Innovative Research Award
Yahya Dorostkar Navaei — University of Mohaghegh Ardabili, Iran
Yahya Dorostkar Navaei is a computer engineering researcher and AI/ML practitioner affiliated with the University of Mohaghegh Ardabili in Iran. His research profile encompasses graph-based recommendation systems, social-network analysis, machine learning, deep learning, reinforcement learning, optimization, cybersecurity, healthcare analytics, Internet of Things, and data-driven computing. His doctoral research addressed hierarchical friend recommendation using deep reinforcement learning, while his broader publication record includes graph-based recommendation, influence maximization, anomaly detection, network security, routing optimization, and recommender systems. His current professional work also includes agentic artificial intelligence, retrieval-augmented generation, vector databases, financial forecasting, and real-time data processing.
Abstract
Yahya Dorostkar Navaei is a computer engineering researcher specializing in artificial intelligence, machine learning, deep learning, reinforcement learning, recommendation systems, and graph-based computing. His research covers social networks, cybersecurity, healthcare, wireless networks, and edge computing, with recent work in agentic AI, RAG, vector databases, and financial forecasting. The supplied academic profile reports 20 documents, 507 citations, and an h-index of 12 on Google Scholar.
Keywords
Graph Databases, Artificial Intelligence, Machine Learning, Deep Learning, Reinforcement Learning, Recommendation Systems, Social Network Analysis, Data Mining, Optimization, Agentic AI, Retrieval-Augmented Generation
Introduction
Yahya Dorostkar Navaei’s research spans artificial intelligence, machine learning, recommender systems, data mining, graph-based social-network analysis, and optimization. His doctoral research focused on friend recommendation using deep reinforcement learning, while his publications address graph recommendation, influence maximization, cybersecurity, healthcare analytics, wireless networks, and edge computing. His professional expertise also includes agentic AI, RAG, LangGraph, vector databases, and AI-driven financial forecasting.
Research Profile
Yahya Dorostkar Navaei holds a Ph.D. and M.Sc. in Computer Engineering and a B.Sc. in Computer Science. His academic and professional experience covers artificial intelligence, data mining, machine learning, recommendation systems, optimization, and financial-data analysis. His current technical interests include agentic AI, retrieval-augmented generation, semantic search, and vector databases.
Research Contributions
Yahya Dorostkar Navaei’s research contributions span graph and social-network computing, recommendation systems, artificial intelligence, cybersecurity, and IoT-based distributed computing. His work includes graph-based friend recommendation, social-network influence analysis, e-commerce and music recommendation, healthcare recommender systems, machine learning, deep learning, reinforcement learning, intrusion detection, anomaly detection, wireless sensor networks, and edge computing. His recent professional activities further extend into agentic AI, LangGraph workflows, retrieval-augmented generation, semantic search, vector databases, and financial-market forecasting.
Publications
Yahya Dorostkar Navaei’s publications span graph-based recommendation, social-network analysis, deep learning, cybersecurity, healthcare, wireless sensor networks, and edge computing. His research applies machine learning, optimization, and data mining to recommendation systems, anomaly detection, network security, IoT healthcare, and data-intensive computational problems.[2][3][4][5][6]
Research Impact
Yahya Dorostkar Navaei’s Google Scholar profile reports 20 documents, 507 citations, and an h-index of 12. His publications span social networks, recommendation systems, cybersecurity, healthcare, wireless communications, and edge computing, with research applying machine learning and optimization to data-driven computational problems.[5] [6] The supplied profile also describes ongoing work involving agentic AI, retrieval-augmented generation, and financial forecasting, extending the application of data-driven methods toward contemporary AI engineering workflows.
Award Suitability
Yahya Dorostkar Navaei’s research aligns with database-oriented and data-intensive computing through graph-based recommendation, social-network analysis, data mining, recommender systems, IoT, edge computing, and machine learning. His work demonstrates applications in graph data, network analytics, intelligent data processing, and AI-enabled information retrieval, making these areas relevant to consideration for the International Database Scientist Awards.
Conclusion
Yahya Dorostkar Navaei’s profile spans artificial intelligence, machine learning, graph-based analysis, recommendation systems, cybersecurity, and data-intensive computing. His research includes social networks, healthcare, wireless communications, and edge computing, while his current work focuses on agentic AI, RAG, vector databases, and financial-data forecasting.
External Links
References
- Elsevier. (n.d.). Scopus author details: Yahya Dorostkar Navaei, Author ID 57222517231. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57222517231
- Navaei, Y. D., et al. (2026). A graph-based friend recommendation system in social networks using Q-Deep Learning Network. Information Sciences. https://doi.org/10.1016/j.ins.2026.124129
- Navaei, Y. D., et al. (2025). Identifying Key Influencers in Social Networks: A New Neighborhood-Based Method. Journal of Soft Computing and Information Technology. https://doi.org/10.22034/jscit.2025.219059
- Navaei, Y. D., et al. (2025). Ordered Clustering-Based Semantic Music Recommender System Using Deep Learning Selection. Computers, Materials & Continua. https://doi.org/10.32604/cmc.2025.061343
- Einy, S., Oz, C., & Navaei, Y. D. (2021). The anomaly- and signature-based IDS for network security using hybrid inference systems. Mathematical Problems in Engineering, 2021, 6639714. https://doi.org/10.1155/2021/6639714
- Nanehkaran, Y. A., Licai, Z., Chen, J., Zhongpan, Q., Xiaofeng, Y., Navaei, Y. D., et al. (2022). Diagnosis of chronic diseases based on patients’ health records in IoT healthcare using the recommender system. Wireless Communications and Mobile Computing, 2022, 5663001. https://doi.org/10.1155/2022/5663001