work Constrained Decoding for Robot Foundation Models How lessons from language models inspired a new way to make robot foundation models provably safe. Online STL Tree Search for Guided Imitation Learning Employed Monte Carlo Tree Search (MCTS) as a means of integrating STL specification into a vanilla LfD policy to improve constraint satisfaction. LfD MCTS STL Social Navigation Example‑based Constrained LTL specification learning using MaxSAT Learning LTL specifications with user specified constraints from system traces MaxSAT LTL Requirements Mining RL Robustness Analysis Analysing Robustness of Safe Reinforcement Learning Policies and Control Agents in the face of Environmental Deviations RL STL SE4AI Robustness Vision-enabled CBFs for High-speed Detection and Avoidance Designed new CBF formulations for safe separation of aircrafts at high speeds using pure vision based sensors Control Barrier Functions Reactive Control Collision Avoidance Safe Planning via Temporal Decomposition of STL A theory for Temporal Decomposition of Requirements Convex Optimisation STL Controller Synthesis Needle A comprehensive deep learning library from scratch, enabling GPU acceleration, automatic differentiation, and customizable layers, loss functions, and optimizers as part of DLSystems course project. Deep Learning Transformers CNNs CUDA Trust elicitation and restoration in assistive robots Investigated the impact of customization and perspective on perceived trust in RL policies for an assistive robotics context via a pilot user study Human Robot Interaction RL Assistive Robotics fun
