Hi! I'm Sahvir, a Biomedical Engineering student at the University of Virginia passionate about using quantitative and computational approaches to better understand biological systems. My work spans systems and synthetic biology, bioinformatics, and molecular modeling, in applications ranging from therapeutics to sustainable biotechnology.
I built this website to document and share my projects, research experiences, and ideas. Whether through mechanistic modeling, transcriptomics, or synthetic biology, I’m especially interested in how computational methods can be used to better understand, engineer, and predict complex biological behavior.
Leading a synthetic biology project focused on enhancing biohydrogen production through engineered biological systems.
Exploring RNA-deconvolution approaches to infer cell-cell signaling via bulk RNA-seq data.
Led a team developing a biological device-assisted methodology to enhance biohydrogen production via dark fermentation.
Identifying CD4+ epitopes to evaluate the potential to develop a pan-hantavirus vaccine to elicit broad-spectrum immunity to hantavirus as a means of availing a public health threat.
Identifying small molecule inhibitors of PCDH1 to serve as a competitive inhibitor of PCDH1-Andes orthohantavirus binding to contribute to developing a treatment.
Evaluation of the relationship between growth conditions and gene essentiality in S. pneumoniae via metabolic modeling.
The development and analysis of a simple logic-based model of TNF/NF-κB signaling to analyze infection-induced inflammation.
Developing an agent-based model of rhinovirus infection in the nasal epithelium to analyze the impact of immunosuppression on infection dynamics.
An exploration of the impact of clustering methods and parameters on the heterogeneity of microglial cell-state classifications across Alzheimer's and healthy microglial cell populations; and its biological implications for understanding microglial function.
The development of a computational pipeline to assist SELEX screening for aptamer design to identify immprove workflow efficiency and candidate selection.
The development of a computational pipeline to assist in parameter optimization of large ODE/PDE mechanistic models using Bayesian sampling.
Exploring bulk RNA-seq deconvolution approaches to infer cell-cell signaling.
I enjoy meeting people who are excited about science and quantitative biology. Whether you want to discuss research, share ideas, or just connect, I'd love to hear from you.