I am a postdoctoral researcher at IBM T. J. Watson Research Center. My areas of interest include cloud computing, federated learning, data privacy, blockchain technology, and healthcare. My current research focuses on container orchestration for Knative events and machine learning workflows. My prior work involves privacy-preserving federated learning models to analyze distributed and sensitive data. I have also built blockchain-based data management frameworks for healthcare and composite cloud applications.
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 on the cloud.