FedEmerge: An Entropy-Guided Federated Learning Method for Sensor Networks and Edge Intelligence
Khan, K., “FedEmerge: An Entropy-Guided Federated Learning Method for Sensor Networks and Edge Intelligence,” Sensors (MDPI), vol. 25, no. 12, Art. no. 3728, Jun. 2025, doi: 10.3390/s25123728.
Sign-Entropy Regularization for Personalized Federated Learning
Khan, K., “Sign-Entropy Regularization for Personalized Federated Learning,” Entropy (MDPI), vol. 27, no. 6, Art. no. 601, Jun. 2025, doi: 10.3390/e27060601.
Enhancing examination integrity through constructivist and reflective practices
Elibox, W., and Khan, K., “Enhancing examination integrity through constructivist and reflective practices: a case study of the science faculty at a commonwealth university,” Quality Assurance in Education (Emerald), vol. 33, no. 4, pp. 554–569, May 2025, doi: 10.1108/QAE-10-2024-0226.
The INSPIRE framework for transformative and inclusive education
Elibox, W., Khan, K., Khan, A., Smart, S., and Cockburn, B. N., “The INSPIRE framework for transformative and inclusive education: a case study of the science faculty at a Commonwealth university,” Quality Assurance in Education (Emerald), vol. 33, no. 4, pp. 585–602, May 2025, doi: 10.1108/QAE-02-2025-0037.
Cucurbit Foliar Disease Identification with Deep Learning and XGBoost: A ResNet50 Approach
Vijayanandh Rajamanickam, Annika Boodoosingh, Quan Afoon, Elijah Lewis and Jayaraj Jayaraman, “Cucurbit Foliar Disease Identification with Deep Learning and XGBoost: A ResNet50 Approach”, Caribbean Journal of Science, 55(2) : 533-545, 2025. https://doi.org/10.18475/cjos.v55i2.a22
A Dynamic Highlight Function for the BrightStart Reading Tutor
Jared Heeralal, Avinash Roopnarine, Phaedra Mohammed and Vijayanandh Rajamanickam, “A Dynamic Highlight Function for the BrightStart Reading Tutor”, Journal of Arts Science and Technology, Publication of the University of Technology, Jamaica, Vol. 17, No. 1, 102 – 124, 2025.
Biofilms Exposed: Innovative Imaging and Therapeutic Plat-forms for Persistent Infections
Manasi Haval, Chandrashekar Unkal, Shridhar C. Ghagane, Bijay Raj Pandit, Esther Daniel, Parbatee Siewdass, Kingsley Ekimeri, Vijayanandh Rajamanickam, Angel Justiz-Vaillant, Kathy-Ann A. Lootawan, Fabio Muniz De Oliveira, Nivedita Bashetti, Tatheer Alam Naqvi, Arun Shettar, Pramod Bhasme, “Biofilms Exposed: Innovative Imaging and Therapeutic Plat-forms for Persistent Infections”, MDPI-Antibiotics, 14(9), 865; 2025. https://doi.org/10.3390/antibiotics14090865
Enhancing Crop Health Monitoring Using XGBoost and Feature-Based Image Analysis
Vijayanandh Rajamanickam, Deepak Ramsubhag, and Jayaraj Jayaraman, “Enhancing Crop Health Monitoring Using XGBoost and Feature-Based Image Analysis”, Caribbean Journal of Science, 55(2) : 371-384, 2025. https://doi.org/10.18475/cjos.v55i2.a7
Sweet Pepper Foliar Diseases Quantification and Identification using an Image Analysis Tool
Vijayanandh Rajamanickam, Adesh Ramsubhag and Jayaraj Jayaraman, “Sweet Pepper Foliar Diseases Quantification and Identification using an Image Analysis Tool”, Journal of Plant Protection Research, 65(1), 89 – 99, 2025. https://doi.org/10.24425/jppr.2025.153821
Internet of Things (IoT) for advanced photovoltaics technology
Amit Neil Ramkissoon, Vijayanandh Rajamanickam, and Wayne Goodridge, “Internet of Things (IoT) for advanced photovoltaics technology”, Advanced Materials and Technologies for Photovoltaics, Elsevier, ISBN: 978-0-44-329250-7, eBook ISBN: 978-0-44-329251-4, 2025.
Ethical AI in HR: Navigating the Data-Driven Frontier
Deepti A.R, Manimekala B, Farzeen B, Vivek K, Vijayanandh Rajamanickam, “Ethical AI in HR: Navigating the Data-Driven Frontier” in the edited book “Innovate to Integrate: Data-Driven Management and TechStrat Fusion Unveiled”, Chapter 2, pp. 19 - 35, 2025, Emerald publishing, England. ISBN: 978-1-83708-460-9. https://doi.org/10.1108/978-1-83708-460-920251002.
Entropy-Regularized Federated Optimization for Non-IID Data
Khan, K., “Entropy-Regularized Federated Optimization for Non-IID Data,” Algorithms (MDPI), vol. 18, no. 8, Art. no. 455, 2025, doi: 10.3390/a18080455.
Learning resilience: gendered adaptation and community-led water management in a resource-stressed village in a small island developing state
Chin, S. R., Ramnath, S. O., Khan, K., and Elibox, W., “Learning resilience: gendered adaptation and community-led water management in a resource-stressed village in a small island developing state,” Journal of Work-Applied Management, vol. 17, no. 3, pp. 1–14, 2025, doi: 10.1108/JWAM-06-2025-0100.
A functional RNA–based and curvature-aware learning framework for federated optimization
K. Khan, W. Goodridge, and W. Elibox, “A functional RNA–based and curvature-aware learning framework for federated optimization,” Neurocomputing (Elsevier), vol. 652, Art. no. 131045, Nov. 1, 2025, doi: 10.1016/j.neucom.2025.131045.
Adaptive Federated Learning with Local Large Language Models for Modeling Photonic and Chemical Systems
Khan, K. (2025). Adaptive Federated Learning with Local Large Language Models for Modeling Photonic and Chemical Systems. IEEE Access, doi: 10.1109/ACCESS.2025.3606855.
DT-QFL: Dual-Timeline Quantum Federated Learning with TimeSymmetric Updates, Temporal Memory Kernels, and Reversed Gradient Dynamics
Khan, K., Khan, K. (2025). DT-QFL: Dual-Timeline Quantum Federated Learning with TimeSymmetric Updates, Temporal Memory Kernels, and Reversed Gradient Dynamics. IEEE Transactions on Quantum Engineering (TQE), doi: 10.1109/TQE.2025.3607689.
FedEHD: Entropic HighOrder Descent for Robust Federated Multi-Source Environmental Monitoring
K. Khan, W. Elibox, T. D. Ramlochan, W. Rajkumar, and S. Ramnath, “FedEHD: Entropic HighOrder Descent for Robust Federated Multi-Source Environmental Monitoring,” AI (MDPI), vol. 6, no. 11, Art. no. 293, Nov. 2025, doi: 10.3390/ai6110293.
HIFLA: Hilbert-Inspired Federated Learning via Action Principles
Khan, K., “HIFLA: Hilbert-Inspired Federated Learning via Action Principles,” IEEE Transactions on Emerging Topics in Computing, vol. 13, no. 4, pp. 1536–1552, Oct.–Dec. 2025, doi: 10.1109/TETC.2025.3629528.
