Jianfei Chen

Jianfei Chen is an Associate Professor in the Department of Computer Science and Technology at Tsinghua University. His research interests include machine learning, deep learning, and Bayesian methods. His work focuses on developing efficient algorithms and theoretical frameworks for deep learning, addressing challenges such as computational intensity, slow convergence, and high memory consumption. Chen has published extensively in top international conferences such as NeurIPS, ICML, and ICLR, and his research has been recognized through open-source software releases like ActNN, WarpLDA, and ZhuSuan. His work is supported by the Youth Fund of the National Natural Science Foundation of China.

Jianfei Chen is an Associate Professor at Tsinghua University, specializing in Machine Learning. His research focuses on advancing diffusion probabilistic models through efficient sampling techniques, such as Dpm-solver and its subsequent improvements like Dpm-solver++ and Dpm-solver-v3. He also explores parameter-efficient fine-tuning methods for large-scale pre-trained language models, including Delta tuning. Chen's work extends to optimizing neural network training and inference, with contributions to sparse attention mechanisms and memory-efficient training techniques. His research also includes applications in natural language processing, reinforcement learning, and topic modeling, emphasizing scalability and efficiency in machine learning systems.