Armita Salahi has earned a Sture G. Olsson Fellowship to develop systems approaches in biomedical engineering. Salahi is a Ph.D. student of electrical engineering advised by Nathan Swami, professor of electrical and computer engineering at the University of Virginia. Salahi joined Swami’s lab in 2015 to pursue her interest in developing devices for disease diagnostics, earning her Master of Science degree within two years. To understand disease onset and progression, Salahi develops label-free microfluidic methods to measure and analyze the biophysical properties of single cells to characterize the role of heterogeneity in diseases.
“Using the measurements from various pancreatic cancer cells, I observed some general trends in my data and recognized an opportunity to use more rigorous machine learning methods,” Salahi said. Machine learning can help decipher the hidden patterns within the electrophysiological properties of cancer versus stromal cells in the tumor microenvironment after various drug treatments.
This realization led to collaborative research with Dr. Todd Bauer, assistant professor of surgery in the Division of Surgical Oncology at UVA’s School of Medicine. Salahi identifies drug sensitivity of early stage pancreatic cancer, which is the fourth leading cause of cancer deaths; the five-year survival rate is less than 6%. Applying machine learning and statistical methods to large amounts of data gathered under different conditions and at different stages of treatment, Salahi can correlate cancer response and chemotherapeutic outcomes.
“I am enthused by my current research direction and determined to make a substantial impact on the field of early cancer diagnosis,” Salahi said. Salahi is on track to graduate in 2021 and plans to continue her research in the area of artificial intelligence applied to biophysical cell analysis.