Privacy-Protecting Technologies for Collaborative Research
The rapid increase in digitized information related to human health has raised the possibility of performing more complex statistical analyses by pooling data from several different sources or institutions. This presentation will discuss modern approaches for sharing access to private data to give clinicians and researchers an overview of how these technologies work, what the current state-of-the-art is, and what the potential benefits and limitations may be.
Dr. Anand Sarwate is an Assistant Professor of Electrical and Computer Engineering at Rutgers University. His work is at the intersection of statistics, computing, and signal analysis, and for the last 5 years he has worked actively on algorithms for machine learning and statistical analysis of private data. He is actively collaborating on several large-scale projects for privacy-preserving data analysis; most relevant is a project designing a differentially private analysis suite for neuroimaging research. His work in this area is currently funded by the National Science Foundation (NSF), the National Institutes of Health (NIH), and the Defense Advanced Projects Research Administration (DARPA). Dr. Sarwate is broadly interested in statistical and information processing algorithms.
The Innovative Discoveries Series, sponsored by the Delaware Clinical & Translational Science ACCEL program and the Christiana Care Value Institute, features informal presentations on topics relevant to current research and healthcare practice, led by knowledgeable and experienced presenters. There are offerings for researchers, healthcare providers, and community members of varying levels of experience.
These free talks are held Fridays at noon at Christiana Hospital but can be viewed from your home or office computer. Earn CMEs by participating in-person or online. Lunch is served and all are welcome to attend.
Contact Sarahfaye Dolman at email@example.com with any questions.
- Anand D. Sarwate, PhD