I am currently a principal researcher at Tencent AI Lab, working on machine learning and natural language processing. Before joining Tencent in March 2018, I worked in the Deep Learning Technology Center (DLTC) at Microsoft Research, Redmond, WA. I completed my PhD in Electrical Engineering at University of California, Los Angeles (UCLA), in June 2014, where I worked in Adaptive Systems Laboratory (ASL), supervised by Prof. Ali H. Sayed.
Email: chenjianshu at gmail dot com OR jianshuchen at tencent dot com
My research interests span several areas, including
- Machine learning (reinforcement learning, deep learning, unsupervised learning)
- Natural Language Processing
For more details, see my publications (also google scholar)
- Jianshu Chen, “Learning Language Representations with Logical Inductive Bias”, Proc. International Conference on Learning Representations (ICLR), 2023.
- Xiaoman Pan, Wenlin Yao, Hongming Zhang, Dian Yu, Dong Yu, Jianshu Chen, “Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models”, Proc. International Conference on Learning Representations (ICLR), 2023.
- Adithya M. Devraj and Jianshu Chen, “Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization”, Proc. Advances in Neural Information Processing Systems (NeurIPS), 2019.
- Yu Liu*, Jianshu Chen* and Li Deng*, "Unsupervised Sequence Classification using Sequential Output Statistics", Proc. 31st Annual Conference on Neural Information Processing Systems (NIPS), 2017. (*Equal contribution)
- Simon Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou, "Stochastic Variance Reduction Methods for Policy Evaluation", Proc. International Conference on Machine Learning (ICML), August 2017.