Prof. Jun Li | Mobile Networks | Best Researcher Award

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Prof. Jun Li | Mobile Networks | Best Researcher Award

Prof. Jun Li, Southeast University, China

Jun Li is a distinguished professor at Southeast University’s School of Information Science and Engineering. A prolific researcher in engineering with a career spanning over two decades, he has contributed significantly to advancements in Industrial Internet, 6G communications, and data privacy in federated learning. Jun Liā€™s pioneering work has been cited over 15,000 times, showcasing his profound impact on these fields. He previously served as a professor at Nanjing University of Science and Technology and held research positions at esteemed institutions such as Princeton University and the University of Sydney. His accomplishments include the Youth Thousand Talents Program and AI Digital Craftsman Award. As an active member of Chinaā€™s technical communities, Jun Li is highly regarded for his innovative research, esteemed publications, and ongoing contributions to the development of intelligent systems and industrial data solutions.

Professional Profile

Google Scholar

suitability summary of best reseacher award

Jun Li stands as a highly qualified candidate for the Best Researcher Award, demonstrating a blend of extensive research contributions, leadership, and technological advancements across domains like industrial internet, wireless communications, and artificial intelligence. As a professor in the School of Information Science and Engineering at Southeast University, his influence extends through both his innovative research and his commitment to developing critical solutions in fields that are vital to technological advancement and industrial applications.

EducationĀ 

Jun Li holds a Ph.D. in Engineering from Shanghai Jiao Tong University (2009), where he specialized in advanced wireless communication systems. Prior to this, he earned his M.S. in Engineering from Nanjing University of Science and Technology (2004), focusing on foundational engineering principles that later influenced his work in Industrial Internet and data privacy. His academic journey began with a B.S. in Engineering from Jilin University (2001), providing a strong theoretical base in engineering. This diverse educational background across three premier Chinese universities has shaped Jun Liā€™s expertise in systems integration and collaborative cloud-edge systems for industrial applications. His academic foundations underpin his innovative approaches to developing new methods in 6G wireless technologies, privacy-preserving systems, and industrial IoT, which continue to influence his teaching and research at Southeast University and beyond.

Experience

Currently a professor at Southeast Universityā€™s School of Information Science and Engineering (2024ā€“present), Jun Li has previously held a series of esteemed positions. He was a professor at Nanjing University of Science and Technology (2015ā€“2024), where he advanced research in Industrial Internet and next-generation communication systems. As a visiting scholar at Princeton University (2018ā€“2019), he collaborated under Vincent Poor, exploring innovative data privacy techniques in federated learning. Earlier, he was a research fellow at the University of Sydney (2012ā€“2015), where he contributed to projects under Branka Vucetic on cloud-based systems for industrial IoT applications. His postdoctoral research at the University of New South Wales (2009ā€“2012) further deepened his expertise in wireless communication. With a brief role at Shanghai Bell R&D Center, Jun Liā€™s diverse experience positions him as a leader in both industrial applications and academic research, emphasizing the practical and scalable development of advanced technological systems.

Awards and HonorsĀ 

Jun Li’s career is marked by numerous prestigious awards, including the Youth Thousand Talents Program by the Ministry of Organization (2016) and the Distinguished Professor title from Jiangsu Province (2015). His innovative contributions have also earned him the Excellent Scientist Award from the Chinese Institute of Electronics (2022) and the Global Top 2% Scientist recognition (2023). In the AI field, he received the AI Digital Craftsman Award from the Chinese Association for Artificial Intelligence (2023). His academic contributions have garnered several competitive awards, including multiple Best Paper Awards from IEEE conferences and a top distinction from the National Industrial Internet Innovation Competition (2023). Jun Liā€™s accolades reflect his prominent role in advancing digital innovation and underscore his commitment to high-impact, interdisciplinary research that addresses key challenges in engineering and industrial communication technologies.

Research Focus

Jun Liā€™s research is centered on integrating advanced wireless communication with the Industrial Internet, focusing on 6G and privacy-preserving technologies for data management. His recent projects address the development of Intelligent Collaborative Cloud-Edge Systems tailored for industrial applications, aiming to enhance real-time data processing and decision-making in large-scale IoT networks. His work in federated learning emphasizes privacy protection, particularly in sensitive industrial settings, where secure data flow and efficient resource allocation are paramount. Jun Li is also pioneering efforts in positioning systems for asset management, optimizing data flow, and ensuring robust privacy protocols in wireless networks. His research interests extend to high-performance computing solutions for industrial data and cutting-edge strategies in collaborative AI applications, reflecting a comprehensive approach to advancing the industrial IoT ecosystem through integrative, secure, and intelligent technologies.

Ā Publication Top Notes

  • Federated Learning with Differential Privacy: Algorithms and Performance Analysis
    • Cited by: 1801
  • Federated Learning for Internet of Things: A Comprehensive Survey
    • Cited by: 927
  • Simultaneous Wireless Information and Power Transfer (SWIPT): Recent Advances and Future Challenges
    • Cited by: 899
  • 6G Internet of Things: A Comprehensive Survey
    • Cited by: 852
  • Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
    • Cited by: 504

Mrs. Dipali Bansal | Mobile Networks Awards | Best Researcher Award

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Mrs. Dipali Bansal | Mobile Networks Awards | Best Researcher Award

Mrs. Dipali Bansal , Amity University,Noida , India

Mrs. Dipali Bansal is a dedicated academic currently pursuing her Ph.D. in Smart Antenna 5G at Amity University, Noida. She holds an M.Tech in Digital Communication from Rajasthan Technical University and a B.E. in Electronics & Communication Engineering from Kautilya Institute of Technology & Engineering, Jaipur. With a strong academic record, including being a gold medalist and securing first rank in her M.Tech, Mrs. Bansal has also contributed significantly to research, with publications in IEEE conferences and SCI-indexed journals. Her professional experience includes a tenure as Assistant Professor at Rajasthan Institute of Engineering & Technology, Jaipur, where she was recognized for her teaching excellence. Her research interests encompass advanced communication technologies, particularly in the areas of antenna design and data hiding techniques. Additionally, Mrs. Bansal has demonstrated a commitment to co-curricular activities, having been an active participant and leader in cultural events during her academic journey.

Professional Profile:

Scopus

Orcid

Ā šŸŽ“Ā Ā Education:

Mrs. Dipali Bansal is currently pursuing her Ph.D. in Smart Antenna 5G at Amity University, Noida. She completed her M.Tech in Digital Communication from Rajasthan Technical University, Kota, Rajasthan, in 2018, achieving a commendable 68.86%. She holds a B.E. in Electronics & Communication Engineering from Kautilya Institute of Technology & Engineering, Jaipur, where she graduated in 2011 with an impressive 75.97%. Prior to her undergraduate studies, she completed her HSC from New Modern Senior Secondary School, Kotputli, under the Rajasthan Board in 2007, with 72.46%. She completed her SSC in 2005 from Govt. Girls Senior Secondary School, Kotputli, also under the Rajasthan Board, with 73.17%.

šŸ¢Work Experience:

At Amity University, where Mrs. Dipali Bansal is pursuing her Ph.D., she has made notable research contributions, including three conference papers published in IEEE and Scopus Indexed journals. One of these papers earned her the Best Female Student in Antenna Track award. She has also published two journal papers, one in the IETE Journal of Research (Taylor & Francis, SCI Indexed) and another in Multimedia Tools and Applications (Springer, SCI Indexed). Additionally, she received a copyright for her work titled “Optimized Beamformation Selection By Using Bilateral Antenna Pattern Selection (Baps) With Adaptive Beamforming In 5G System”.

Ā šŸ†Awards and Achievements

Mrs. Dipali Bansal has been recognized for her exceptional academic and extracurricular achievements throughout her educational journey. She was a gold medalist for academic excellence in her B.Tech ECE at Kautilya Institute of Technology & Engineering, Jaipur (2007-2011), and received an academic scholarship from the MHRD for her M.Tech based on her GATE qualification (2015-17). She secured first rank in her M.Tech in Digital Communications in 2018. Additionally, she was honored with the Student of the Year Award in 2011 for her outstanding academic and co-curricular performance during her B.E. ECE. While pursuing her Ph.D. at Amity University, she won the Best Female Student in Antenna Track Award for a conference paper. She also demonstrated leadership skills as the Student Coordinator for Cultural Activities at Kautilya Institute of Technology & Engineering, Jaipur (2009-2011), and won multiple cultural competitions at the inter-college level.

Publication Top Notes:

  • Design a Bow-Tie Antenna for Multiband Applications
    • Authors: Kumari, S.; Awasthi, Y.K.; Bansal, D.
  • Robust Feature Extraction and Recognition Model for Automatic Speech Recognition System on News Report Dataset
    • Authors: Mendiratta, S.; Turk, N.; Bansal, D.
    • Citations: 1
  • Image Forgery Detection and Localization Using Block Based and Key-Point Based Feature Matching Forensic Investigation
    • Authors: Monika; Bansal, D.; Passi, A.
    • Citations: 1
  • Proposed Multiband Fractal Monopole Antenna for WLAN and WiMax Applications
    • Authors: Kumari, S.; Awasthi, Y.K.; Bansal, D.
    • Citations: 4
  • A Miniaturized Circularly Polarized Multiband Antenna for Wi-Max, C-Band & X-Band Applications
    • Authors: Kumari, S.; Awasthi, Y.K.; Bansal, D.
    • Citations: 5

 

 

 

Prof Dr. Alvaro Barradas | Routing | Best Researcher Award

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Prof Dr. Alvaro Barradas | Routing | Best Researcher Award

Prof Dr. Alvaro Barradas, University of Algarve, Portugal

Dr. Alvaro Barradas holds a PhD in Electronic Engineering and Computing (2009/11) and a Bachelor’s in Computer Science Management from the University of Algarve. šŸŽ“ With a teaching career spanning 2013 to 2019 at the same university, he specialized in Electrotechnical Engineering, Electronics, and Informatics. šŸ« Dr. Barradas is a prolific researcher with 15 articles and a book to his credit, focusing on Substation Automation Systems, Interoperability, and Routing Algorithms. šŸ“š Currently affiliated with the University of Algarve’s Center for Optoelectronics, Electronics, and Telecommunications, his projects include SensWorking, blending IoT with biological monitoring, and optimizing wireless mesh and sensor networks.

šŸŒĀ Professional Profiles :

Scopus

Orcid

šŸŽ“ Education:

Dr. Alvaro Barradas completed his PhD in Electronic Engineering and Computing in 2009/11 from the University of Algarve, specializing in Computer Systems Architecture. He also holds a Bachelor’s degree in Computer Science Management from the University of Algarve.

šŸ« Teaching Experience:

With a career spanning from 2013 to 2019, Dr. Barradas served as an Assistant Professor at the University of Algarve, Portugal, imparting knowledge in the fields of Electrotechnical Engineering, Electronics, and Informatics.

šŸ“š Research Focus:

Dr. Barradas has contributed significantly to the academic community with 15 articles published in specialized journals and 1 book. His research interests include Substation Automation Systems, Interoperability, Computer Networks, Optical Networks, and Routing Algorithms.

šŸŒ Affiliation & Projects:

Currently affiliated with the University of Algarve’s Center for Optoelectronics, Electronics, and Telecommunications, Dr. Barradas is involved in projects such as SensWorking, aiming to merge IoT with biological monitoring. He has also been part of strategic projects focusing on wireless mesh and sensor networks optimization.

Scopus Metrics:

  • šŸ“Ā Publications: 24 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 148 citations for his publications, reflecting the widespread impact and recognition of Dr. Mahrokhā€™s research within the academic community.

Publications Top Notes :

  1. DAG-Coder: Directed Acyclic Graph-Based Network Coding for Reliable Wireless Sensor Networks
    • Published in IEEE Access in 2020.
    • 6 citations.
  2. Design of network coding based reliable sensor networks
    • Published in Ad Hoc Networks in 2019.
    • 8 citations.
  3. A Bounded Heuristic for Collection-Based Routing in Wireless Sensor Networks
    • Published in IEEE Access in 2018.
    • 2 citations.
  4. GACN: Self-Clustering Genetic Algorithm for Constrained Networks
    • Published in IEEE Communications Letters in 2017.
    • 18 citations.
  5. Resource design in constrained networks for network lifetime increase
    • Published in IEEE Internet of Things Journal in 2017.
    • 10 citations.