I am a full technical staff at MIT Lincoln Laboratory, where I work with inter-disciplinary teams of researchers and engineers to develop practical algorithms and architectures. My primary research focus over the last eight years has been formal methods, i.e., algorithms that use formal languages to model correct or desired behaviors of systems such as robots or networked cyber-physical systems. By using a mathematically rigorous concepts of what we’d like a system to do, we can narrow the search space of plans or policies to only those that will exhibit the desired behavior. Similarly, we can examine a designed legacy system and determine whether that system will exhibit those desired behaviors or whether we can find poorly-behaving “corner cases”. My research has focused on using formal methods alongside probability theory, whether that is planning under uncertainty, using machine learning to gain insights about system behaviors, or using differential privacy to protect information about behaviors.
Prior to joining MIT Lincoln Laboratory, I was a post-doc in the AMBER and GRITS labs at the Georgia Institute of Technology. I completed my Ph.D. in Systems Engineering at Boston University while working in the HyNeSS and MSL laboratories.