Four frontiers of computation

We study the physics and engineering of quantum information, from qubit coherence and error correction to hybrid quantum-classical algorithms with near-term impact.

• Qubit coherence & noise characterization
• Quantum error correction & mitigation
• Hybrid quantum-classical algorithms
• Quantum machine learning
• Workforce development & education

We build machine learning systems that are capable, transparent, and aligned with human values, with a strong emphasis on the ethics of deploying AI in the real world.

• Generative & foundation models
• Reinforcement & continual learning
• AI safety, alignment & governance
• Interpretability & trustworthy ML
• Applied AI for science

We design robots that perceive, reason, and act in unstructured environments, bridging AI research and the physical world through embodied learning.

• Perception & sensor fusion
• Learning-based control & planning
• Human-robot interaction & safety
• Embodied & sim-to-real learning
• Autonomous field robotics

We explore biologically inspired computation and the mathematical foundations (algorithms, theory, and neuromorphic ideas) that underpin next-generation intelligence.

• Neuromorphic & spiking models
• Theoretical foundations of learning
• Models of cognition & memory
• Algorithms & computational theory
• Energy-efficient computation