Muhammad Jawaid | Computer Science | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Muhammad Jawaid
De Montfort University Leicester,United Kingdom

Muhammad Jawaid, De Montfort University Leicester, United Kingdom, is a computer science researcher whose scholarly work encompasses medical imaging, machine learning, intelligent systems, and applied computational methods. His research record includes contributions to multimodal neuroimaging classification, coronary imaging analysis, and smart agriculture applications.

Muhammad Jawaid
Affiliation De Montfort University Leicester
Country United Kingdom
Scopus ID 57188570160
Documents 25
Citations 214
h-index 6
Subject Area Computer Science
Event International Academic Excellence Awards
Google Scholar ID DWR4rb8AAAAJ

Abstract

Muhammad Jawaid’s research profile reflects an interdisciplinary application of computational intelligence to complex scientific and biomedical problems. His documented publications include work on multimodal neuroimaging classification for autism spectrum disorder, non-calcified coronary plaque quantification, and smart agriculture systems. A 2026 Journal of Imaging article applies contrastive and transfer learning to aligned structural and functional neuroimaging data, demonstrating the relevance of machine learning to medical-image analysis.[1]

Keywords

Computer Science; Machine Learning; Medical Imaging; Neuroimaging; Artificial Intelligence; Image Classification; Coronary Imaging; Smart Agriculture; Transfer Learning; Research Innovation.

Introduction

The researcher is associated with computational research addressing practical challenges where data analysis and intelligent algorithms can support scientific interpretation. Recent work demonstrates applications ranging from neuroimaging classification to voxel-level analysis of coronary computed tomography data.[1][2] Earlier research also explored Internet-of-Things technologies and recurrent neural-network forecasting for agricultural monitoring.[3]

Research Profile

The supplied bibliometric profile records 25 documents, 214 citations, and an h-index of 6 in Scopus. These indicators provide a quantitative view of publication and citation activity, while individual publications provide additional evidence of the breadth and application-oriented character of the research.

Research Contributions

  • Multimodal neuroimaging classification using contrastive and transfer-learning strategies.[1]
  • Voxel-based computational analysis for non-calcified coronary plaque quantification in CT images.[2]
  • Application of IoT and neural-network forecasting techniques to smart agriculture.[3]

Publications

Recent publications include Contrastive and Transfer Learning for Aligned Multimodal Neuroimaging Classification of Autism Spectrum Disorder in Journal of Imaging (2026), and Non-calcified coronary plaque quantification in CT images using voxel-based descriptive features in Forensic Imaging (2026).[1][2] His earlier publication, Internet of Plants Application for Smart Agriculture, appeared in 2018.[3]

Research Impact

The reported citation profile indicates established scholarly visibility, while the publication topics show application across medical imaging and intelligent computational systems. The 2026 neuroimaging study reports multimodal classification experiments using an aligned feature-learning framework, while the coronary-imaging study investigates computational quantification of non-calcified plaque in CT data.[1][2]

Award Suitability

The documented combination of publication activity, citation indicators, and research spanning machine learning, medical imaging, and intelligent systems provides a substantive basis for consideration for an Innovative Research Award. The profile is particularly relevant to recognition frameworks that evaluate research originality, interdisciplinary application, documented scholarly output, and potential contribution to advancing computational approaches.

Conclusion

Muhammad Jawaid presents a computer science research profile characterized by applied machine learning, medical-image analysis, and intelligent computational applications. His reported bibliometric indicators and publication record support recognition of sustained scholarly activity and interdisciplinary research development.

References

  1. Vavekanand, R., Kumar, G., Jawaid, M. M., Memon, S. Q., & Kumar, T. (2026). Contrastive and Transfer Learning for Aligned Multimodal Neuroimaging Classification of Autism Spectrum Disorder. Journal of Imaging, 12(7), 328.
    https://doi.org/10.3390/jimaging12070328
  2. Memon, S. Q., Brown, J. M., & Jawaid, M. M. (2026). Non-calcified coronary plaque quantification in CT images using voxel-based descriptive features. Forensic Imaging, 44, 200664.
    https://doi.org/10.1016/j.fri.2025.200664
  3. Aliev, K., Moazzam, M. M., Narejo, S., Pasero, E., & Pulatov, A. (2018). Internet of Plants Application for Smart Agriculture. International Journal of Advanced Computer Science and Applications, 9(4), 421–429.
    https://doi.org/10.14569/IJACSA.2018.090458
  4. Elsevier. (n.d.). Scopus author details: Muhammad Moazzam Jawaid, Author ID 57188570160. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57188570160
  5. De Montfort University. (n.d.). School of Computer Science and Informatics. De Montfort University.

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