Scholar
Jagath Rajapakse, PhD, FIEEE
Google Scholar ID: 9WPWHiEAAAAJ
Professor of Data Science; College of Computing and Data Science; Nanyang Technological University
Citations & Impact
Citations
3,512
H-index
31
i10-index
67
Publications
20
Co-authors
36
list available
Contact
No contact links provided.
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published over 300 peer-reviewed research articles in high-impact journals and conferences
- Elevated to IEEE Fellow in 2012 for contributions to brain image analysis
- Fulbright Scholar
- Editor for Engineering Applications in Artificial Intelligence (IF = 8.0)
- Former Associate Editor for IEEE Transactions on Medical Imaging, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Computational Biology and Bioinformatics
- Recent notable publications include:
- - 'Interpretable modality-specific and interactive graph convolutional neural networks on brain functional and structural connectome', Medical Image Analysis, 2025 (IF=10.7)
- - 'Drug discovery and mechanism prediction with explainable graph neural networks', Scientific Reports, 2025 (IF=3.8)
- - 'GLDM: Hit molecule generation with constrained graph latent diffusion model', Briefings in Bioinformatics, 2024
- - 'Two-stage approach to intracranial hemorrhage segmentation from head CT images', IEEE Access, 2024 (IF=3.9)
- - 'Self-supervised learning for hotspot detection and isolation from thermal images', Expert Systems with Applications, 2024 (IF=8.665)
Background
- Professor of Data Science at the College of Computing and Data Science, Nanyang Technological University (NTU), Singapore
- Research interests include explainable AI, generative AI, brain imaging, and computational and systems biology
- Current research focuses on developing computational techniques and tools for diagnosis and treatment of brain diseases by integrating neuroimaging and multi-omics data
- Also investigates integration of imaging data with multi-omics (genomics, proteomics, transcriptomics, epigenomics) to study molecular mechanisms of diseases
- Research includes generating small molecule and peptide-based drugs for cancer
