Research
Our research advances the foundations of safe, intelligent, and collaborative autonomous systems, bridging machine learning, control theory, robotics, and embedded AI to enable reliable autonomy in complex real-world environments. Each of our four research directions has its own page with its funded projects and representative publications; the full list is on the Publications page.
- Direction 1
Safe Learning & Trustworthy Autonomy
We develop learning-based control and planning frameworks that enable autonomous systems to operate safely and reliably in uncertain, dynamic environments. Our research integrates reinforcement learning, safety-critical control, uncertainty quantification, and risk-aware decision-making to provide trustworthy autonomy with formal safety guarantees.
Explore this direction · 9 representative papers - Direction 2
Human–AI Collaboration & Multi-Agent Autonomy
We investigate intelligent collaboration between humans and autonomous agents, as well as coordination among interconnected robotic systems. Our research focuses on human-autonomy teaming, trust-aware decision-making, adaptive task allocation, cooperative perception, and distributed control to enable effective and resilient multi-agent operations.
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NASA · 2023–2027 -
NSF CHS: Small · 2020–2025
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- Direction 3
Space & Planetary Autonomy
We advance intelligent and reliable autonomy for spacecraft and planetary robotic systems operating in challenging and resource-constrained environments. Our research combines physics-informed reinforcement learning, safety-critical guidance and control, and efficient onboard planning to support autonomous space missions and planetary exploration.
- NASA Early Career Faculty Award (ECF25) · 2026–2029
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- Direction 4
Efficient Edge AI & Intelligent Perception
We develop resource-efficient machine learning and perception algorithms that bring advanced AI capabilities to embedded and robotic platforms. Our research emphasizes hardware-aware neural architecture search, energy-efficient computer vision, model optimization, and real-time edge intelligence for autonomous systems with limited computing resources.
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NVIDIA Academic Grant Program · 2026
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