LIN Xiaodie 林小蝶
Research Assistant Professor
Xiaodie Lin received her B.Eng. degree in soft engineering from Sun Yat-sen University, Guangdong, China in 2019 and her Ph.D. degree in computer science and technology from the Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China in 2024. She joined the College of Computer and Data Science, Fuzhou University as an associate professor in August, 2024. She is currently working as a research assistant professor at the Department of Mechanical and Automation Engineering, the Chinese University of Hong Kong in November, 2024.
Research Interests
- Quantum information and quantum computing
- Quantum metrology
- Quantum machine learning
Journal Papers
- Chen, Z., Lin, L., Lin, X.(𝛼–𝛽), Wei, Z., & Yao, P. (2024). The generations of classical correlations via quantum schemes. IEEE Transactions on Information Theory, 70(6), 4160- 4169.
- Lin, X., Chen, Z., & Wei, Z. (2023). Quantifying quantum entanglement via a hybrid quantum-classical machine learning framework. Physical Review A, 107(6), 062409.
- Lin, X., Chen, Z., & Wei, Z. (2023). Quantifying unknown entanglement by neural networks. Quantum Information Processing, 22(9), 341.
- Chen, Z., Lin, X., & Wei, Z. (2023). Certifying unknown genuine multipartite entanglement by neural networks. Quantum Science and Technology, 8(3), 035029.
- Guo, Y., Lin, L., Cao, H., Zhang, C., Lin, X., Hu, X. M., …& Guo, G. C. (2023). Experimental entanglement quantification for unknown quantum states in a semi-device- independent manner. Science China Information Sciences, 66(8), 180506.
- Lin, X.(𝛼–𝛽), Wei, Z., & Yao, P. (2021). Quantum and classical hybrid generations for classical correlations. IEEE Transactions on Information Theory, 68(1), 302-310. (α-β) denotes alphabetical ordering.