Profile Picture
吴亚东

Ya-Dong Wu

wuyadong301@sjtu.edu.cn

I am a tenure-track associate professor at John Hopcroft Center for Computer Science, Shanghai Jiao Tong University. My research focuses on quantum information lying at the intersection of quantum physics and computer science.
My research interests include: (1) applying machine learning for quantum information science, and (2) continuous-variable quantum information theory.

research description

Now I have open positions for postdoc working on AI+quantum. Please contact me if you are interested!

Working Experience

Education

News

My group

Publications

Machine Learning for Quantum:

  1. X Gao, Y Zhu, FX Sun, YD Wu, Q He, "Foundation Model for Unified Characterization of Optical Quantum States", arXiv
  2. Y Du, Y Zhu, Y-H Zhang, M-H Hsieh, P Rebentrost, W Gao, Y-Z You, J Eisert, G Chiribella, D Tao, B C. Sanders, YD Wu, "Artificial intelligence for representing and characterizing quantum systems", Nature Reviews Physics 2026
  3. J Huang, Y Zhu, G Chiribella, YD Wu, "Sequence-Model-Guided Measurement Selection for Quantum State Learning", arXiv
  4. X Gao, M Tian, FX Sun, YD Wu, Y Xiang, Q He, "Classifying Multipartite Continuous Variable Entanglement Structures through Data-augmented Neural Networks", Nature Machine Intelligence
  5. Y Zhu, T Xiao, G Zeng, G Chiribella, YD Wu, "Controlling Unknown Quantum States via Data-Driven State Representations", NPJ Quantum Information
  6. Y Zhu, YD Wu(co-first), Q Liu, Y Wang, G Chiribella, "Predictive modelling of quantum process with neural networks", arXiv
  7. YD Wu, Y Zhu, Y Wang, G Chiribella, “Learning quantum properties from short-range correlations using multi-task networks”, Nature Communications 2024 ("远见"公众号新闻) (News by Quantum Zeitgeist)
  8. YD Wu, Y Zhu, G Bai, Y Wang, G Chiribella, "Quantum Similarity Testing with Convolutional Neural Networks", Physical Review Letters 2023 (highlighted by Nature Computational Science) (News by NewScientist)
  9. Y Zhu, YD Wu(co-first), G Bai, DS Wang, Y Wang, G Chiribella, "Flexible Learning of Quantum States with Generative Query Neural Networks", Nature Communications 2022

Continuous-Variable Quantum Information:

  1. YD Wu, Y Zhu, G Chiribella, N Liu, “Efficient learning of continuous-variable quantum states”, Physical Review Research 2024
  2. YD Wu, G Chiribella, “Detecting quantum capacities of continuous-variable quantum channels”, Physical Review Research 2022
  3. YD Wu, G Bai, G Chiribella, N Liu, "Efficient Verification of Continuous-Variable Quantum States and Devices without Assuming Identical and Independent Operations", Physical Review Letters 2021
  4. YD Wu, B Sanders, “Efficient verification of bosonic quantum channels via benchmarking”, New Journal of Physics 2019
  5. M Ahmadi, YD Wu, B Sanders, “Relativistic (2,3)-threshold quantum secret sharing”, Physical Review D 2017
  6. YD Wu, J Zhou, X Gong, Y Guo, ZM Zhang, G He, "Continuous-variable measurement-device-independent multipartite communication", Physical Review A 2016

Other topics:

  1. KY Zhang, AJ Huang, K Tu, MH Li, C Zhang, W Qi, YD Wu, Y Yu, "Experimental Secure Multiparty Computation from Quantum Oblivious Transfer with Bit Commitment", NPJ quantum information 2026
  2. G Bai, YD Wu, Y Zhu, M Hayashi, G Chiribella, “Quantum causal unravelling”, NPJ quantum information 2022
  3. C Qian, YD Wu, Y Xiao, B Sanders, "Multiple uncertainty relation for accelerated quantum information", Physical Review D 2020
  4. M Jafarzadeh, YD Wu(co-first), Y Sanders, B Sanders, “Randomized benchmarking for qudit Clifford gates”, New Journal of Physics 2020
  5. YD Wu, A Khalid, B Sanders, “Efficient Code for Relativistic Quantum Summoning”, New Journal of Physics 2018