Deepika Lokesh | Computer Science | Academic Leadership Award

Published on by Academic Excellence

Academic Leadership Award

Deepika Lokesh
C byregowda Institute of Technology, India

Deepika Lokesh
Affiliation C byregowda Institute of Technology
Country India
Scopus ID 57444272400
Documents 3
Citations 6
h-index 2
Subject Area Computer Science
Event International Academic Excellence Awards

Deepika Lokesh is a researcher in Computer Science affiliated with C byregowda Institute of Technology, India. Her documented research interests include wireless sensor networks, energy-efficient target tracking, routing design, solar-powered mobility infrastructure, and machine-learning-assisted electromagnetic applications. Her publication record demonstrates a multidisciplinary approach connecting network optimization, intelligent systems, sustainable engineering, and emerging communication technologies.

Abstract

Deepika Lokesh’s research portfolio reflects sustained work in computer science with particular attention to wireless sensor networks and energy-aware intelligent systems. Her studies address multi-sensory scheduling, routing efficiency, latency reduction, and target-tracking applications, while later work extends toward solar-based charging infrastructure and machine-learning algorithms for sub-6G applications. These topics are relevant to efficient distributed computing, wireless communication, sustainable engineering, and intelligent network design. [1] [2]

Keywords

Wireless sensor networks, target tracking, energy-efficient routing, low-latency routing, multi-sensory scheduling, solar charging, machine learning, sub-6G applications, computer science, intelligent communication systems.

Introduction

Wireless sensor networks require efficient communication strategies because sensing nodes commonly operate under constrained energy resources. Research on target tracking therefore considers scheduling, routing, latency, and energy consumption as interconnected design factors. Lokesh’s published studies address these challenges through energy-efficient multi-sensory scheduling and routing approaches. [1] [3]

Research Profile

The available publication record indicates a research trajectory centered on computational and engineering problems. The portfolio combines wireless sensor network optimization with applications involving sustainable transportation infrastructure and machine-learning-enabled frequency selective surface design. The Scopus record supplied for this profile reports 3 documents, 6 citations, and an h-index of 2.

Research Contributions

  • Energy-aware multi-sensory scheduling for target tracking in wireless sensor networks. [1]
  • Energy-efficient and low-latency routing designs for target-tracking applications. [2] [3]
  • Design of a solar-based mobile vehicle charging station, linking engineering research with sustainable mobility. [4]
  • Application of machine-learning algorithms to dual-square frequency selective surfaces for sub-6G applications. [5]

Publications

1. “Energy efficient target tracking method for multi-sensory scheduling in wireless sensor networks,” International Journal of Innovative Technology and Exploring Engineering.[1]

2. “Energy Efficient Routing Design for Target Tracking in Wireless Sensor Network,” WSEAS Transactions on Information Science and Applications. [2]

3. “Energy Efficient Low Latency Routing Design for Target Tracking Applications of Wireless Sensor Network,” International Journal of Circuits, Systems and Signal Processing. [3]

4. “Design and Developed of a Solar based mobile vehicle charging station,” Gradiva Review Journal. [4]

5. “Machine learning Algorithms for Enhancement of a Dual Square FSS for Sub 6G Applications,” International Journal of Science Research in Engineering and Management. [5]

Research Impact

The research addresses practical challenges in networked sensing and communication, particularly the need to balance energy consumption, routing performance, latency, and tracking reliability. The additional work on solar charging and machine learning indicates application-oriented research extending beyond a single technical problem. The reported Scopus metrics provide a quantitative snapshot of the indexed research record and should be interpreted alongside publication quality, relevance, and broader scholarly contributions.

Award Suitability

For the International Academic Excellence Awards, the Academic Leadership Award category can be considered in relation to the documented evidence of research activity, publication output, and technical focus. Lokesh’s work presents identifiable contributions in energy-efficient wireless sensor networks and related intelligent engineering applications. The portfolio provides a reasonable scholarly basis for recognition, subject to the award’s formal evaluation criteria and independent verification of submitted credentials.

Conclusion

Deepika Lokesh’s research profile demonstrates work at the intersection of computer science, wireless sensor networks, intelligent routing, sustainable engineering, and machine-learning applications. Her publications document a progression from energy-efficient target tracking toward broader engineering and emerging communication applications. The available bibliographic and citation information provides a concise basis for academic recognition within the International Academic Excellence Awards.

References

  1. Lokesh, Deepika. (n.d.). Energy efficient target tracking method for multi-sensory scheduling in wireless sensor networks. International Journal of Innovative Technology and Exploring Engineering, 9(3), 1638–1644.
    https://doi.org/10.35940/ijitee.c8529.019320
  2. Lokesh, Deepika. (2022). Energy Efficient Routing Design for Target Tracking in Wireless Sensor Network. WSEAS Transactions on Information Science and Applications, 19, 132–137.
    https://doi.org/10.37394/23209.2022.19.13
  3. Lokesh, Deepika. (2022). Energy Efficient Low Latency Routing Design for Target Tracking Applications of Wireless Sensor Network. International Journal of Circuits, Systems and Signal Processing, 16, 1018–1026.
    https://doi.org/10.46300/9106.2022.16.124
  4. Lokesh, Deepika. (2023). Design and Developed of a Solar based mobile vehicle charging station. Gradiva Review Journal, 9(8), 565–568.
  5. Lokesh, Deepika. (2024). Machine learning Algorithms for Enhancement of a Dual Square FSS for Sub 6G Applications. International Journal of Science Research in Engineering and Management, 8(8).
    https://doi.org/10.55041/IJSREM35833
  6. Elsevier. (n.d.). Scopus author details: Deepika Lokesh, Author ID 57444272400. Scopus.
    https://www.scopus.com/pages/authors/57444272400

SYED NAVAZ A S | Computer Science | Research Excellence Award

Published on by Academic Excellence

Dr. SYED NAVAZ A S | Computer Science | Research Excellence Award

Shine & Inspire Academy | India

Dr. A. S. Syed Navaz is an accomplished academician, researcher, and educational leader with over 14 years of teaching experience at both undergraduate and postgraduate levels in the field of Computer Science and Applications. He holds a Ph.D. in Computer Science from Prist University, Thanjavur, where his doctoral research focused on Layer-Based and Flow-Based Channel Assignment in Tree-Structured Wireless Sensor Networks for Fast Data Collection, reflecting his strong expertise in networking and data communication systems. Beyond academia, Dr. Syed Navaz plays prominent leadership roles as Publisher and Chief Editor of the International Organization of Innovative Research & Publishers (IOIRP) and as Managing Director of Shine & Inspire Academy, where he supports research, Ph.D. guidance, publications, patents, entrepreneurship training, and motivational and soft-skill development. He has also successfully mobilized government funding through DST–NSTEDB for multiple Entrepreneurship Awareness Camps, demonstrating his commitment to innovation and societal development. With multidisciplinary expertise spanning education, research, entrepreneurship, blockchain consulting, and life advisory services, Dr. A. S. Syed Navaz continues to make impactful contributions to academic excellence, research advancement, and human capacity building.

 

Citation Metrics (Scopus)

160
80
40
10
0

Citations
151

Documents
10

h-index
6

Citations

Documents

h-index


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Featured Publications

Entropy Based Anomaly Detection System to Prevent DDoS Attacks in Cloud
– International Journal of Computer Applications, 2013
Data Visualization: Enhancing Big Data More Adaptable and Valuable
– International Journal of Applied Engineering Research, 2016
Face Recognition Using Principal Component Analysis and Neural Networks
– International Journal of Computer Networking, Wireless and Mobile Computing, 2013
Human Resource Management System
– IOSR Journal of Computer Engineering, 2013
Flow Based Layer Selection Algorithm for Data Collection in Tree Structure Wireless Sensor Networks
– International Journal of Applied Engineering Research, 2016

Fengrui Hao | Computer Science | Best Researcher Award

Published on by Academic Excellence

Dr. Fengrui Hao | Computer Science | Best Researcher Award

Jinan University, China

Dr. Fengrui Hao is an emerging researcher in the field of computer science, currently pursuing his Ph.D. in Cyber Security at the School of Information Science and Technology, Jinan University, Guangzhou, China. He holds a B.S. degree in Information Management and Information Systems and an M.S. degree in Computer Technology from Guilin University of Electronic Technology, which laid the foundation for his deep engagement with advanced computing and security research. His primary focus lies in adversarial machine learning and trustworthy artificial intelligence, where he has made significant contributions to strengthening AI systems against vulnerabilities and ensuring fairness, transparency, and robustness in their applications. With more than ten publications in prestigious journals and conferences such as IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Industrial Informatics (TII), and IEEE Transactions on Knowledge and Data Engineering (TKDE), Dr. Hao has established himself as a promising scholar. His research contributions include the development of novel attack and defense mechanisms, fairness-aware algorithms, and privacy-preserving techniques for graph data publishing, all of which are shaping the foundation of secure and ethical AI. His work has been recognized through two completed or ongoing research projects, one consultancy project, and an impressive record of sixteen patents under process. With a citation index of twenty, his influence in the field continues to expand as he pursues innovative research directions. Dr. Hao’s dedication to advancing adversarial learning and trustworthy AI reflects his vision of creating resilient, secure, and human-centered AI technologies for the future.

Profiles: Scopus | Orcid

Featured Publications

  • FBA: Fairness Backdoor Attack on Graph Neural Networks – IEEE Transactions on Dependable and Secure Computing, 2025, DOI: 10.1109/TDSC.2025.3563668

  • dK-DGDP: A Differential Privacy Approach on Directed Social Network Graphs – Computers & Security, 2025, DOI: 10.1016/j.cose.2025.104647

  • GCPA: GAN-Based Collusive Poisoning Attack in Federated Recommender Systems – IEEE Transactions on Knowledge and Data Engineering, 2025, DOI: 10.1109/TKDE.2025.3579807

  • CBAs: Character-level Backdoor Attacks against Chinese Pre-trained Language Models – ACM Transactions on Privacy and Security, 2024, DOI: 10.1145/3678007

  • Collusive Model Poisoning Attack in Decentralized Federated Learning – IEEE Transactions on Industrial Informatics, 2024, DOI: 10.1109/TII.2023.3342901