Jayakrishnan Anandakrishnan

About

Jayakrishnan Anandakrishnan received the bachelor's degree in Computer Science and Engineering from Kerala University, India, in 2011, and the master's degree in Computer Science with a specialization in Image Processing from the Cochin University of Science and Technology, India, in 2013. He received his Ph.D. in Computer Science and Engineering from the National Institute of Technology, Puducherry, Karaikal, India, in 2025. He expanded his expertise through an internship at the International Internship Pilot Program funded by the National Science and Technology Council of Taiwan, further enriching his knowledge and experience in his field. He is currently a full-time Assistant Professor with the School of Computing, Amrita Vishwa Vidyapeetham, Coimbatore, India. His research interests encompass machine learning, remote sensing, geospatial analytics, IoT, and edge computing.

Employment

• Amrita Vishwa Vidyapeetham University Assistant Professor
  2025 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• HydroFedNet: An Intent-Based Unified Federated Framework for Multisource Water Quality Monitoring
  IEEE Internet of Things Journal 2026 DOI: 10.1109/JIOT.2025.3627665
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• Point-KAN: Leveraging Trustworthy AI for Reliable 3-D Point Cloud Completion With Kolmogorov-Arnold Networks for 6G-IoT Applications
  IEEE Internet of Things Journal 2026 DOI: 10.1109/JIOT.2025.3576434
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• E-OptEEG: A Hybrid Ensemble Metaheuristic Feature Optimization for EEG-Based Sentiment Analysis on Resource-Constrained Edge Devices
  IEEE Transactions on Computational Social Systems 2026 DOI: 10.1109/TCSS.2026.3663208
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• Multimodal Sentinel-1/2 Data Fusion with a Dual-Path ViT-Kolmogorov-Arnold Network Pipeline for AI-driven Flood Event Classification
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3709031
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• A Parallel Attention-Guided Generative Adversarial Network for Efficient Thin Cloud Removal From Satellite Imagery
  2025 DOI: 10.4018/979-8-3693-6900-5.ch001
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• R-UAV-Net: Enhanced YOLOv4 With Graph-Semantic Compression for Transformative UAV Sensing in Paddy Agronomy
  IEEE Transactions on Cognitive Communications and Networking 2025 DOI: 10.1109/TCCN.2024.3452053
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• LCUT-Sv9: UAV-Assisted Powerline Inspection Framework with Secure Time-Sensitive Communication for Industry 5.0
  IEEE Open Journal of the Communications Society 2025 DOI: 10.1109/OJCOMS.2025.3537105
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• Precise Spatial Prediction of Rice Seedlings From Large-Scale Airborne Remote Sensing Data Using Optimized Li-YOLOv9
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025 DOI: 10.1109/JSTARS.2024.3505964
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• STA-AgriNet: A Spatio-Temporal Attention Framework for Crop Type Mapping from Fused Multi-Sensor Multi-Temporal SITS
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025 DOI: 10.1109/JSTARS.2024.3510468
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• CERMF-Net: A SAR-Optical Feature Fusion for Cloud Elimination From Sentinel-2 Imagery Using Residual Multiscale Dilated Network
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2024 DOI: 10.1109/JSTARS.2024.3411032
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