Quantum computing & learning
I develop dissipative algorithms and quantum linear algebra methods, and study how efficiently we can learn quantum dynamics from limited data. I also explore the fundamental limits of quantum computation and learning.
郭乃绪
Quantum ComputingAgents for Science
Quantum computing and AI
for scientific discovery.
What I’m working on
AI for scientific discovery
I’m building toward agents that invent methods and pursue scientific questions, starting with classical–quantum co-design and quantum-engineering environments.
Through QIQCOP, I’m exploring new ways to share open problems and collaborate.
For ideas and collaborations, let’s talk.
About me
I completed my PhD at the Centre for Quantum Technologies, National University of Singapore, supervised by Patrick Rebentrost. I will soon join Alan Aspuru-Guzik at the University of Toronto as a postdoctoral researcher.
Contact
Recent news
- Oct 2026
New paper: Perspective on AI and quantum open-source software.
- Oct 2026
Successfully defended my PhD thesis at the National University of Singapore on 7 October.
- Sep 2026
Near-Optimal Learning of Local Lindbladians accepted at SODA 2027.
- Sep 2026
Invited talk at IntelligenceX 2026, National University of Singapore.
- Sep 2026
New paper: Evaluating Verified Autonomy in Quantum Engineering (Quantum-Harbor and QIQCBench).