Research Scientist
Current- Technical lead on Peraton Labs OCCAM program, a TA2 performer for the DARPA ConSec program. Implemented agile team methodologies to manage a large Python, Java, and JavaScript code base with components from CS domains such as Machine Learning, Satisfiability Modulo Theories, sBlack Box Optimization, and UI. Interfacing with other ConSec performers on a weekly basis to maintain technical cohesion and alignment with DARPA goals. Regularly designing and leading implementation of improvements to the scaling of the optimization engine.- Technical and scientific contributor at both the design and implementation levels of a large-scale, modular, graph data modeling system for another DARPA project.- Co-author in a successful bid on the IARPA project TrojAI; helping to develop novel techniques for detecting back doors in pre-trained neural networks without access to large amounts of training or validation data.- Co-author in a successful bid on the DARPA TMVD program. Aiding in the understanding of universal adversarial perturbations.- Co-author of a bid for the DARPA GARD project. This effort involved the primary authorship of a paper showing strong theoretical results in the field of certifiably adversarial resistant neural networks.- Performing ongoing theoretical and experimental research on the topic of adversarial machine learning as part of crafting project proposals for government R&D projects.