Naixu Guo (郭乃绪)
I am a fourth-year PhD student at CQT, advised by Patrick Rebentrost and Miklos Santha. Previously, I graduated from Kyoto University and Osaka University, under the supervision of Keisuke Fujii and Kosuke Mitarai. To know more about quantum machine learning, welcome to read our book.
I am on the job market this year, and actively looking for postdoc positions and other opportunities.
Research Focus
Explore the principles of nature to pioneer transformative algorithms and new paradigms of intelligence for accelerating scientific discovery.
Quantum simulation and algorithm
Artificial Intelligence (AI) for Science
Recent News
-
[11/2025] Our work Fast-forwardable Lindbladians imply quantum phase estimation has been accepted at QIP 2026.
-
[10/2025] I gave invited taks on Quantum algorithms for linear differential equation and phase estimation via Lindbladians at Institute for Quantum Computing and Oxford University.
-
[10/2025] Our new works Fast-forwardable Lindbladians imply quantum phase estimation, Accelerating Inference for Multilayer Neural Networks with Quantum Computers haven been out on arXiv.
-
[08/2025] Our paper Online Learning of Pure States is as Hard as Mixed States has been accepted by NeurIPS 2025.
-
[08/2025] Our paper Design nearly optimal quantum algorithm for linear differential equations via Lindbladians has been accepted by Physical Review Letters.
Get in Touch
I'm always interested in discussing research collaborations, opportunities, or just having a chat about quantum computing and AI.