I hold a Master's in Technology in Bioinformatics and currently work as a Bioinformatician in the Department of Clinical Microbiology at Christian Medical College, Vellore.
My research sits at the intersection of clinical microbiology, pathogen genomics, and machine learning. I specialize in large-scale bacterial genome analysis, focusing on antimicrobial resistance (AMR), virulence profiling, and host-pathogen interactions.
- Hypervirulent E. coli classification using whole-genome sequencing (WGS), clustering, and expert-guided labeling.
- Bacterial WGS pipelines with Nextflow for automated analysis.
- Helicobacter pylori disease classification using machine learning, integrating phylogeographic, genomic, and host metadata (age, sex, location).
- SNP mining in clinically relevant genes and preparing ML-ready feature sets from variant data (VCFs).
- Machine learning in microbial genomics
- Genomic epidemiology and pathogen surveillance
- AMR and virulence gene detection in large datasets
- Developing scalable and reproducible pipelines for pathogen analysis
- Feature engineering using:
- Z-curve parameters
- Trinucleotide frequencies
- SNP effect annotations
- Model building with Logistic Regression, Random Forests, and SVM
- SHAP-based feature interpretation for gastric cancer classification
- Publish pipelines and notebooks used in ongoing clinical microbiology research
- Collaborate on open-source microbial genomics projects
- Secure a fully funded PhD position in computational biology
- Contribute to open data initiatives for AMR and virulence gene tracking
Feel free to reach out if you share similar interests or are working in microbial genomics!