Sonal Jha

Sonal joined ARC in the Summer of 2021. As a Ph.D. student in Computer Engineering, her research lies at the intersection of Data Science and High-Performance Computing, often referred to as Data Science at Scale. Her main focus is anomaly detection in healthcare, addressing both human and animal health. In the healthcare context, anomalies typically represent diseases or conditions that require early forecasting or at least real time detection, with high accuracy and speed. To achieve accuracy, Sonal leverages graph-based algorithms, commonly known as network science, for early and real-time disease detection or disease risk identification. To enhance speed, she focuses on optimizing and scaling these algorithms to ensure computational efficiency. Before joining Virginia Tech, Sonal worked as a Business Intelligence Developer in the banking sector in India. She enjoys engaging with students and researchers in her role at ARC and assisting them in overcoming obstacles to scale their research work on ARC’s clusters.