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Author

Johnson Kolluri

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Conference Aug 2026

A Clinically Validated Explainable Federated Multi-Modal Learning Framework for Privacy Preserving Cardiac Arrhythmia Classification in Heterogeneous Data Environments

Cardiac arrhythmia is a leading cause of morbidity worldwide, and automated electrocardiogram (ECG) classification has become an essential tool for early screening and triage. Two barriers separate research prototypes from clinical deployment: patient data cannot be centralized due to privacy regulations (HIPAA, GDPR),...

B. R, Johnson Kolluri · 0 citations
Conference Aug 2026

Digital Twin-Enabled Explainable Multi-Agent Deep Reinforcement Learning for Adaptive Cross-Layer Hybrid IoT Communication Networks

The explosive growth of heterogeneous Internet of Things (IoT) applications has posed great challenges in realizing energy-efficient, reliable, and adaptive communication in highly dynamic network environments. Traditional communication optimization techniques usually suffer from static decision making, poor scalabilit...

Sandhya R, Johnson Kolluri · 0 citations
Conference Aug 2026

Computer Vision-Based Stroke Lesion Detection and Prognosis Prediction Using Deep Learning

In this paper, a novel hybrid Swin Transformer and convolutional neural network (CNN) encoder-decoder, called StrokeDL-Net, is proposed for accurate multimodal brain MRI lesion segmentation and a temporal multi-modal fusion network, called ProgNet, is proposed for 90-day functional outcome prediction via the modified R...

Burgula Sowmya, Johnson Kolluri, P. Shailaja · 0 citations
Conference Aug 2026

A Multimodal Earth Digital Twin Framework with Causal AI for Autonomous Climate Intervention Planning

Climate change is among the most pressing challenges of the twenty-first century, demanding decision-support tools that are scientifically grounded, data-rich, and capable of evaluating the consequences of interventions rather than merely forecasting trends. Existing AI-driven climate platforms largely rely on correlat...

Vishala Pathapalli, Johnson Kolluri · 0 citations
Conference Jul 2026

Multimodal Context-Enriched Visual Representation Learning for Enhanced Vision–Language Image Captioning

Image captioning models can produce rapid Sentences, without visual relationships, or insert non-existing plausible objects. A common cause is to compress image evidence into visual symbols that carry a weak neighbourhood context. The multimodal context-enhanced visual representation learning framework (MCVRL) addresse...

E. Divya, Johnson Kolluri, Kiran Siripuri · 0 citations

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