Broadly speaking, my lab develops and applies advanced computational methods to solve relevant biomedical problems furthering the understanding, diagnosis and treatment of human diseases. A unique aspect of my lab is the close integration of advanced machine learning and cutting-edge experimental techniques. And, because our goal is ultimately to improve diagnosis and treatment of human diseases, close collaborations with clinicians and industry colleagues is a vital component of the lab’s activities.

From the computer science perspective, we focus on innovation, developing novel statistical machine learning models incorporating techniques including Bayesian nonparametric priors that automatically adapt model capacity, human-interpretable rules with domain-specific biases, and relaxations of dynamical systems with physically realistic constraints to enable efficient inference. Our objective with these models is to gain new and deep insights into biological systems and ultimately make scientifically and clinically useful predictions about these systems.

From the biology perspective, a major focus of the lab is understanding the dynamics of the microbiome, or trillions of micro-organisms living on, within and around us, and its role in human diseases such as food allergy and C. difficile infection. A second area of great interest to my lab is the use of synthetic biology coupled with high-throughput experiments to understand and manipulate the microbiome.

I have an unusual background that gives me perspective on the work of the lab from different angles. My training includes a PhD in Computer Science, an MD, Residency/Board Certification in Clinical Pathology, and a Fellowship and Masters’ in Microbiology/Infectious Diseases. I also worked for 7+ years in industry in senior management positions in startup companies, including producing computer graphics for feature and IMAX films.