About Me
Hi! I’m Sahvir, a biomedical engineering student at UVA interested in computational biology, systems modeling, synthetic biology, and transcriptomics.
I’m drawn to problems where biology, mathematics, and computation intersect. I enjoy thinking about biological systems as dynamic, interconnected networks — from signaling pathways and cellular states to engineered biological circuits.
What Excites Me
My interests sit broadly within quantitative biology. I’m especially interested in how computational and mathematical tools can help us understand complex biological behavior, design better experiments, and generate more interpretable biological hypotheses.
Current Work
Virginia iGEM 2025
I’m leading a synthetic biology project focused on enhancing biohydrogen production through engineered biological systems.
Lazzara Lab
I’m exploring bulk RNA-seq deconvolution workflows to better understand variation in cell-type fractions and how to use said data to infer cell-cell interactions.
View All Experience
Lazzara Lab — Undergraduate Researcher
Configured parallel comptutation to optimize computational efficiency.
Developed computational methods for parameter estimation using limited data sets.
Optimized bulk RNA-seq deconvolution workflows to enable estimation of cell-cell interactions.
Virginia iGEM — Team Lead
Lead the Virginia iGEM team in developing synthetic biology projects, coordinating research efforts, mentoring team members, and preparing presentations for the International Genetically Engineered Machine competition.
Independent Research Projects
Conducted independent computational biology projects focused on pan-hantavirus vaccine design and small-molecule inhibitor design against Andes orthohantavirus infection.
Posters & Presentations
The Cysteinator: Cell-Regulated Optimization of L-Cysteine for Biohydrogren Production, Mid-Atlantic Synthetic Biology Network 2026
The Cysteinator: A Biological Device to Enhance Biohydrogen Production, iGEM Grand Jamboree 2025
Selected Coursework
Systems Bioengineering, Computational Biology, Biomedical Data Science, Molecular Data Science, Probability & Statistics, Differential Equations, Organic Chemistry, and related coursework.
Organizations & Activities
Charlottesville Debate League, Virginia Cricket Club, Virginia iGEM, Data Science for Sustainable Development at UVA, and undergraduate research mentoring activities.
How I Think About Research
To me, research is fundamentally about asking better questions. What excites me most about quantitative biology is how advances in computation now allow us to connect mechanism with data in entirely new ways. By combining models, experiments, and data analysis, we can explore biological systems with a level of depth and scale that was previously impossible.
I’m especially fascinated by systems where behavior emerges from interactions between many components. Whether the system is a signaling pathway, a microbial community, or a transcriptomic cell state, quantitative approaches help make complex biological behavior more understandable.
More than anything, I see research as the process of asking meaningful questions and sharing meaningful answers. That mindset is part of why I built this website. I’m drawn to the inherently interdisciplinary nature of quantitative biology and the way it brings together modeling, experimentation, and computation to better understand the living world.
Tools & Methods
Computational
Python, MATLAB, R, RNA-seq workflows, single-cell analysis, modeling, clustering, and data visualization.
Modeling
ODE models, systems biology models, signaling network dynamics, parameter analysis, and biological simulation workflows.
Biological
Synthetic biology, molecular biology, assay design, wet-lab collaboration, and experimental planning.
Looking Ahead
Long-term, I hope to pursue a PhD and contribute to research at the intersection of computational biology, systems modeling, and biological engineering. I’m excited by work that uses quantitative methods to better understand, predict, and eventually design biological systems.