Architecting reproducible multi‑omics and AI systems for cancer and immunology.
I design and deploy scalable bioinformatics pipelines, integrate heterogeneous data, and translate insights into actionable strategies for both academia and industry. My experience spans structural immunology, cancer genomics, proteomics, and AI‑driven healthcare operations.
Translational research
Connecting multi‑omics data with clinical outcomes for biomarker discovery and therapeutic development.
Reproducible pipelines
Scalable workflows using Nextflow, nf‑core, and Slurm/cloud, with comprehensive documentation and versioning.
AI & healthcare analytics
Operational modeling and predictive analytics for hospital resource management and translational research.
Leadership & mentoring
Guiding interdisciplinary teams, training researchers, and advising biotech and startup executives.
Academic research focus
My scientific foundation combines structural bioinformatics with systems‑level multi‑omics.
Structural & immune systems biology
- Protein‑protein interaction modeling (cytokines, receptors, pMHC–TCR complexes)
- Dynamic simulations and energy landscape analyses for drug discovery
- Neoantigen prediction and immune signaling pathways
Multi‑omics integration
- Proteogenomic pipelines for cancer (RNA‑seq, WES/WGS, TMT proteomics)
- Dual RNA‑seq for host–pathogen studies
- Single‑cell workflows (Seurat / nf‑core)
Industry & innovation
I translate academic rigor into practical solutions for biotech, pharma, and AI‑powered healthcare startups.
Biotech & pharma collaboration
- Pipeline architecture and workflow refactoring for omics data
- Biomarker strategy and experimental design consultation
- Data modeling and ETL for regulatory submissions
AI & healthcare startups
- Predictive analytics for resource allocation and clinical operations
- Machine‑learning integration with genomics and EHR data
- Technical due diligence and roadmap development for founders
Selected publications
Highlights from my peer‑reviewed contributions. See ORCID/Google Scholar for the full list.
- proteoDA — R package for quantitative proteomics (JOSS, 2023)
- EXCESP — Extracellular interactome database (J Proteome Res, 2022)
- Dual RNA‑Seq pipeline — Host–pathogen transcriptomics (ms in prep, 2024)
- TNF/TNFR interactome analyses (Comput Biol Chem, 2023)
Software & resources
Open source & reproducible work
- proteoDA — differential analysis toolkit (R)
- EXCESP — extracellular interactome resource
- Nextflow / nf‑core pipelines — cancer genomics & proteomics
- ARINBRE GitHub maintenance & workflow trainings
Visualization & reporting
- Publication‑ready figures (ggplot2, matplotlib)
- Interactive notebooks & dashboards
- Single‑cell analytic reports
Service & peer review
- AR INBRE NIH pilot grant reviewer
- Journal reviewer across bioinformatics & immunology (see ORCID)
- Mentorship & workshops in computational methods and reproducibility
Consulting & retainer services
I partner with research groups, biotech companies, and startups to build robust data infrastructures and analytical strategies.
Engagement models
- Strategic advisor — guidance on workflow architecture, technology selection, and team structuring
- Project‑based — defined scope, milestones, and deliverables for pipeline builds or data integration
- Retainer — ongoing fractional chief data officer support for startups and labs
Expertise offered
- Omics pipeline development & refactoring (RNA‑seq, scRNA‑seq, proteomics, WES/WGS)
- AI/ML integration with omics and clinical data
- Data governance, reproducibility & regulatory readiness
I can provide references and project summaries under NDA as appropriate.
Contact
Email: kalyanidhusia.bhu@gmail.com
Location: Little Rock, AR (UTC‑6) • Available for remote collaboration
When reaching out, please share your project scope, timelines, data types, and infrastructure (HPC/cloud).