Yi Li | Social Network Analysis | Best Researcher Award

Mr. Yi Li | Social Network Analysis | Best Researcher Award

Graduate Student | university of science and technology beijing | China 

Mr. Yi Li is a promising graduate student at the University of Science and Technology Beijing, actively pursuing an M.S. degree in Communication Engineering. With a solid academic foundation laid at Tianjin University of Science and Technology, where he earned his B.S. degree in Electronic Information Engineering in 2022, Yi Li has cultivated a deep interest in vehicular communications and the Internet of Vehicles (IoV). His research combines theoretical insights and practical applications, contributing to the advancement of signal detection methods within vehicular ad-hoc networks.

Profile

Scopus

Education

Yi Li’s educational journey reflects his commitment to excelling in the field of communication engineering. He completed his B.S. degree in Electronic Information Engineering from Tianjin University of Science and Technology in 2022. Currently, he is a graduate student at the University of Science and Technology Beijing, where he is focused on exploring innovations in vehicular communication systems. His academic training has equipped him with strong analytical and problem-solving skills, essential for addressing complex challenges in IoV systems.

Experience

During his academic tenure, Yi Li has amassed substantial research experience. He has been actively involved in developing advanced signal detection techniques for vehicular ad-hoc networks, contributing to both academia and industry. Yi Li’s work includes designing distributed communication frameworks and IoT testing instruments and participating in large-scale projects such as millimeter wave cloud radar development. Additionally, his internship at the Beijing Academy of Artificial Intelligence (BAAI) allowed him to contribute to cutting-edge projects, including a subjective evaluation platform for large language models.

Research Interests

Yi Li’s primary research interests lie in the Internet of Vehicles (IoV) and Vehicular Communications. He is particularly focused on developing innovative signal detection methods that leverage social network analysis and parallel intelligence. His work aims to enhance vehicular communication networks’ reliability and efficiency, addressing real-world challenges in intelligent transportation systems.

Awards

Yi Li has demonstrated excellence through his scholarly contributions, which have earned him recognition in academic and professional circles. His patent on a marine communication signal detection method is a testament to his innovative capabilities. In addition, he has received nominations for research awards, including the Young Scientist Award, reflecting his potential as a rising researcher in vehicular communication technologies.

Publications

Yi Li has authored several significant publications in indexed journals and conferences. Notable works include:

“Signal Detection Techniques in Social Internet of Vehicles: Review and Challenges”
IEEE Transactions on Intelligent Vehicles, Major Revision Submitted, 2024.

“Signal Detection Techniques in Social Internet of Vehicles: Review and Challenges”
IEEE Intelligent Transportation Systems Magazine, 2024. Cited by 10 articles.

“Signal Detection Method Based on Social Relationship Strength in Vehicular Ad-hoc Networks”
IFAC-PapersOnLine, Vol. 58, Issue 10, 2024. DOI: 10.1016/j.ifacol.2024.07.336.

“Signal Detection Method Based on Data Characteristics in Vehicular Ad Hoc Networks”
2024 IEEE Intelligent Vehicles Symposium, Jeju Island, Korea, 2024. DOI: 10.1109/IV55156.2024.10588388.

“Computational Experiments and Comparative Analysis of Signal Detection Algorithms in Vehicular Ad Hoc Networks”
IEEE Journal of Radio Frequency Identification, Vol. 8, 2024. DOI: 10.1109/JRFID.2024.3355298.

“Computational Experiments of Signal Detection Algorithms in VANETs based on Parallel Intelligence”
2023 IEEE International Conference on Digital Twins and Parallel Intelligence, Orlando, USA, 2023. DOI: 10.1109/DTPI59677.2023.10365425.

“SIoV Research Status and Development Trends”
Complexity and Intelligence, 2022, Vol. 18(03).

Conclusion

Mr. Yi Li’s academic and research endeavors showcase his commitment to pushing the boundaries of communication engineering. With a strong foundation, innovative research, and impactful publications, he is well on his way to becoming a prominent figure in the field of vehicular communications. His dedication to advancing signal detection methods and IoV technologies demonstrates his potential to contribute significantly to the future of intelligent transportation systems.

Alireza Rezvanian | Social Network Analysis | Best Researcher Award

Assist. Prof. Dr. Alireza Rezvanian | Social Network Analysis | Best Researcher Award

Assistant Professor | University of Science and Culture | Iran

Dr. Alireza Rezvanian is an accomplished academic and researcher, currently serving as an Assistant Professor at the University of Science and Culture (USC) in Tehran, Iran. He is widely recognized for his contributions to computer engineering and complex network analysis. He has held several editorial positions in notable journals, such as CAAI Transactions on Intelligence Technology, Human-centric Computing and Information Sciences, The Journal of Engineering, and Data in Brief. His research has influenced fields like social network analysis, machine learning, and data mining.

Profile

Scopus

Education

Dr. Rezvanian earned his Ph.D. in Computer Engineering from Amirkabir University of Technology (Tehran Polytechnic) in 2016, under the mentorship of Dr. Mohammad Reza Meybodi. His doctoral research focused on “Stochastic Graphs for Social Network Analysis.” Before his Ph.D., he completed his M.Sc. in Computer Engineering at Islamic Azad University of Qazvin in 2010 and his B.Sc. from Bu-Ali Sina University of Hamedan in 2007. Both his M.Sc. and B.Sc. theses dealt with topics in artificial intelligence, specifically in the improvement of algorithms using learning automata for dynamic environments.

Experience

Dr. Rezvanian’s career spans a variety of academic and research roles. He is currently the Director of Information and Scientific Resources at USC, a position he has held since 2023. He is also a member of the Board of IEEE Computer Society Iran Chapter and a supervisor for MSc students in Computer Engineering. Prior to this, Dr. Rezvanian was the Head of the Computer Engineering Department at USC from 2021 to 2023. Additionally, he has served as an adjunct professor at prestigious institutions such as Amirkabir University of Technology, University of Tehran, and Tarbiat Modares University. His research experience extends beyond academic roles, including research positions at the Institute for Research in Fundamental Sciences (IPM) and the Niroo Research Institute.

Research Interests

Dr. Rezvanian’s research interests are rooted in complex networks and social network analysis, with a particular focus on learning automata and evolutionary algorithms. His work spans a range of topics, including machine learning, data mining, soft computing, image processing, and the application of stochastic models in social networks. His interdisciplinary approach allows him to develop innovative solutions for dynamic environments, particularly in areas involving graph-based structures, network sampling, and influence maximization.

Awards

Dr. Rezvanian’s research and academic excellence have garnered multiple recognitions throughout his career. Notably, he has received the Best Paper Award at various conferences and been nominated for multiple IEEE Best Paper awards. His H-index on Google Scholar is 26, showcasing the significant impact of his work within the scientific community.

Publications

Dr. Rezvanian’s publication record is robust, comprising numerous influential books, journal articles, and conference papers. His books include “Advances in Learning Automata and Intelligent Optimization” (Springer, 2022), “Cellular Learning Automata: Theory and Applications” (Springer, 2021), and “Learning Automata Approach for Social Networks” (Springer, 2019). His journal papers have been published in high-impact journals such as Results in Engineering, Social Network Analysis and Mining, and Applied Network Science. Below are some of his notable journal articles:

Khomami, M. M. D., Meybodi, M. R., & Rezvanian, A. (2024). Efficient Identification of Maximum Independent Sets in Stochastic Multilayer Graphs with Learning Automata. Results in Engineering, 24, 103224.

Rezvanian, A., Vahidipour, S. M., & Jalali, Z. S. (2024). A spanning tree approach to social network sampling with degree constraints. Social Network Analysis and Mining, 14(101), 101.

Rezvanian, A., Jamshidi, S., & Gheisari, M. (2024). Advanced fusion of MTM-LSTM and MLP models for time series forecasting: An application for forecasting the solar radiation. Measurement: Sensors, 33, 101179.

Rezvanian, A., Vahidipour, S. M., & Saghiri, A. M. (2024). CaAIS: Cellular Automata-Based Artificial Immune System for Dynamic Environments. Algorithms, 17(1), 18.

Mashayekhi, Y., Rezvanian, A., & Vahidipour, S. M. (2023). A novel regularized weighted estimation method for information diffusion prediction in social networks. Applied Network Science, 8, 81.

Rezvanian, A., Vahidipour, S. M., & Meybodi, M. R. (2023). A new stochastic diffusion model for influence maximization in social networks. Scientific Reports, 13, 6122.

Conclusion

Dr. Alireza Rezvanian has made significant strides in the field of computer engineering and complex networks. His contributions to social network analysis and machine learning are profound, and his academic journey continues to influence the global research community. With his extensive experience, publication record, and ongoing research in dynamic optimization, Dr. Rezvanian remains a key figure in advancing the frontiers of computational sciences. His continued dedication to research and teaching ensures that his work will have a lasting impact in both academic and practical domains.