Advancing molecular diagnostics and microbial genomics to improve pathogen detection, surveillance, and public health outcomes
Growing up in Dhaka, Bangladesh, I witnessed firsthand how waterborne diseases and antibiotic-resistant infections disproportionately affect communities with limited access to diagnostic infrastructure. This sparked my determination to understand pathogens at the molecular level and develop tools that bring reliable detection to where it is needed most.
As a microbiology student at BRAC University, I found my calling at the intersection of wet-lab experimentation and computational analysis. From culturing Legionella pneumophila on selective media to performing 16S rRNA sequencing analysis with QIIME2, I discovered that combining traditional microbiology with bioinformatics and genomics opens powerful new avenues for pathogen surveillance and antimicrobial resistance tracking.
My research now spans molecular diagnostics, probiotic mechanisms, and environmental microbiology. Whether I am conducting PRISMA-guided systematic reviews of 180+ probiotic studies, building predictive models for antibiotic resistance, or mapping Legionella contamination hotspots in urban water systems, my goal remains the same: translating microbial science into actionable public health solutions.
I am dedicated to advancing molecular diagnostics and microbial genomics to improve the detection and surveillance of waterborne and clinically relevant pathogens. My research bridges wet-lab microbiology, bioinformatics, and data science to develop reproducible, evidence-based approaches for public health challenges.
Through PCR-based pathogen detection, microbiome analysis pipelines, systematic reviews, and predictive modeling for antimicrobial resistance, I work to strengthen global health surveillance and make diagnostic tools more accessible to underserved communities.
From PCR optimization and primer design to dnaJ gene-based identification of Legionella pneumophila, I develop and refine molecular tools for accurate pathogen detection in environmental and clinical samples.
Leveraging 16S rRNA analysis with QIIME2, BLAST, and phylogenetic tools alongside Python and R to analyze microbial communities, track diversity patterns, and build reproducible data pipelines.
Committed to translating laboratory findings into real-world solutions, from community water safety programs to AMR surveillance models that inform hospital infection control strategies.
Conducted a PRISMA-guided systematic review of 180+ studies examining strain-specific effects of Lactobacillus and Bifidobacterium on gut microbiota composition and mucosal immunity. Identified mechanistic pathways involving antimicrobial peptide secretion, SCFA metabolism, and TLR2/NF-kB signaling. Performed meta-analytic modeling using RevMan, JASP, and R (metafor, vegan) to compare effect sizes, standardizing CFU dosage and controlling for delivery-route variability. Published in Exploration of Drug Science (2025).
180+ reviewed
RevMan, R, JASP
Published
Selectively isolated and molecularly identified Legionella pneumophila from various water sources across Dhaka, Bangladesh using dnaJ gene-targeted PCR. Collected 42 water samples from 12 sites, applying acid, heat, and chlorine pretreatment to reduce non-Legionellae organisms. Cultured on optimized BCYE media and confirmed isolates via PCR, gel electrophoresis, and 16S rDNA and dnaJ gene sequencing. Published in Journal of Preventive, Diagnostic and Treatment Strategies in Medicine (2024).
42 collected
12 locations
dnaJ gene PCR
Preparing an integrative review manuscript proposing a mechanistic framework linking metformin-induced AMPK activation to modulation of intrinsic cardiac nervous system (ICNS) neuroinflammation and downstream arrhythmogenic remodeling. Synthesizing interdisciplinary literature spanning cardiometabolic pharmacology, neuroinflammation, autonomic neuroscience, and cardiac electrophysiology to establish an "AMPK-ICNS-arrhythmia axis." Expected submission May 2026.
AMPK Signaling
Interdisciplinary
In Preparation
Processed 16S rRNA sequencing data using QIIME2 and R to analyze microbial diversity and community shifts under varying environmental conditions. Generated OTU heatmaps, PCA plots, and phylogenetic trees to identify microbial indicators of environmental stress. Automated analysis pipelines to improve reproducibility and reduce processing time across datasets.
Analyzed 5-year clinical isolate data to quantify multidrug-resistant E. coli and Staphylococcus aureus trends and identify emerging AMR patterns. Built predictive models using logistic regression and random forests to forecast resistance profiles, informing hospital infection control strategies. This project demonstrated the power of combining microbiological data with machine learning for actionable public health surveillance.
5-year dataset
LR, Random Forest
Hospital IC
I am actively seeking research collaborations in molecular diagnostics, microbial genomics, and pathogen surveillance. Particularly interested in projects involving PCR/NGS-based detection, microbiome analysis, antimicrobial resistance, and public health microbiology.
Whether you're interested in collaborative research, need expertise in molecular diagnostics, or want to discuss microbial genomics and public health, I'd love to hear from you.
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