Ilya Levin | Artificial Intelligence | Research Excellence Award

Prof. Ilya Levin | Artificial Intelligence | Research Excellence Award

Professor | Holon Institute of Technology | Israel

Prof. Ilya Levin is a researcher at Holon Institute of Technology, specializing in artificial intelligence, machine learning, and educational technology. His research focuses on computational thinking, neural networks, and AI-driven learning systems. He has strong expertise in algorithm design and interdisciplinary innovation. His contributions are recognized through impactful publications and academic work. According to Scopus, he has 552 citations, 88 documents, and an h-index of 13, reflecting his significant impact in AI and education research.

 

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View Scopus Profile View ORCID Profile View Google Scholar Profile

Featured Publications


Culture and Society in the Digital Age

– Information, 2021 (Citations: 275)


Massive open online courses – the modern concept in education and learning

– Vestnik Tomskogo State University, 2014 (Citations: 133)


Teaching machine learning in elementary school

– International Journal of Child-Computer Interaction, 2022 (Citations: 82)

 

Muhammad Furqan Zia | Artificial Intelligence | Young Scientist Award

Mr. Muhammad Furqan Zia | Artificial Intelligence | Young Scientist Award

Researcher | Université du Québec à Trois-Rivières | Canada

Mr. Muhammad Furqan Zia is an emerging researcher at Université du Québec à Trois-Rivières, specializing in artificial intelligence and semantic communication. His research focuses on explainable AI and intelligent communication systems, addressing transparency and efficiency challenges. He has skills in AI modeling, data analysis, and system design, contributing to scholarly publications. His work is gaining recognition in the research community. According to Scopus, he has 5 citations, 4 documents, and an h-index of 2, reflecting his growing academic impact.

 

Citation Metrics (Scopus)

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View Scopus Profile View ORCID Profile View Google Scholar Profile

Featured Publications


An Advanced Non-Orthogonal Multiple Access Security Technique for Future Wireless Communication Networks

– RS Open Journal on Innovative Communication Technologies, 2020 (Citations: 27)

 

Awele Okolie | Artificial Intelligence | Research Excellence Award

Ms. Awele Okolie | Artificial Intelligence | Research Excellence Award

Data Analyst Intern | Wentworth Institute of Technology | United States

Ms. Awele Okolie is an emerging researcher in Machine Learning and Artificial Intelligence, with a strong focus on socially impactful, data-driven research. Her work spans food insecurity prediction, financial fraud detection, healthcare analytics, traffic safety modeling, and explainable AI, demonstrating applied innovation across public policy and safety-critical domains. Her research interests include predictive modeling, explainable machine learning, spatiotemporal analysis, and AI-driven decision systems, supported by skills in data analytics, statistical modeling, and real-world dataset integration. Her scholarly contributions show growing recognition, with Google Scholar metrics of 41 citations, 14 documents, and an h-index of 5, while Scopus citations, documents, and h-index are not provided. Overall, her work reflects a strong commitment to transparent, ethical, and high-impact artificial intelligence research.

 

Citation Metrics (Google Scholar)

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14

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View Google Scholar Profile  View ResearchGate Profile

Featured Publications


Predicting food insecurity across US census tracts: A machine learning analysis using the USDA Food Access Research Atlas

– International Journal of Science and Research Archive, 17(2), 1156-1172, 2025 (Citations: 11)


An Explainable XGBoost Framework for Detecting Fraudulent Financial Transactions

– Journal of Scientific Research and Reports, 31(12), 244-255, 2025 (Citations: 6)


Spatiotemporal analysis and predictive modeling of traffic accidents in Boston: Insights for advancing Vision Zero initiatives

– International Journal of Science and Research Archive, 17(1), 528-543, 2025 (Citations: 6)


Machine learning approaches for predicting 30-day hospital readmissions: Evidence from Massachusetts healthcare data

– World Journal of Advanced Research and Reviews, 28(1), 1-12, 2025 (Citations: 6)

 

Maliki Moustapha | Computer Science | Best Researcher Award

Dr. Maliki Moustapha | Computer Science | Best Researcher Award

PhD | Erciyes University | Turkey

Dr. Maliki Moustapha, an accomplished researcher from Erciyes University, is recognized for his expertise in Artificial Intelligence (AI), Deep Transfer Learning, and Data Engineering, with a strong focus on the integration of intelligent algorithms and data-driven models to address real-world computational challenges. His academic background is rooted in computer science and engineering, where he developed advanced skills in machine learning, neural networks, data mining, and smart systems design. Professionally, Dr. Moustapha has been actively engaged in both research and academic mentorship, contributing to the development of innovative solutions in AI-powered automation, pattern recognition, and intelligent monitoring systems. His major research interests encompass computer vision, deep learning model optimization, spatiotemporal data analysis, and Internet of Things (IoT)-based smart healthcare systems. Among his most cited contributions is the publication titled “A Novel YOLOv5 Deep Learning Model for Handwriting Detection and Recognition” in the International Journal on Artificial Intelligence Tools (2023), which demonstrates superior accuracy and efficiency in image recognition. He has also published influential works on spatial and spatiotemporal clustering algorithms and IoT-based patient monitoring, bridging the gap between data intelligence and applied computing. His research skills span across Python programming, neural network modeling, big data analytics, data preprocessing, and model training for intelligent systems. Though early in his academic journey, Dr. Moustapha has earned recognition for his impactful work, showing promising potential in advancing AI technologies. According to Scopus and Google Scholar, he has achieved 9 citations, an h-index of 1, and several published documents reflecting growing international recognition. Dr. Moustapha’s research continues to contribute meaningfully to the fields of artificial intelligence and computational intelligence. In conclusion, his innovative approach, interdisciplinary mindset, and technological vision position him as a forward-thinking researcher committed to shaping the next generation of intelligent data systems and AI-driven innovations.

Profiles: ORCID | Google Scholar

Featured Publications

1. Moustapha, M., Taşyürek, M., & Öztürk, C. (2023). A novel YOLOv5 deep learning model for handwriting detection and recognition. International Journal on Artificial Intelligence Tools, 32(04), 2350016.

2. Moustapha, M. (2024). Spatial and spatiotemporal clustering algorithms in data mining. In Proceedings of the 3rd International Conference on Data and Electronics and Computing (ICDEC).

3. Moustapha, M. (2019). Alternative approach of patient monitoring system based on Internet of Things. In Proceedings of the II. International Science and Academic Congress (INSAC).