3068-0115

Editorial Structure

Editor-In-Chief 
Binbin Cui, Ph.D., C.P.A.
Royal Canadian Mint, Ottawa, ON, Canada
Dr. Binbin Cui is a seasoned finance and AI professional with over 20 years of experience in digital transformation, ERP systems, and data-driven innovation. Holding a PhD in Finance and CPA designation, Dr. Cui currently leads AI-powered financial planning and forecasting initiatives at the Royal Canadian Mint, integrating tools like Microsoft Dynamics 365. An editorial board member for several journals—including Journal of Artificial Intelligence General Science—Dr. Cui reviews manuscripts on algorithmic trading, fraud detection, and behavioral finance. His research explores AI applications in finance, supply chain management, and education, aiming to bridge academic theory with real-world digital innovation.
 
Associate Editors
 
Ahmed Obaid, Ph.D.
University of Kufa, Iraq
Dr. Ahmed J. Obaid is an Assistant Professor in the Department of Computer Science at the University of Kufa's Faculty of Computer Science and Mathematics in Iraq. He earned his Bachelor's degree in Computer Science, specializing in Information Systems, from the University of Anbar, and his Ph.D. in Computer Science from the University of Babylon. Dr. Obaid has authored 62 research articles, with 67 publications indexed in the Web of Science, and holds an H-index of 11, reflecting his significant contributions to the fields of computer science and mathematics.
 
Vishwanadham Mandala, Ph.D.
Senior Research Scientist, Indiana University, United States
Dr. Vishwanadham Mandala is a leading expert in big data, AI, machine learning, and data engineering, with significant contributions to data science and analytics. Currently serving as Enterprise Architect - Data at Cummins, he focuses on AI-driven solutions in automotive safety, manufacturing, and predictive maintenance. Dr. Mandala has authored numerous papers on topics like AI-based recommendation models, predictive failure analytics, and real-time engine failure prediction. His research also explores big data lake houses, data integration, and optimizing supply chains, making him a recognized figure in the field of advanced data analytics and artificial intelligence.
 
Noman Hossain, Ph.D.
Assistant Professor, Primeasia University, Bangladesh
 
Y. Zhang, Ph.D.
University of Pittsburgh, United States
Dr. Y. Zhang is a prominent researcher at the University of Pittsburgh, specializing in artificial intelligence, machine learning, and intelligent systems. With a verified academic profile and over a dozen influential publications in 2024–2025, Dr. Zhang's work spans credit card fraud detection, robotic manipulation, gastrointestinal imaging, and AI-generated text authentication. Notable contributions include applications of transformer models, ensemble learning (LightGBM, XGBoost), and deep reinforcement learning. Dr. Zhang has presented at major IEEE conferences and authored high-impact studies addressing real-world challenges in credit risk prediction, robotics, and content moderation. Their interdisciplinary approach continues to advance innovation in computational intelligence and automation.
 
Khondaker Abdullah Al Mamun, Ph.D.
United International University, Bangladesh; specializes in AI, biomedical signal processing, brain–computer interfacing, digital health applications. https://en.wikipedia.org/wiki/Khondaker_Abdullah_Al_Mamun
 
Ahmedul Kabir, Ph.D.
Institute of Information Technology, University of Dhaka, Bangladesh; NLP, Computer Vision, Data Mining, Software Analytics, ensemble machine learning https://www.dndlab.org/people
 
Mohammed Ashikur Rahman, Ph.D.
University of Liberal Arts Bangladesh; ML, predictive models, IoT, Explainable AI, publishes in IEEE/Scopus journals. https://www.ulab.edu.bd/faculty/mohammed-ashikur-rahman-phd
 
Syed Akhter Hossain, Ph.D.
Dean, Computer Science & Engineering, Daffodil International University, Bangladesh; long-standing contributions in NLP, AI education and research for Bangla language processing. https://en.wikipedia.org/wiki/Syed_Akhter_Hossain
 
Md. Habib Ullah Khan, Ph.D.
Bangladesh University of Engineering and Technology (BUET); research in image processing, computer vision, ML, medical imaging; recipient of IEEE ICIP best paper award. physicsclass.blog
 
 
Himabindu Lakkaraju, PH.D.
Harvard University, USA; expert in interpretable, fair, and trustworthy AI/ML and high-stakes decision-making systems. https://en.wikipedia.org/wiki/Himabindu_Lakkaraju
 
Mohamed Rafiquzzaman, Ph.D.
California State Polytechnic University, Pomona, USA; veteran in CS/EE with contributions to microprocessor-based AI systems and teaching numerous students https://en.wikipedia.org/wiki/Mohamed_Rafiquzzaman
 
Shafiqul Islam, Ph.D.
Tufts University, USA; although notable for engineering diplomacy and systems thinking, has leadership in data-driven decision-making and system-AI interfaces relevant to broader AI/engineering contexts. https://en.wikipedia.org/wiki/Shafiqul_Islam_%28academic%29
 
Regional Editors (Bangladesh)
Sazzad Hossain, Ph.D.
AI & Quantum Computing, Bangladesh-based researcher with global experience in AI-driven cybersecurity and big-data architectures (University of Liberal Arts Bangladesh). https://www.professorsazzad.com/
 
Khondaker Abdullah Al Mamun, Ph.D.
Habibur Rahman, Ph.D.
Islamic University, Kushtia
Expertise spans ML, DL, bioinformatics, and health informatics in Bangladesh. https://cabaair.com/people/
 
 
Early Career Editorial Board
 

Rensi Chen
Senior Analyst – Revenue Management, United States

Rensi Chen is a Senior Analyst specializing in Revenue Management, with a strong academic and professional background in business intelligence and big data analytics. A verified scholar affiliated with the University of Rochester, Chen has contributed to interdisciplinary research at the intersection of data mining, AI, and economic forecasting. Notable works include the design of big data-driven analytics systems and the development of multi-modal AI models for macroeconomic prediction. With experience in both academic research and industry applications, Chen brings practical insight into leveraging large-scale data for strategic decision-making, performance optimization, and predictive modeling in complex business environments.

 

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