About
My name is Congcong Zheng, currently a fourth-year Ph.D. student in the School of Information Science and Engineering at Southeast University, Nanjing, advised by Prof. Xutao Yu and Prof. Zaichen Zhang. I received my B.E. degree from the School of Electronics and Information Engineering at Hangzhou Dianzi University in 2022. I am also a research intern at Baidu Quantum in 2022, supervised by Kun Wang.
I expect to graduate in the first half of 2027 and am seeking postdoctoral opportunities. If you are interested in my research, please feel free to reach out via email. I am always happy to chat!
Research Interests
I am interested in Quantum Learning Theory, which studies how to learn unknown quantum systems under limited resources. Relevant topics include quantum tomography, quantum verification/certification, stabilizer testing/learning, and quantum property testing.
- Learning Algorithms: designing efficient quantum algorithms for typical quantum learning tasks under constraints such as limited entanglement and quantum memory.
- Learning Complexity: determining the minimal resources required to learn an unknown quantum object.
- Learning Methods: developing tools based on randomized measurements, tensor networks, and representation theory.
News
- [2025-08] Our work "Optimal Distributed Similarity Estimation of Quantum Channels" is accepted as a talk at AQIS 2026.
- [2026-05] Our work "Efficient verification of stabilizer code subspaces with local measurements" is published in Quantum Science and Technology.
- [2026-04] Our work "Distributed quantum inner product estimation with structured random circuits" is published in npj Quantum Information.
- [2025-12] Our work "Optimal Distributed Similarity Estimation of Quantum Channels" is posted on arXiv.
- [2025-10] Received the 2025 National Scholarship.
- [2025-08] Our work "GHZ-W Genuinely Entangled Subspace Verification with Adaptive Local Measurements" is published in Science China Information Sciences.
- [2025-08] Our work "Distributed quantum inner product estimation with shallow circuits" is accepted as a talk at AQIS 2025.
- [2025-06] Our work "Quantum process overlapping tomography: Theory and experiment" is published in Physical Review Applied.
- [2025-01] Our work "Quantum comb tomography via learning isometries on stiefel manifold" is published in Physical Review Letters.
- [2024-01] Our work "Cross-platform comparison of arbitrary quantum processes" is published in npj Quantum Information.
