The Autonomous Control and Decision Systems (ACDS) Laboratory is part of the Flight Mechanics and Controls (FMC) group at the Daniel Guggenheim School of Aerospace Engineering, Georgia Institute of Technology (GaTech). The ACDS laboratory is also affiliated with the Institute for Robotics and Intelligent Machines (IRIM), the Decision Control Lab (DCL) and the Center for Machine Learning at Georgia Tech.

The research objective of the ACDS lab is to develop computational methods grounded on first principles, for learning and control of engineered, artificial and natural systems characterized by different notions of complexity. These notions include nonlinearities, uncertainty, high dimensionality and the existence of multiple temporal and/or spatial scales. Such characteristics appear in systems in autonomy and robotics, applied physics, artificial intelligence, economics, networked control systems and financial processes.  On the theoretical side, research in ACDS lab spans the areas of stochastic optimal control and dynamical systems theory, information theory, reinforcement learning, dynamic and large-scale distributed optimization.

We are always looking for exceptional students, postdocs and visitor scholars. Our current research thrusts include three scientific areas. The first area is on learning-to-optimize for large-scale distributed optimal control problems. Applications include general supply-demand systems, swarms, and multi-agent autonomous systems in robotics, aerospace engineering and economics. The second area is on generative AI methods with an emphasis on stochastic and robust optimal control and applications in the area of AI for science. The third area is on safe perceptual planning and control methods for safety critical dynamical systems in robotics and aerospace engineering. If you are interested in joining our group, you can directly contact me. We have particular interests for candidates with a strong background on optimization, control and statistics.