I am an Aerospace Ph.D. Candidate in the Land, Air and Space Robotics Laboratory at Texas A&M University passionate about developing provably safe control algorithms for autonomous systems. My research focuses on robotic and spacecraft applications, where I leverage insights from control theory, optimization, and estimation to enhance the reliability of autonomous operations in complex environments.
Texas A&M University
Ph.D. Aerospace Engineering, (2021 - Expected May 2025)
Cornell University
B.S. Mechanical and Aerospace Engineering, (2017 - 2021)
Magna Cum Laude
Novel class of CBFs for online controlled invariance of uncertain systems with input constraints, whilst reducing conservatism via an observer.
Novel state estimation formulation for improving filter stability and statistical consistency for nonlinear systems.
Novel class of CBFs for online controlled invariance of systems with input constraints and unmodelled dynamics disturbances.
Closed-loop GNC framework for spacecraft servicing module deployment, optimizing low-thrust trajectories while addressing state constraints and impact uncertainty.
RL-based on-orbit spacecraft inspection with safety ensured via control barrier functions and RTA, analyzing task performance under various state constraints.
Novel motion planning framework for directional sensors ensuring target visibility, obstacle avoidance, and efficiency in cluttered environments.
Control barrier functions and sensor fusion for safe closed-loop GNC in multi-agent satellite servicing missions.
RTA-enhanced RL training for 6-DOF spacecraft inspection, enforcing safety via control barrier functions and analyzing trade-offs in performance and safety.
Collision mitigation for low-thrust spacecraft in a quasi-periodic orbit using high order control barrier functions.
Safety-critical spacecraft control in the presence of faults and rapidly variable dynamics using sequential estimation and control barrier functions.
RL-based control for on-orbit spacecraft inspection, optimizing illumination and evaluating performance with statistically robust metrics.
Development of spacecraft constraints for multi-agent inspection mission, enforced using control barrier functions.
RL-based control for multirotor tracking of maneuvering ground targets using a fixed optical sensor, addressing occlusions and target motion types in simulation.
Stochastic control barrier functions and stochastic optimal control applied to classical economics problems.