個人主頁： https://if-lab-pku.github.io/
主要研究方向
高能效移動邊緣計算系統
高性能分布式與大規模人工智能系統
新型移動人工智能應用
主要科研項目
高能效人工智能計算，研究針對人工智能軟硬件的加速算法和計算體系結構優化，并實現電子設計自動化（EDA）的協同創新
高性能分布式和大規模計算系統，研究和設計面向移動邊緣終端的大規模人工智能部署和計算系統優化技術；
新型移動智能應用，結合人工智能和高性能系統，探索多模态計算，泛用智能交互等新型交互智能應用。
論文代表作
[MLSys22][最佳論文獎] J. Mao, X. Chen, K. Nixon, C. Krieger, and Y. Chen. “MoDNN: Local Distributed Mobile Computing System for Deep Neural Network,” in Proceedings of the International Conference on Design Automation and Test in Europe, pp. 1396∼1401, 2017.
[DAC21] Z. Xu, F. Yu, J. Xiong, and X. Chen. “Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration,” in Proceedings of the Design Automation Conference, pp. 997∼1022, 2021.
[KDD21] F. Yu, W. Zhang, Z. Qin, Z. Xu, D. Wang, C. Liu, Z. Tian, and X. Chen. “Fed2: Feature-Aligned Federated Learning,” in Proceedings of the ACM SigKDD Conference on Knowledge Discovery and Data Mining, pp. 2066∼2074, 2021.
[DATE20][最佳論文提名] F. Yu, C. Liu, D. Wang, Y. Wang, and X. Chen. “AntiDOte: Attention- based Dynamic Optimization for Neural Network Runtime Efficiency,” in Proceedings of the International Conference on Design Automation and Test in Europe, pp. 951∼956, 2020.
[DATE17][最佳論文獎] J. Mao, X. Chen, K. Nixon, C. Krieger, and Y. Chen. “MoDNN: Local Distributed Mobile Computing System for Deep Neural Network,” in Proceedings of the International Conference on Design Automation and Test in Europe, pp. 1396∼1401, 2017.
