Use quantum computers and machine learning to solve real-world problems.
Quantum Machine Learning
Develop machine learning methods used on quantum computers.
Citation
- Hanqi Jiang†, Yi Pan†, Junhao Chen†, Zhengjiang Liu, Lichao Sun, Quanzheng Li, Lu Zhang, Dajiang Zhu, Xianqiao Wang, Wei Liu, Xiang Li, Gang Li, Wei Zhang, Lin Zhao, Xiaowei Yu, Yingfeng Wang, and Tianming Liu*, “Quantum Artificial Intelligence: A Comprehensive Survey,” Meta-Radiology, vol. 4, no. 1, pp. 100205, 2026.
- Yi Pan†, Hanqi Jiang†, Junhao Chen, Yiwei Li, Huaqin Zhao, Lin Zhao, Yohannes Abate, Yingfeng Wang*, and Tianming Liu*, “Bridging Classical and Quantum Computing for Next-Generation Language Models,” Proceedings of the AAAI Symposium Series, vol. 7, no. 1, pp. 381-389, 2025.
- Afrar Jahin, Yi Pan, Yingfeng Wang*, Tianming Liu*, and Wei Zhang*, “Quantum-Classical Hybrid Molecular Autoencoder for Advancing Classical Decoding,” Proceedings of the AAAI Symposium Series, vol. 7, no. 1, pp. 368-373, 2025.
- Yi Pan†, Hanqi Jiang†, Wei Ruan, Dajiang Zhu, Xiang Li, Yohannes Abate, Yingfeng Wang*, and Tianming Liu*, “MolQAE: Quantum Autoencoder for Molecular Representation Learning,” 2025 IEEE International Conference on Quantum Artificial Intelligence (IEEE QAI), pp. 98-105, 2025.
Quantum Computing for Metabolite Identification
Integrate quantum computing to speed up metabolite identification
Citation
- Li-An Tsai, Estelle Nuckels, and Yingfeng Wang*, “Integrating Quantum Computing into De Novo Metabolite Identification,” Journal of Systemics, Cybernetics and Informatics, vol. 21, no. 2, pp. 83-86, 2023. (Also see IMCIC 2023)
- Li-An Tsai, Estelle Nuckels, and Yingfeng Wang*, “Integrating Quantum Computing into De Novo Metabolite Identification,” Proceedings of the International Multi-Conference on Complexity, Informatics and Cybernetics (IMCIC), pp. 84-87, 2023.