Murphy Yuezhen Niu

Murphy Yuezhen Niu is an Adjunct Assistant Professor at the University of Maryland's Institute for Advanced Computer Studies (UMIACS) and a former QuICS Fellow. She holds a PhD in theoretical and mathematical physics from MIT (2018) and previously worked at Google Quantum AI, focusing on quantum control optimization, quantum machine learning, and error correction. Her research integrates deep reinforcement learning and generative models with quantum computing, leveraging superconducting qubit systems.

Education: PhD in Theoretical and Mathematical Physics (MIT, 2018); Prior roles include Senior Research Scientist at Google Quantum AI (2023–2024).

Research Interests: Quantum error correction, quantum algorithm design, photonic quantum computing, and hybrid quantum-classical systems. She explores topics like quantum control optimization using AI, fault-tolerant architectures, and applications of quantum machine learning to quantum processor design.

Articles Trends: Recent work emphasizes quantum error correction below surface code thresholds, quantum photonic neural networks, and disorder-free localization in quantum systems. Themes include scaling logical qubits, optimizing quantum gates, and leveraging machine learning for error decoding.

• Awards: Claude E. Shannon Research Assistantship (for work at photonic quantum computation/quantum cryptography intersection).

Advising & Grants: No students listed. Active in collaborative projects at UMIACS and UCSB.

Labs/Teams: Joint Center for Quantum Information and Computer Science (QuICS), Google Quantum AI (prior role).