Publications
75 citations · h-index 3 · i10-index 2 · Google Scholar profile
Journal articles
Limits of depth: Over-smoothing and over-squashing in GNNsBig Data Mining and Analytics 7(1), 205–2162023IF 13.6cited by 55
A review of challenges and solutions in the design and implementation of deep graph neural networksInternational Journal of Computers and Applications 45(3), 221–2302023IF 3.6cited by 13
Depth-defying OOF-GNN: Sailing smoothly amidst GNN wavesKnowledge-Based Systems 280, 1109912023IF 8.8cited by 3
Conference papers
Deep Learning Meets Graph Theory: A Novel Approach to Generating Embeddings for Recommender Systems21st Learning and Technology Conference (L&T), IEEE, 302–3072024
Book chapters
GNN approach for software reliabilitySystem Reliability and Security, 1–132023cited by 3
Software reliability prediction using neural networks: A non-parametric approachSystem Reliability and Security, 14–272023cited by 1
Under review
AI-driven intelligent visualization agents for high-performance, user-centric web-based data explorationData and Knowledge Engineering (Elsevier)2025
Trinity: Transformer-driven real-time intrusion detection with adaptive intelligenceIEEE Big Data Mining and Analytics2025
Multi-model performance benchmarking for house price predictionSN Computer Science (Springer Nature)2025
Research projects
2022 – 2024
OOF-SAGE: an over-smoothing and over-squashing free graph neural network
OOF-SAGE: an over-smoothing and over-squashing free graph neural network
2022 – 2023
Partitioned-GNN for personalised recommendations
Partitioned-GNN for personalised recommendations