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

Google Scholar, GitHubGitHub, CV (Chinese,English)

  • 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.

  • Our book "Recommender System: Frontiers and Practices" has been published in JD! Please read our intro.

Recent News
  • 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 - Latest English article about our AAAI 2021 paper! (MSR Blog)

  • 2021.1 - Latest Chinese article about our quantitative finance research! (WeChat, MSRA news)

  • 2020.12 - One paper about quantitative finance has been accepted in AAAI 2021.

  • 2020.4 - I'll serve as a co-chair for 2nd workshop on Practice of Deep Learning on High-dimensional Sparse Data in KDD 2020.

  • 2020.4 - Two papers about unbiased learning and knowledge graph-enhanced recommendation have been accepted in SIGIR 2020.

  • 2019.10 - One paper about sequential recommendation has been accepted in WSDM 2020 (AC rate: 15%).

  • 2019.7 - I will join Machine Learning Group of Microsoft Research Asia.

  • 2019.4 - One paper has been accepted in Research Track of KDD 2019 as an oral presentation (AC rate oral/total: 9.1/14.1%).

  • 2018.12 - Two papers have been accepted in AAAI 2019 (AC rate: 16.2%).

  • 2018.12 - Our paper “Deep Recurrent Survival Analysis” has been selected as an oral presentation on Jan. 27.


  • 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.




  • Modeling and Decision Optimization in Real-time Bidding Advertising (Chinese) (PDF)



Academic Service

  • PC member: ICML, NeurIPS, AAAI, SIGIR, etc.

  • Journal Reviewer: JMLR, TKDE, NeuralComputing, etc.