Currently, I am Lead Technical Architect at Airlitix, Inc., where we develop scalable, automated drone-based solutions for plant monitoring inside a greenhouse environment, including plant stress analysis and seed counting. I lead a small, dedicated team integrating state-of the art control, planning, and visual odometry techniques to provide precise data analysis.

Throughout my academic career, I worked together with a team of fellow graduate students to develop a powerful, hierarchical planning and control infrastructure known as PRACSYS. This open-source software written in C++ and built off of the ROS framework is the culmination of years of effort, and was used as a basis for the below Picking Challenge and Crowd Simulation projects. The software is still actively developed, consisting of tens of thousands of lines of code to my last knowledge.

Additional information about the structure and scope of the project can be found in publications I co-authored here and here.

During my graduate study, I participated in the first annual Amazon Picking Challenge with the RUPracsys team, achieving 7th place overall. I worked together with a diverse, multi-disciplinary team to create a complex hierarchical planning and control framework for automated order picking.

Here is video of a test run of the framework.

I worked with the Port Authority of New York and New Jersey as part of a DHS fellowship. Together, with a team of developers, I worked on a tool to design and test different floor layouts using a crowd simulation infrastructure to provide crowd flow analytics for simulated crowds, providing actionable data to the PANYNJ for decision-making and planning purposes.