Research
Our research lies at the intersection of artificial intelligence, computer vision, and robotics. We work both on advancing the theory of learning and perception methods and on deploying them on real robotic and autonomous systems.
AI for Autonomous & Robotic Systems
Learning-based perception, decision making, and adaptation that allow autonomous agents to operate safely and reliably in complex, dynamic, and uncertain real-world environments.
Robotic & Computer Vision
Environmental and human-centered analysis and interaction: scene understanding, pose estimation, active perception, and visual analysis for robots.
Deep Reinforcement Learning
Robust and data-efficient reinforcement learning for control, navigation, and localization, including UAVs and other autonomous platforms.
Efficient AI
Lightweight, energy-efficient, and adaptive deep learning for embedded and resource-constrained platforms, including neuromorphic and photonic hardware.