【Date and Time】2-April-2026 14:30 (Beijing time)

【Venue】Room 526

【Host】  Meng-Jun Hu (Quantum Operating System Software Team)

【Title】 AI for Quantum: From Circuit Synthesis to Error Correction

【Speaker】 

Yan Ge is a postdoctoral researcher at Nanyang Technological University, Singapore, working in the group of Yuxuan Du. He received his bachelor's degree from the ACM Class at Shanghai Jiao Tong University and his Ph.D. from the Department of Computer Science at Shanghai Jiao Tong University, under the supervision of Junchi Yan. His research focuses on quantum computing and artificial intelligence. He has published over ten CCF Category A papers, including six as first or co-first author. He serves as a reviewer for conferences and journals such as ICML, NeurIPS, ICLR, and NPJ Quantum Information.

【Abstract】

With the full implementation of the 15th Five-Year Plan, the deep integration of quantum computing and artificial intelligence has become one of the core strategic directions for technological development in China. However, constrained by the scale and noise levels of current quantum hardware, large-scale commercial applications of Quantum for AI are still some way off. In contrast, AI for Quantum demonstrates more immediate and pressing engineering and scientific value in the short term, serving as a key bridge to cross the chasm of the noisy intermediate-scale quantum (NISQ) era.

This talk systematically explores how advanced classical AI algorithms can be leveraged to enhance the performance of quantum computing systems in a full-stack manner, from front-end compilation to back-end error correction. The first part of the talk reviews our series of work on circuit synthesis and quantum architecture search. The second part focuses on quantum error correction, particularly the scalability of neural network decoders and the feasibility validation of real-time decoding.