Shayesteh Tabatabaei | Computer Science | Women Researcher Award

Assoc. Prof. Dr. Shayesteh Tabatabaei | Computer Science | Women Researcher Award

Doctored at University of Saravan, Iran

Assoc. Prof. Dr. Shayesteh Tabatabaei is a distinguished computer engineering researcher, ranked among the top 2% of scientists worldwide in 2024. She holds a Ph.D. in Computer Engineering and specializes in Wireless Sensor Networks, Mobile Ad-Hoc Networks, IoT, and Optimization Algorithms. With numerous high-impact journal publications, she has significantly contributed to intelligent routing protocols and energy-efficient networking solutions. As an Associate Professor, she teaches advanced courses in Artificial Intelligence, Fuzzy Logic, and Distributed Systems while mentoring students and researchers. Recognized as a top researcher multiple times, she has also led workshops on ISI article writing, IoT, and wireless networks. Her expertise in computational methodologies and commitment to knowledge dissemination make her a key figure in her field. Dr. Tabatabaei’s research excellence, leadership, and dedication to innovation make her a strong candidate for prestigious academic awards, with potential for further global collaborations and industry-driven research initiatives.

Professional Profile 

Education

Assoc. Prof. Dr. Shayesteh Tabatabaei holds a Ph.D. in Computer Engineering from Tehran Science and Research University, Iran, earned in 2015 with an outstanding GPA of 18.63/20. Her doctoral research focused on developing intelligent routing protocols for mobile ad-hoc networks under the supervision of Dr. M. Teshnehlab. She completed her M.Sc. in Computer Engineering at Islamic Azad University of Shabestar in 2009, where she improved the AODV routing protocol using reinforcement learning, achieving a GPA of 18.69/20. Her academic journey began with a B.Sc. in Computer Engineering from the same university, graduating in 2006 with a GPA of 17.12/20. Throughout her education, Dr. Tabatabaei demonstrated excellence in research and innovation, particularly in wireless networks and intelligent algorithms. Her strong academic background has shaped her expertise in computer engineering, making her a leading researcher and educator in the field of network optimization, IoT, and artificial intelligence.

Professional Experience

Assoc. Prof. Dr. Shayesteh Tabatabaei is a highly accomplished academic and researcher in computer engineering, currently serving as an Associate Professor in the Department of Computer Engineering at the Higher Education Complex of Saravan, Iran. With extensive teaching experience, she has instructed both undergraduate and postgraduate courses in Artificial Intelligence, Fuzzy Logic, Distributed Systems, Advanced Database Systems, and Programming Languages such as C, C++, Python, and SQL. Her research focuses on Wireless Sensor Networks, Mobile Ad-Hoc Networks, IoT, and Optimization Algorithms, with numerous high-impact journal publications and conference presentations. She has been recognized multiple times as a top researcher and has actively contributed to academic development by organizing workshops on ISI article writing, IoT, and wireless networks. Dr. Tabatabaei’s expertise extends to computational simulations and algorithm development, making her a leading figure in her field. Her dedication to education, research, and innovation continues to influence the next generation of computer engineers.

Research Interest

Assoc. Prof. Dr. Shayesteh Tabatabaei’s research interests lie at the intersection of intelligent computing and network optimization, focusing on Wireless Sensor Networks (WSNs), Mobile Ad-Hoc Networks (MANETs), Internet of Things (IoT), and Intelligent Algorithms. Her work aims to enhance the efficiency, reliability, and security of communication networks through advanced routing protocols, optimization algorithms, and artificial intelligence techniques. She has contributed significantly to energy-aware clustering, fault tolerance mechanisms, and adaptive routing in WSNs, utilizing machine learning, fuzzy logic, and evolutionary computing. Additionally, her research explores optimization algorithms such as Genetic Algorithms, Bee Colony Optimization, and Social Spider Optimization to improve network performance. Through her extensive publications in high-impact journals and conferences, Dr. Tabatabaei continues to advance the field of computational intelligence and networked systems. Her passion for innovation drives her to develop cutting-edge solutions for real-world challenges in modern communication technologies.

Award and Honor

Assoc. Prof. Dr. Shayesteh Tabatabaei has received multiple awards and honors in recognition of her outstanding contributions to research and academia. She has been ranked among the top 2% of scientists worldwide in 2024, highlighting her global impact in computer engineering. She has been recognized as the Top Researcher at various institutions multiple times, including Islamic Azad University of Malekan Branch in 2011, 2016, and 2017, and the Higher Education Complex of Saravan in 2019, 2021, and 2022. Her achievements reflect her dedication to advancing knowledge in wireless sensor networks, optimization algorithms, and artificial intelligence. In addition to her research excellence, she has led training workshops and mentored young scholars, further solidifying her reputation as a leader in her field. Her numerous accolades demonstrate her commitment to innovation, making her a strong candidate for prestigious academic and scientific awards on both national and international levels.

Research Skill

Assoc. Prof. Dr. Shayesteh Tabatabaei possesses strong research skills in computer engineering, wireless communication, and intelligent systems. Her expertise spans algorithm design, network optimization, artificial intelligence, and data analysis, with a particular focus on Wireless Sensor Networks (WSNs), Mobile Ad-Hoc Networks (MANETs), IoT, and optimization techniques. She is proficient in developing energy-efficient routing protocols, fault-tolerant clustering methods, and machine learning-based optimization algorithms. Dr. Tabatabaei has extensive experience with simulation tools such as MATLAB, R, Opnet, and GloMoSim, which she utilizes to validate her research findings. Additionally, she is skilled in multiple programming languages, including C, C++, Python, JavaScript, SQL, and Oracle, enabling her to implement and test computational models effectively. Her ability to integrate fuzzy logic, evolutionary algorithms, and artificial intelligence into network solutions showcases her innovative approach to problem-solving, making her a highly capable and influential researcher in the field.

Conclusion

Dr. Shayesteh Tabatabaei is highly qualified for the Women Researcher Award, given her global recognition, extensive research contributions, leadership in academia, and dedication to advancing knowledge in computer engineering. Strengthening international collaborations and industry partnerships could further elevate her impact.

Publications Top Noted

  • A novel fault tolerance energy-aware clustering method via social spider optimization (SSO) and fuzzy logic and mobile sink in wireless sensor networks (WSNs).

    • Cited by: 65
    • Year: 2020
  • A novel energy-aware clustering method via Lion Pride Optimizer Algorithm (LPO) and fuzzy logic in wireless sensor networks (WSNs).

    • Cited by: 50
    • Year: 2019
  • Proposing an energy-aware routing protocol by using fish swarm optimization algorithm in WSN (wireless sensor networks).

    • Cited by: 47
    • Year: 2021
  • A new method to find a high reliable route in IoT by using reinforcement learning and fuzzy logic.

    • Cited by: 36
    • Year: 2020
  • Reliable routing algorithm based on clustering and mobile sink in wireless sensor networks.

    • Cited by: 30
    • Year: 2019
  • A novel method for clustering in WSNs via TOPSIS multi-criteria decision-making algorithm.

    • Cited by: 23
    • Year: 2020
  • Improved routing vehicular ad-hoc networks (VANETs) based on mobility and bandwidth available criteria using fuzzy logic.

    • Cited by: 20
    • Year: 2020
  • A new routing protocol to increase throughput in mobile ad hoc networks.

    • Cited by: 20
    • Year: 2015
  • Provide energy-aware routing protocol in wireless sensor networks using bacterial foraging optimization algorithm and mobile sink.

    • Cited by: 19
    • Year: 2022

Nguyen Minh Tuan | Computer science | Best Researcher Award

🌟Mr. Nguyen Minh Tuan, Computer science, Best Researcher Award🏆

Nguyen Minh Tuan at KMUTNB, Thailand

Nguyen Minh Tuan is a dedicated educator and researcher in the field of applied mathematics and computer science. With a strong academic background including a Ph.D. from King Mongkut’s University of Technology North Bangkok, Thailand, Tuan has demonstrated expertise in areas such as differential equations, data science, and deep machine learning. His passion for teaching is evident from his years of experience as a lecturer and mentor at various educational institutions in Vietnam.

Author Metrics

Tuan’s scholarly contributions are underscored by his ORCID profile, showcasing his publications and citations. With a GPA of 3.87 in his Ph.D. program and accolades for his master’s thesis, Tuan has consistently demonstrated excellence in academic pursuits. They have been cited 6 times across 3 documents and have authored 4 documents. Their h-index is 2.

Scopus Profile

ORCID Profile

Education

Tuan’s educational journey encompasses rigorous training in mathematics and computer science. He earned his Bachelor’s degree from Can Tho University, Vietnam, followed by a Master’s degree from the University of Science, Ho Chi Minh City. Currently pursuing a Ph.D., Tuan is expanding his expertise in applied mathematics and computer science.

Research Focus

Tuan’s research interests lie at the intersection of applied mathematics and computer science. His work focuses on areas such as ordinary and nonlinear differential equations, fractional differential equations, and deep machine learning. By exploring these fields, Tuan aims to contribute to advancements in mathematical modeling and data-driven problem-solving.

Professional Journey

Tuan’s professional journey began as a teacher at An Thoi High School, Ben Tre Province, Vietnam, where he honed his skills in mathematics education. He later transitioned to a lecturer position at Ho Chi Minh City Vinatex College of Technology and Economics, where he also served as the leader of the Computer Club. Currently, Tuan is pursuing his Ph.D. while actively engaging in research and academia.

Honors & Awards

Throughout his career, Tuan has received recognition for his academic achievements. His master’s thesis earned accolades with a GPA of 9.5, reflecting his dedication and proficiency in mathematics research. Additionally, his consistent performance, evidenced by a GPA of 3.87 in his Ph.D. program, speaks to his commitment to excellence.

Publications Noted & Contributions

Tuan’s contributions to the field of applied mathematics and computer science are evident in his publications and research outputs. Notable works include papers addressing topics such as nonlinear heat equations and their applications, as well as advancements in deep machine learning algorithms. Through his research, Tuan seeks to address real-world challenges and contribute to the academic discourse.

“The Bilinear Neural Network Method for Solving Benney–Luke Equation”

Published in the journal Partial Differential Equations in Applied Mathematics in June 2024.

DOI: 10.1016/j.padiff.2024.100682

Contributors: Nguyen Minh Tuan, Sanoe Koonprasert, Sekson Sirisubtawee, Phayung Meesad

“Fareeha Transform Performance In Solving Fractional Differential Telegraph Equations Combining Adomian Decomposition Method”

Published in the WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL in April 16, 2024.

DOI: 10.37394/23203.2024.19.9

Contributors: Nguyen Minh Tuan, Sanoe Koonprasert, Phayung Meesad

“General Integral Transform Performance for Space-Time Fractional Telegraph Equations”

Published in the WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL in April 11, 2024.

DOI: 10.37394/23203.2024.19.6

Contributors: Nguyen Minh Tuan, Sanoe Koonprasert, Phayung Meesad

“New Exact Traveling Wave Solutions of the (3+1)-Dimensional Chiral Nonlinear Schrodinger Equation Using Two Reliable Techniques”

Published in the Thai Journal of Mathematics on March 31, 2024.

Contributors: Nguyen Minh Tuan

“New Data About Library Service Quality and Convolution Prediction”

Published in the CTU Journal of Innovation and Sustainable Development on October 16, 2023.

DOI: 10.22144/ctujoisd.2023.032

Contributors: Minh Tuan Nguyen, Meesad Phayung, Van Hieu Duong, Maliyaem Maleerat

Research Timeline

Tuan’s research trajectory spans several years, beginning with his undergraduate studies at Can Tho University and culminating in his current Ph.D. program at King Mongkut’s University of Technology North Bangkok. Along this journey, he has delved into various research topics, gaining expertise and making valuable contributions to the field.

Collaborations and Projects

Tuan has collaborated with fellow researchers and participated in projects aimed at advancing mathematical modeling and computational techniques. His involvement in interdisciplinary collaborations has allowed him to leverage diverse perspectives and methodologies, leading to innovative solutions and insights in applied mathematics and computer science.