I am a postdoctoral researcher at IBM Research Cambridge. My areas of interest include federated learning, blockchain technology, healthcare informatics, cloud computing, data privacy, and genomics. My current research focuses on developing privacy-preserving federated learning models to analyze large-scale distributed data. I am also interested in blockchain technology and its application in healthcare and composite cloud solutions.
I am a Visiting Scientist at the Broad Institute of MIT and Harvard, where I am designing methods to improve the predictive power of polygenic risk scores to help clinicians identify patients at serious risk for cardiovascular disease.
I received my Ph.D. in Computer Science and Engineering from University of Notre Dame, IN. My doctoral thesis focused on designing cloud computing-based infrastructures to expedite analysis and learning-based algorithms to improve quality of large-scale genomic data. Prior to joining IBM Research, I worked at the Broad Institute of MIT and Harvard on comparative genomics to control Zika outbreak. During my internship at IBM Watson, I built automated tools to optimize cloud-based resource allocation for SoftLayer Infrastructure as a Service (IaaS) and deploy Watson applications (Watson Oncology and Watson Engagement Advisor) on the cloud.