Phd, University of Saravan, Iran
Dr. Shayesteh Tabatabei is an accomplished Iranian Associate Professor in Computer Engineering at the Higher Education Complex of Saravan. Born in Tabriz, she has been recognized among the top 2% of scientists worldwide in 2024 🌍. With a Ph.D. from Tehran Science and Research University, her expertise spans wireless sensor networks, mobile ad-hoc networks, IoT, and intelligent algorithms 🤖📡. She is a passionate educator and researcher who actively contributes to advancing intelligent routing protocols and optimization algorithms. Shayesteh also organizes workshops to foster knowledge in wireless networks and ISI article writing, supporting academic growth in her community 📚🎓.
Profile:
🎓Education & Experience :
Dr. Shayesteh Tabatabei earned her Ph.D. in Computer Engineering from Tehran Science and Research University between 2010 and 2015, where she focused on intelligent routing protocols for mobile ad-hoc networks 🎓. Prior to that, she completed her M.Sc. at Islamic Azad University of Shabestar from 2007 to 2009, researching improvements to the AODV routing protocol using reinforcement learning 🎓. She also holds a B.Sc. in Computer Engineering from the same university, earned between 2002 and 2006 🎓. Currently, she serves as an Associate Professor at the Department of Computer Engineering, Higher Education Complex of Saravan 💼. Shayesteh has extensive teaching experience in advanced computer engineering courses across several universities 📱 and is proficient in simulation tools and programming languages such as Matlab, R, Opnet, GloMoSim, C/C++, Python, HTML, SQL, and Oracle 💻.
🔹Professional Development :
Dr. Tabatabei actively pursues professional growth through leading and organizing numerous workshops, including Wireless Networks, IoT, and ISI Article Writing workshops, held between 2014 and 2022 🛠️📅. Her commitment to advancing scientific knowledge is reflected in her top researcher awards at multiple universities 🏆. She continually updates her skills in simulation tools and programming languages, strengthening her research and teaching capabilities 💻. Her dedication to academic excellence and community support drives her efforts in mentoring students and colleagues, facilitating better understanding and application of cutting-edge technologies in wireless communication and intelligent systems 🤝🌐.
🔹 Research Focus :
Dr. Tabatabei’s research centers on wireless sensor networks, mobile ad-hoc networks, and Internet of Things (IoT), focusing on designing and optimizing intelligent routing protocols for efficient communication in dynamic networks 📡📶. She explores intelligent and optimization algorithms to enhance network performance and reliability, integrating reinforcement learning techniques for adaptive routing 📊🤖. Her work addresses challenges in distributed systems and intelligent systems to support scalable, energy-efficient, and secure data transmission. This research is crucial for advancing next-generation smart networks and IoT applications, contributing to improved connectivity and smart infrastructure development 🌐⚙️.
🏆Awards and Honors :
Dr. Shayesteh Tabatabei has been recognized multiple times for her outstanding research contributions. She was honored as the Top Researcher at the Islamic Azad University of Malekan Branch in 2011, 2016, and 2017 🏆. More recently, she received the Top Researcher award at the Higher Education Complex of Saravan in 2019, 2021, and 2022 🏅. These accolades highlight her consistent dedication to advancing research and excellence in her academic field.
🔹Publication Top Notes :
- Title: New energy efficient management approach for wireless sensor networks in target tracking using Vortex Search Algorithm
Citation:
Tabatabaei, S. (2025). New energy efficient management approach for wireless sensor networks in target tracking using Vortex Search Algorithm. Heliyon, 2025-Mar. https://doi.org/10.1016/j.heliyon.2025.e42867
Summary:
This paper proposes a novel energy-efficient management protocol for wireless sensor networks (WSNs) focused on improving target tracking accuracy and prolonging network lifetime. It employs the Vortex Search Algorithm, a nature-inspired metaheuristic optimization technique, to optimize cluster formation and routing paths, reducing energy consumption. Simulation results demonstrate enhanced performance compared to existing methods, showing increased network longevity and tracking reliability.
- Title: WITHDRAWN: A Novel method of routing in multi-channel multi-radio wireless mesh networks
Citation:
Tabatabaei, S., & Mehbodniya, A. (2025). WITHDRAWN: A Novel method of routing in multi-channel multi-radio wireless mesh networks. Preprint, 2025-Mar-05. https://doi.org/10.21203/rs.3.rs-3069796/v2
Summary:
This preprint, now withdrawn, originally introduced a new routing method for multi-channel, multi-radio wireless mesh networks aimed at enhancing throughput and minimizing interference. The approach integrated channel assignment and route optimization strategies. As the paper was withdrawn, details on methodology or results are unavailable.
- Title: An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic
Citation:
Tabatabaei, S., & Shaheen, Q. (2024). An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic. PLOS ONE, 2024-Nov-04. https://doi.org/10.1371/journal.pone.0297728
Summary:
This article presents an energy-aware routing protocol that combines the Scattered Search Algorithm, a global optimization technique, with fuzzy logic to improve decision-making in WSNs. The protocol focuses on efficient energy usage by dynamically adapting routing paths according to network conditions and sensor node energy levels, significantly extending network lifespan while maintaining reliable data transmission.
- Title: A Fault-Tolerant Clustering Approach for Target Tracking in Wireless Sensor Networks
Citation:
Tabatabaei, S. (2024). A Fault-Tolerant Clustering Approach for Target Tracking in Wireless Sensor Networks. Wireless Personal Communications, 2024-Aug. https://doi.org/10.1007/s11277-024-11495-4
Summary:
This paper introduces a fault-tolerant clustering protocol designed for target tracking applications in WSNs. The method enhances network robustness by incorporating mechanisms to detect and recover from node failures during target tracking, ensuring continuous monitoring and reducing data loss. Results show improved reliability and accuracy in tracking moving targets under adverse network conditions.
- Title: A new model for evaluating the impact of organizational culture variables on the success of knowledge management in organizations using the TOPSIS multi-criteria algorithm: Case study
Citation:
Tabatabaei, S. (2024). A new model for evaluating the impact of organizational culture variables on the success of knowledge management in organizations using the TOPSIS multi-criteria algorithm: Case study. Computers in Human Behavior Reports, 2024-May. https://doi.org/10.1016/j.chbr.2024.100417
Summary:
This interdisciplinary paper applies the TOPSIS multi-criteria decision-making algorithm to evaluate how various organizational culture factors affect the success of knowledge management initiatives. The case study reveals key cultural drivers that significantly influence knowledge sharing and management, providing actionable insights for organizational development and strategy planning.
🔹Conclusion:
Dr. Shayesteh Tabatabei exemplifies the qualities that the Best Researcher Award seeks to honor: impactful research, global recognition, leadership in knowledge dissemination, and a clear dedication to advancing her field. Her combination of technical innovation and educational mentorship makes her an ideal candidate for this award, reflecting both academic excellence and meaningful community impact.