Alisa Yurovsky (Department of Biomedical Informatics, College of Engineering and Applied Sciences)
Yurovsky’s research focuses on the development of new algorithms and computational methods that aid in the advances of precision medicine, with the potential to address existing disparities in health data. She is also interested in algorithms for synthetic gene design and analysis methods for small size differential expression studies, with goals for advancing vaccine design and promoting diverse and inclusive research. Yurovsky received her undergraduate degree in computer science from Carnegie Mellon University, completed her research-focused master’s at EPFL, and received a PhD in computer science from Stony Brook University, where she was a recipient of an NSF Graduate Research Fellowship. For her post-doctoral work, Yurovsky was a recipient of the NSF/CRA Computing Innovation Fellowship for research on precise compartment deconvolution and weight estimation of mixed tissue samples.
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