Kan Ren (任侃)
Kan Ren , Senior Researcher
Microsoft Research Asia
Office: 43rd Floor, International AI Tower,
No.701 Yunjin Rd., Xuhui District,
Shanghai, China
kan.ren(-AT-)microsoft.com
Google Scholar , GitHub
I'm now looking for prospective student interns (preferably more than 3 months) to work together on sequence data modeling with applications in healthcare and finance, and (sequential) decision making optimization with cutting-edge machine learning technologies. Please drop me an email with your resume if you are interested.
Recent News
2023.9 - Two papers about irregular time-series modeling and EEG model pretraining have been accepted in NeurIPS 2023.
2023.8 - Our work about AIGC through brain-computer interface (BCI) has been online. Please checkout this .
2023.7 - Checkout the latest Chinese article about our research of RL for Finance and Qlib toolkit ! (WeChat , MSRA News )
2023.5 - Our work about AI for healthcare on neonatal seizure detection has been accepted in SMC 2023.
2023.5 - Our work about reinforcement learning for finance has been accepted in KDD 2023.
2023.4 - Our work MLCopilot about LLMs for machine learning tasks has been online.
2023.4 - One paper about brain-inspired neural network has been accepted in ICML 2023.
2023.3 - The website of our SeqML research (machine intelligence on sequence data) has been online.
2023.1 - One paper about enseble learning for pretrained models has been accepted in ICLR 2023.
2022.11 - Two papers about spatial-temporal data mining and efficient ensemble learning have been accepted in AAAI 2023.
2022.9 - Two papers about AutoRL and Transformer in offline RL have been accepted in NeurIPS 2022.
2022.4 - One paper about policy ensemble in reinforcement learning has been accepted in IJCAI 2022.
2021.8 - Two papers about sequential user modeling and sequence data generation have been accepted in CIKM 2021 and ICDM 2021.
2021.2 - The latest English article about our AAAI 2021 paper! (MSR Blog )
2021.1 - The latest Chinese article about our quantitative finance research! (WeChat , MSRA news )
2020.12 - One paper about quantitative finance has been accepted in AAAI 2021.
2018.12 - Our paper “Deep Recurrent Survival Analysis” has been selected as an oral presentation on Jan. 27.
Research
Data mining: sequence data mining and time-series data modeling.
Machine learning: meta-learning, AutoML and ensemble learning.
Reinforcement learning and its real-world applications.
Publications
Preprint
Seeing through the Brain: Image Reconstruction of Visual Perception from Human Brain Signals , Y. Lan, K. Ren (corresponding), Y. Wang, W. Zheng, et al.
MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks , L. Zhang, Y. Zhang, K. Ren (corresponding), et al.
Is Risk-Sensitive Reinforcement Learning Properly Resolved? , R. Zhou, M. Liu, K. Ren (corresponding), et al.
Selected
Protecting the Future: Neonatal Seizure Detection with Spatial-Temporal Modeling , Z. Li, Y. Fang, Y. Li, K. Ren (corresponding), et al.
IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2023 .
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance , Y. Fang, Z. Tang, K. Ren (corresponding), W. Liu, et al.
Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, 2023 .
CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling , Y. Wang, X. Jiang, K. Ren, et al.
Fortieth International Conference on Machine Learning (ICML-23) .
SIMPLE: Specialized Model-Sample Matching for Domain Generalization , Z. Li, K. Ren (corresponding), et al.
Eleventh International Conference on Learning Representations (ICLR 2023) .
Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling , Y. Fang, K. Ren (corresponding), et al.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23) .
Towards Inference Efficient Deep Ensemble Learning , Z. Li, K. Ren (corresponding), et al.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23) .
Bootstrapped Transformer for Offline Reinforcement Learning , K. Wang, H. Zhao, X. Luo, K. Ren (corresponding), et al.
The 36th Conference on Neural Information Processing Systems (NeurIPS 2022) .
Reinforcement Learning with Automated Auxiliary Loss Search , T. He, Y. Zhang, K. Ren (corresponding), et al.
The 36th Conference on Neural Information Processing Systems (NeurIPS 2022) .
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble , Z. Yang, K. Ren (corresponding), et al.
The 31st International Joint Conference on Artificial Intelligence (IJCAI-22) .
Towards Generating Real-World Time Series Data , H. Pei, K. Ren (corresponding), et al.
The 21st IEEE International Conference on Data Mining (ICDM) .
Universal Trading for Order Execution with Oracle Policy Distillation , Y. Fang, K. Ren (corresponding), et al.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21) .
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling , J. Qin, K. Ren (corresponding), Y. Fang, W. Zhang and Y. Yu.
Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM 2020) .
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction , K. Ren* , J. Qin*, Y. Fang*, W. Zhang, et al. (* = equal contribution)
Proceedings of 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019) .
Deep Recurrent Survival Analysis , K. Ren , J. Qin, L. Zheng, Z. Yang, W. Zhang, L. Qiu, Y. Yu
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) .
Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising , K. Ren , W. Zhang, K. Chang, Y. Rong, Y. Yu and J. Wang
IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 4, pp. 645-659, April 1 2018 .
Real-Time Bidding by Reinforcement Learning in Display Advertising , H. Cai, K. Ren , W. Zhang, K. Malialis, J. Wang, Y. Yu, D. Guo
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining Pages 661-670 .
Product-Based Neural Networks for User Response Prediction , Y. Qu, H. Cai, K. Ren , W. Zhang, Y. Yu, Y. Wen, J. Wang
2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona, 2016, pp. 1149-1154 .
Thesis
Topical
Chronological
Academic Service
PC member: ICML, NeurIPS, AAAI, SIGIR, etc.
Journal Reviewer: JMLR, TKDE, NeuralComputing, etc.
Education