Research Programs & Four Scientific Pillars
My computational biology program investigates how viral genomic variation and host regulatory networks shape infection outcomes, cross-species spillover, and disease severity. By uniting high-throughput diagnostic sequencing with context-aware machine learning and scalable web engineering, our work bridges molecular mechanism with real-time epidemiological impact.
The Four Pillars of My Research Program
Each pillar represents a fundamental thrust of my computational biology research program, operating synergistically while contributing algorithms, datasets, and predictive models to an integrated discovery engine.
Viral Surveillance & Multi-Omics Discovery
Modern disease surveillance requires looking beyond consensus sequences to resolve the dynamic intra-host population structures of rapidly emerging pathogens. This pillar investigates the relationship between viral sequence variation and host transcriptional responses during infection and cross-species transmission events.
Key Research Directions & Methodologies:
Machine Learning & Context-Aware AI for Host–Pathogen Interactions
Sequence similarity alone often fails to explain why certain viral variants readily cross species barriers while closely related lineages remain restricted. This pillar develops multimodal machine learning architectures that combine sequence embeddings, structural interfaces, and host-receptor orthology to predict continuous interaction properties.
Key Research Directions & Methodologies:
Comparative Systems Biology & Host Immune Networks
When a pathogen encounters a new host, differences in outcome are governed by how effectively viral proteins disrupt or co-opt the host's intracellular regulatory networks. This pillar uses comparative network biology to discover conserved immune vulnerabilities and explain species-specific virulence differences.
Key Research Directions & Methodologies:
Reproducible Software Architecture & Public Web Infrastructure
Scientific discovery is accelerated when complex computational workflows are accessible, reproducible, and easy to run across heterogeneous computing environments. This pillar focuses on architecting enterprise-grade pipelines and publicly deployed web portals that serve the international research community.
Key Research Directions & Methodologies:
Awarded & Active Research Grants
Federal and foundation awards supporting pathogen genomic surveillance, host-pathogen interactomics, and rapid outbreak diagnostic intervention across agricultural and biological systems.
Decoding the Poultry-HPAI Interactome: An Integrative Pipeline for Targeted Therapeutics Against Highly Pathogenic Avian Influenza
Investigator Role: Co-PI
Decoding the poultry-HPAI interactome to develop an integrative pipeline for targeted therapeutics against Highly Pathogenic Avian Influenza. Incorporates multi-omics sequencing, structural interactomics, and viral surveillance.
Emerging avian metapneumovirus subgroup A and B in US poultry: development of diagnostic assays and control strategies
Investigator Role: Co-PI
Development of high-sensitivity diagnostic assays and control strategies for emerging avian metapneumovirus (aMPV) subgroups A and B causing outbreaks in US poultry flocks.
Broad-spectrum live recombinant vaccine and improved diagnostics for emerging avian metapneumovirus subgroups A and B causing severe outbreaks in US poultry
Investigator Role: Co-I
Rapid outbreak response for evaluating broad-spectrum live recombinant vaccines and improved diagnostics for emerging aMPV subgroups A and B.
Submitted Proposals & Grants Under Review
Competitive research proposals submitted as Principal Investigator (PI) and Co-Investigator to USDA-AFRI and NIH R21 programs.
AI-Driven Genomic Surveillance and Control Strategies for Emerging Turkey Reoviruses (TRV)
AI-driven computational genomic surveillance, molecular evolution modeling, and intervention strategies for emerging turkey reoviruses.
BRIDGE: A host-pathogen interactome and machine learning platform to predict zoonotic risk of livestock and poultry viruses
Developing a host-pathogen interactome and deep learning platform to forecast cross-species transmission and zoonotic spillover risk.
Innovative approaches for early detection and control of zoonotic influenza viruses in poultry
Innovative computational and experimental approaches for early detection, variant characterization, and control of zoonotic influenza viruses.
Novel mass administration vaccine for humoral and cellular immunity using mRNA plus virus like particle
Computational design and evaluation of mass-administration mRNA and virus-like particle (VLP) vaccine platforms for agricultural livestock.
Systems-Level Host Interactome Framework for Avian Metapneumovirus Mitigation: Advancing Therapeutics to Strengthen US Agricultural Biosecurity
Systems-level host interactome framework modeling host-pathogen protein networks to advance antiviral discovery and biosecurity defenses.
Bridging High-Performance Computing with Diagnostic Reality
Computational biology is at its best when algorithms are continually calibrated against real diagnostic samples and biological reality. By anchoring our computational pipelines directly in high-throughput sequencing workflows and active pathogen outbreak surveillance, our tools are tested against real-world biological complexity rather than idealized theoretical datasets.
Whether uncovering novel zoonotic spillover markers, building containerized Nextflow pipelines for high-performance clusters, or deploying accessible web servers for global scientists, my program is committed to open, reproducible, and interdisciplinary computational science.