Curriculum Vitae
Computational & Systems Biology · Graph neural networks for biological systems, biomarker discovery, and protein dynamics. A full PDF version is available for download.
Research interests - Graph neural networks for biological systems · biological network analysis · biomarker discovery · protein dynamics and flexibility · physics-informed machine learning · knowledge graph and Gene Ontology embeddings.
Education
M.Sc. Bioinformatics
University of North Bengal · CGPA 7.65
Dissertation research conducted in the Computational Systems Biology Lab.
B.Sc. Zoology (Honours)
Kalimpong College, University of North Bengal · CGPA 7.64
Coursework: molecular biology, genetics, and biochemistry.
Research Experience
Research Scholar
Computational Systems Biology Lab · Department of Bioinformatics · University of North Bengal
- Developing deep learning methods for cancer biomarker identification and protein conformational dynamics prediction.
- Designing graph neural network architectures that integrate protein–protein interaction networks, Gene Ontology embeddings, and knowledge graph representations.
- Building physics-informed graph models incorporating quantum-inspired neural PDE operators for protein dynamics.
Software & Tools
CABIgoWEB
Web server implementing graph-based deep learning for cancer biomarker identification. Combines PPI networks with Gene Ontology and knowledge graph embeddings; provides biomarker prediction and functional enrichment. Live ↗
LGNM
Learnable Graph Network Model for protein conformational dynamics. Learns heterogeneous residue interactions from molecular dynamics data using a physics-constrained graph formulation to predict residue-level flexibility. Live ↗
Methods
Graph Learning
Graph neural networks · GCN · GAT / GATv2 · GraphSAGE · message passing · graph representation learning · biological network learning
Biological Modelling
PPI networks · Gene Ontology · knowledge graphs · biomarker prioritization · differential expression · pathway & functional enrichment · multi-omics analysis
Computational Biophysics
Elastic network models · protein flexibility · normal modes · molecular dynamics analysis · physics-informed graph models · residue-level interaction modelling
Statistical Modelling
PCA · PCR · linear & multivariate regression · correlation and partial correlation · high-dimensional data analysis · network-based inference
Computational Stack
Programming
Python · R · Bash · C · Java · Perl · JavaScript
ML Frameworks
PyTorch · PyTorch Geometric · DGL · scikit-learn · HuggingFace Transformers
Scientific Computing
NumPy · SciPy · Pandas · CUDA · GPU computing · SQLite
Bioinformatics
Bioconductor · limma · edgeR · DESeq2 · clusterProfiler · biomaRt · ComBat · STRING · RDKit
Networks
NetworkX · Cytoscape · Neo4j
Infrastructure
Linux · Git · Docker · SLURM · Flask
Languages
English · Nepali · Hindi