Naresh Kumar Thapa K | Digital Signatures | Best Researcher Award

Dr. Naresh Kumar Thapa K | Digital Signatures | Best Researcher Award

Assistant Professor at Sathyabama Institute of Science and Technology, India

Dr. Naresh Kumar Thapa K. is an Assistant Professor at R.M.K. Engineering College, specializing in communication theory, wireless communication, multimedia compression, and communication networks. With over a decade of academic experience, Dr. Thapa has made significant contributions to research in AI, machine learning, cybersecurity, and 5G/6G wireless networks. He has published numerous papers in reputed journals and conferences and has applied for multiple patents related to emerging technologies. Dr. Thapa has played an instrumental role in various academic processes, including NBA, ABET, and NAAC accreditation, and has been a key contributor to the development of foreign language programs and international collaborations. His current research includes anomaly detection in network traffic and security architectures for next-generation networks. Additionally, Dr. Thapa has guided students in national-level competitions, such as the Smart India Hackathon, and is dedicated to furthering research in cutting-edge technological advancements.

Education:

Dr. Naresh Kumar Thapa K. holds a strong educational background in communication systems, cybersecurity, and related fields. He completed his undergraduate studies in Electronics and Communication Engineering, followed by a Master’s degree in the same discipline. Dr. Thapa further advanced his academic qualifications by pursuing a Ph.D., with a focus on communication technologies and cybersecurity, from a reputed institution. Throughout his academic journey, Dr. Thapa has honed his skills in programming languages such as C, C++, Python, Matlab, and NS2, as well as in operating systems like Windows and Linux. His academic expertise has greatly contributed to his ability to lead and innovate in the areas of AI, machine learning, and wireless communication. His education has laid a solid foundation for his current role as an Assistant Professor at R.M.K. Engineering College, where he applies his extensive knowledge in teaching and research.

Professional Experience:

Dr. Naresh Kumar Thapa K. has extensive professional experience in academia, currently serving as an Assistant Professor at R.M.K. Engineering College since June 2023. He has taught a wide range of subjects, including Intelligent Robotics and Drones, 5G and 6G Wireless Networks, and AI Lab and Advanced Robotics Lab. Dr. Thapa has been involved in significant research projects, including a proposal titled “Study of Anomaly Detection using Network Traffic Generated by Internet-Enabled Devices for Cyber Security,” which was selected for funding under the Telecom Technology Development Fund. Previously, from 2018 to 2023, he was an Assistant Professor at R.M.K. Engineering College, where he played a pivotal role in handling subjects such as Analog and Digital Communication, Wireless Communication, and Multimedia Compression and Communication. He applied for two patents and published eight papers during this time. Dr. Thapa also contributed significantly to the department by assisting with NBA and NAAC accreditation processes and coordinating the Center for Foreign Language program, establishing partnerships with Japanese companies. Prior to his tenure at R.M.K. Engineering College, he worked at Velammal Engineering College from 2013 to 2018, where he started his academic career, handling subjects such as Digital Electronics and Wireless Communication, and coordinating various departmental events.

Research Interests:

Dr. Naresh Kumar Thapa K.’s research interests lie at the intersection of Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. He is particularly focused on leveraging AI and ML techniques to enhance network security, with a specific interest in anomaly detection and intrusion detection systems for wireless and IoT networks. His work also explores advanced topics in 5G and 6G wireless networks, emphasizing security frameworks for next-generation communication systems. Additionally, Dr. Thapa has shown keen interest in multimedia compression, wireless communication, and communication networks, and has contributed to the development of innovative systems and solutions in these areas. His ongoing research aims to bridge the gaps in AI-driven security protocols and explore the use of emerging technologies like blockchain for securing wireless sensor networks.

Awards and Honors:

Dr. Naresh Kumar Thapa K. has received several notable awards and honors in recognition of his contributions to the fields of communication, AI, and cybersecurity. Among his achievements, he was awarded Best Paper at the International IEEE-ICCIC Conference in 2014 for his work on differential amplifier-based speed monitoring circuits for airport and production industries. His research on blockchain-based identity authentication and traffic sign identification systems using AI has garnered widespread recognition, with papers accepted at prestigious international conferences such as IEEE-ICECAA 2022 and IEEE-ICERCS 2023. Furthermore, Dr. Thapa’s work on cybersecurity and anomaly detection has earned him accolades in the academic community, enhancing his reputation as a leading researcher in the field.

Skills:

Dr. Naresh Kumar Thapa K. possesses a diverse and comprehensive skill set that spans across various areas of technology and engineering. He is proficient in operating systems such as Windows and Linux, and has expertise in programming languages including C, C++, Python, Matlab, and NS2. His technical skills extend to areas of artificial intelligence (AI) and machine learning (ML), where he applies advanced algorithms for data analysis and cybersecurity solutions. Additionally, Dr. Thapa is adept in wireless communication, multimedia compression, and communication networks, with a focus on 5G and 6G technologies. His strong analytical capabilities and hands-on experience in cybersecurity, particularly in anomaly detection and traffic analysis, further strengthen his technical proficiency.

Publication Top Noted:

  • A novel enhanced security architecture for sixth generation (6G) cellular networks using authentication and acknowledgement (AA) approach
    • Authors: V, S.P., Albert, A.J., Thapa, K.N.K., Krishnaprasanna, R.
    • Journal: Results in Engineering, 2024, Vol. 21, Article 101669
    • Citations: 2
  • Implementation of Transmission Line Fault Detection System using Long Range Wireless Sensor Networks
    • Authors: Raja, P.D.A., Thapa, K.N.K., Harsha, K.S.S., Krishna, K.S., Sivakumar, A.
    • Journal: International Journal on Recent and Innovation Trends in Computing and Communication, 2023, 11(5), pp. 77–84
    • Citations: 1
  • Design and Development of Artificial Intelligence based Real-Time Traffic Sign Identification Scheme using Novel Learning Strategy
    • Authors: Tamilselvi, M., Iyswariya, A., Thapa, K.N.K., Vinithra Banu, T., Pandi, V.S.
    • Conference: 1st International Conference on Emerging Research in Computational Science (ICERCS 2023)
    • Citations: 0
  • A Novel Framework in Scheduling Packets for Energy-Efficient Bandwidth Allocation in Wireless Networks
    • Authors: Sivajothi, E., Jayaudhaya, J., Santhiya, S., Kamatchi, S., Ganapathy, N.B.S.
    • Conference: 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC 2023), pp. 1311–1316
    • Citations: 0
  • A Comprehensive Analysis for Implementing IoT on LTE Systems
    • Authors: Kumar Thapa, K.N., Malini, A.H., Kalaimani, A., Srinivasan, S.
    • Conference: International Conference on Applied Artificial Intelligence and Computing (ICAAIC 2022), pp. 502–507
    • Citations: 4
  • Malicious Traffic classification Using Long Short-Term Memory (LSTM) Model
    • Authors: Thapa, K.N.K., Duraipandian, N.
    • Journal: Wireless Personal Communications, 2021, 119(3), pp. 2707–2724
    • Citations: 22
  • Differential Amplifier Based Speed Monitoring Circuit for Airport and Production Industry
    • Authors: Naresh Kumar Thapa, K., Kalaivani, S., Vanaja, S., Joselin Jeya Sheela, J., Deepika, Y.
    • Conference: 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics, and Cloud), 2021, pp. 1761–1764
    • Citations: 1
  • Post disaster damage estimation using integrated GPS sensor network & GIS
    • Authors: John Samuel Raj, K., Naresh Kumar Thapa, K., Balakrishnan, R.
    • Conference: IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2016), pp. 1234–1238
    • Citations: 3
  • Digital signature using stationary wavelet transform based watermarking for robots
    • Authors: Thapa, K.N.K., Kumari, P., Kantham, L.
    • Conference: IEEE International Conference on Computational Intelligence and Computing Research (IEEE ICCIC 2014), 2015, pp. 307–312
    • Citations: 0

Conclusion:

Dr. Naresh Kumar Thapa K. is an exemplary academic and researcher with a proven track record in teaching, research, and innovation. His contributions to the fields of communication, AI, cybersecurity, and IoT have had a significant impact on both his institution and the broader academic and research communities. His research outputs, including publications in high-impact journals, patents, and successful grant proposals, demonstrate his ability to address contemporary technological challenges. Therefore, Dr. Thapa is a highly deserving candidate for the Best Researcher Award, owing to his impressive research achievements, leadership in academia, and dedication to student success.

Yonghong Wang | Access Control | Best Researcher Award

Dr. Yonghong Wang | Access Control | Best Researcher Award

Lecturer at Xinzhou Normal University, China

Dr. Yonghong Wang is a Lecturer in Computer Science at Xinzhou Normal University, where he has taught since 2007. He holds a B.S. in Computer Science and Technology from Xinzhou Normal University, an M.S. in Civil and Commercial Law from Shanxi University of Finance and Economics, and an M.S. in Software Engineering from North University of China. Currently pursuing a Ph.D. in Information Systems at INTI International University, Dr. Wang specializes in computer vision, network security, and the Internet of Things. He has published extensively in SCI and Scopus-indexed journals and is actively engaged in both academic and industry research projects.

Education:

Dr. Yonghong Wang holds a Bachelor of Science degree in Computer Science and Technology from Xinzhou Normal University, awarded in 2007. He pursued further studies and earned a Master of Science in Civil and Commercial Law from Shanxi University of Finance and Economics in 2015. Additionally, Dr. Wang completed a second Master’s degree in Software Engineering at North University of China in 2016. Currently, he is pursuing a Ph.D. in Information Systems at INTI International University, a program he began in 2020. His educational background is multidisciplinary, integrating expertise in computer science, law, and software engineering.

Professional Experience:

Dr. Yonghong Wang has extensive professional experience as a Lecturer in Computer Science at Xinzhou Normal University, a position he has held since 2007. In this role, he has been responsible for teaching various computer science courses, mentoring students, and contributing to curriculum development. Over the years, he has actively participated in research projects, leading four completed projects and currently overseeing two ongoing projects. Dr. Wang has also engaged in consultancy and industry projects, collaborating with various organizations to apply his expertise in computer vision, network security, and the Internet of Things. His involvement in both academia and industry showcases his commitment to bridging theoretical knowledge with practical applications.

Research Interests:

Dr. Yonghong Wang’s research interests encompass a diverse range of fields, primarily focusing on computer vision, network security, and the Internet of Things (IoT). His work in computer vision explores innovative methods for image processing and analysis, aiming to enhance machine perception capabilities. In the realm of network security, Dr. Wang investigates strategies to protect data integrity and confidentiality in increasingly complex digital environments. Additionally, his research on the Internet of Things emphasizes the integration of smart devices and systems, addressing challenges related to security and interoperability. Through his multifaceted research, Dr. Wang aims to contribute to advancements in technology and improve practical applications in these critical areas.

Skills:

Dr. Yonghong Wang possesses a robust skill set that reflects his expertise in multiple domains. He has strong technical proficiency in computer programming and software development, which underpins his work in computer science and software engineering. His skills in computer vision enable him to implement advanced algorithms for image analysis and processing, while his knowledge of network security equips him to devise effective strategies for safeguarding digital information. Dr. Wang is also adept at data analysis, which is essential for his research in the Internet of Things, where he addresses challenges related to data management and device integration. Additionally, his effective communication and collaboration skills enhance his ability to work on interdisciplinary projects and contribute to both academic and industry partnerships.

Conclusion:

Based on his academic and professional achievements, Dr. Wang Yonghong is a suitable candidate for the Best Researcher Award. His work reflects a blend of technical proficiency and practical impact, especially in the fields of computer vision, network security, and IoT. His academic publications, industry engagements, and commitment to ongoing research affirm his qualifications for this award.

Publication Top Noted:

Federated deep learning for anomaly detection in the internet of things

  • Authors: X. Wang, Y. Wang, Z. Javaheri, L. Almutairi, N. Moghadamnejad, O.S. Younes
  • Journal: Computers and Electrical Engineering
  • Volume: 108
  • Article ID: 108651
  • Year: 2023
  • Citations: 51

Attack detection analysis in software-defined networks using various machine learning methods

  • Authors: Y. Wang, X. Wang, M.M. Ariffin, M. Abolfathi, A. Alqhatani, L. Almutairi
  • Journal: Computers and Electrical Engineering
  • Volume: 108
  • Article ID: 108655
  • Year: 2023
  • Citations: 11

WSLC: Weighted semi-local centrality to identify influential nodes in complex networks

  • Authors: X. Wang, M. Othman, D.A. Dewi, Y. Wang
  • Journal: Journal of King Saud University – Computer and Information Sciences
  • Volume: 36
  • Issue: 1
  • Article ID: 101906
  • Year: 2024
  • Citations: 4

Enhancing Enterprise Value Creation Through Intelligent Digital Transformation of the Value Chain: A Deep Learning and Edge Computing Approach

  • Authors: R. Liu, Y. Wang
  • Journal: Journal of the Knowledge Economy
  • Pages: 1-19
  • Year: 2024
  • Citations: 1

Face Recognition Technology Based on Deep Learning Algorithm for Smart Classroom Usage

  • Authors: Y.H. Wang, W.O. Choo, X.F. Wang
  • Journal: Journal of Engineering Science and Technology
  • Volume: 18
  • Pages: 39-47
  • Year: 2023
  • Citations: 1

DFRDRL: A dynamic fuzzy routing algorithm based on deep reinforcement learning with guaranteed latency and bandwidth for software-defined networks

  • Authors: Y. Wang, M. Othman, W.O. Choo, R. Liu, X. Wang
  • Journal: Journal of Big Data
  • Volume: 11
  • Issue: 1
  • Article ID: 150
  • Year: 2024