Quantum Control
Optimal and robust control of quantum systems: programmable quantum matter, high-fidelity gate sequences, scalable entanglement compilation, and reinforcement-learning-based scheduling for quantum processors and networks.

Ph.D. Researcher, MIT EECS · Quantum Photonics Group
Quantum control, AI-driven co-design, and scalable quantum photonic systems.
Our paper Programmable Quantum Matter: Heralding Large Cluster States in Driven Inhomogeneous Spin Ensembles has been accepted in PRX Quantum. Read on arXiv
I will join IonQ as a summer intern, working on quantum error correction (QEC).
I am a Ph.D. researcher in the Quantum Photonics group at the Massachusetts Institute of Technology, advised by Prof. Dirk R. Englund.
My research focuses on quantum control, programmable quantum matter, and spin-photon interfaces for scalable quantum information systems.
I also collaborate with Prof. Kaiming He on machine-learning methods for co-designing quantum hardware and algorithms under realistic noise and resource constraints.
This website highlights my publications, research notes, and selected projects.
Optimal and robust control of quantum systems: programmable quantum matter, high-fidelity gate sequences, scalable entanglement compilation, and reinforcement-learning-based scheduling for quantum processors and networks.
Spin–photon and spin–optomechanical interfaces, microwave single-photon detection, quantum-dot and cavity QED systems, and experimental platforms for quantum communication and sensing.
AI-based co-design of quantum hardware and algorithms, physics-informed neural networks for PDE simulation, and learning-driven control for large-scale quantum systems.