Genome-scale modeling · Multi-omics analytics · Reproducible pipelines
Genome-scale modeling & data analytics for biology.
I help research and industry teams turn multi-omics data into predictive, genome-scale models. My work spans constraint-based modeling (GEMs and ME-models) and practical data analytics to support hypothesis generation, experimental design, and reproducible biological insight.
Quick links
Available for consulting and independent contracting in genome-scale modeling and biological data analytics.
About
I help research and industry teams turn multi-omics data into predictive, genome-scale models. My work spans constraint-based modeling (GEMs and ME-models) and practical data analytics to support hypothesis generation, experimental design, and reproducible biological insight.
I’ve developed and applied metabolism-and-expression (ME) modeling workflows to study resource allocation, stress responses, and metabolic efficiency in E. coli, and I build software that makes these methods easier to use and share.
Services
Independent contracting and consulting for academic labs, biotech, and industry R&D.
Genome-scale modeling
Build, curate, and analyze GEMs and ME-models; condition-specific constraints; gene knockouts; and interpretable model-based predictions.
Constraint-based analysis
FBA / ME optimization, resource allocation analyses, and workflow automation with clear documentation and reproducible outputs.
Multi-omics integration
Integrate transcriptomics, proteomics, and metabolomics with modeling frameworks; quality control, normalization, and structured compendia.
Data analytics
Statistics and ML for high-dimensional biology (dimensionality reduction, clustering, regression) with an emphasis on interpretability.
Reproducible pipelines
Python + Git + Docker-based pipelines for analyses you can hand off to a team and maintain over time.
Engagement types
- Short consult — one or two calls + written recommendations
- Fixed-scope project — defined deliverables and timeline
- Ongoing support — weekly hours for modeling/analytics work
Selected work
Representative artifacts that show capabilities end-to-end.
COBRAme.org
Web-based platform to run and explore genome-scale metabolism & expression modeling workflows.
↗PhD Dissertation
Integrating multi-omics knowledge with constraint-based modeling to improve predictive physiology.
↗Google Scholar
Complete publication list, citations, and links.
↗GitHub
Open-source tools, pipelines, and modeling code.
↗Publications
Full metrics and links on Google Scholar ↗.
2025
- Laboratory evolution reveals transcriptional mechanisms underlying thermal adaptation of Escherichia coli. Genome Biology and Evolution 2025 Sep 30;17(10):evaf171.
- Extracellular respiration is a latent energy metabolism in Escherichia coli. Cell 188(11), 2907–2924.e23.
- iModulonDB 2.0: dynamic tools to facilitate knowledge-mining and user-enabled analyses of curated transcriptomic datasets. Nucleic Acids Research 53(D1), D99–D106.
- Aerobicity stimulon in Escherichia coli revealed using multi-scale computational systems biology of adapted respiratory variants. bioRxiv 2025.03.13.642450.
- Trade-off between resistance and persistence in high cell density Escherichia coli cultures. mSystems 10(7), e0032325.
2024
- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome. Nature Communications 15(1), 5234.
- The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions. mSystems 9(7), e00305-24.
2023
- Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance. Cell Reports 42(9):113105.
- TCA cycle tailoring facilitates optimal growth of proton-pumping NADH dehydrogenase-dependent Escherichia coli. Microbiology Spectrum 11(6), e02225-23.
2022
- Laboratory evolution of synthetic electron transport system variants reveals a larger metabolic respiratory system and its plasticity. Nature Communications 13(1), 3682.
2021
- Restoration of fitness lost due to dysregulation of the pyruvate dehydrogenase complex is triggered by ribosomal binding site modifications. Cell Reports 35(1), 108961.
2020
- The expanding computational toolbox for engineering microbial phenotypes at the genome scale. Microorganisms 8(12), 2050.
2018
- Ethical considerations in the translation of CAR-T cell therapies. Immuno-oncology Insights
CV
Education
- PhD, Bioengineering — University of California, San Diego (Dec 2025)
- BS, Biomedical Engineering — Georgia Institute of Technology (May 2019) — GPA: 4.0
Focus areas
- Genome-scale metabolic and expression (ME) modeling (COBRAme, DynamicME, StressME)
- Constraint-based modeling workflows (FBA/ME), resource allocation, condition-specific modeling
- Multi-omics integration and interpretable ML for regulatory structure discovery
- Software engineering for reproducible modeling pipelines (Python, Docker, GitHub)
Experience (condensed)
- UC San Diego — Systems Biology Research Group (Palsson Lab)
Genome-scale modeling + multi-omics analytics; tool development and collaborations across projects. - Selected talks & service
Hosted COBRA methods workshop (COBRA 2024); guest lecture on genome-scale modeling (TIFR 2025); teaching assistant roles.
Download
The on-page CV is intentionally condensed for readability; the PDF contains the full academic CV.