معرفی
Alisa Yurovsky is a Lecturer and IDEA Fellow at the Department of Biomedical Informatics at Stony Brook University. Her research focuses on computational biology at the intersection of computer science, genetics, and statistics to advance precision medicine. She earned her PhD in Computer Science from Stony Brook University under Steven Skiena, an M.S. in Computational Biology from EPFL under Bernard Moret, and a B.S. in Computer Science with a Mathematics minor from Carnegie Mellon University.
Research Interests: Alisa develops computational algorithms for precision medicine applications, particularly addressing racial disparities in health data. Her current projects include compartment deconvolution in mixed tissue samples, spatial transcriptomics analysis, small-size differential expression studies, and machine learning in biomedical informatics.
Publications Trends: Her recent work spans spatial transcriptomics, survival analysis, and machine learning applications in genomics. She has contributed to algorithms for cell-cycle phase detection, ribosomal frameshift identification, and non-negative matrix factorization.
Scientific Awards:
- 2023 IDEA Fellowship
- 2020 NSF/CRA/CCC Computing Innovation Postdoctoral Fellow
- 2017 CEWIT Best Poster Award
- 2016 NSF Graduate Research Fellowship
- 2010 Prix Annaheim-Mattille for Master’s Thesis
- 2007 Cadence Design Systems Award
Advising and Grants: She mentors undergraduate and high school students through Stony Brook’s VIP Webgen team and Simons Summer Research Program. Her research has received support from NSF and institutional grants.
