Machine learning is enabling groundbreaking advances, but its success in some areas and applications is hampered by a lack of data.
For this reason, one of the most challenging tasks for machine learning is the modeling of RNA-mediated interactions, which play a critical role in human health and disease.
As a 2025 Schmidt Science Fellow, Alissa will develop a high-throughput experimental technique to create a large-scale dataset of RNA-mediated interactions. Alissa aims to answer questions about RNA-mediated interactions in disease, focusing on viral infections, and to empower the development of next-generation therapeutics to improve human health.
Alissa will pivot from Machine Learning to Biochemistry