任侃博士，现任上海科技大学助理教授，曾就职于微软亚洲研究院并担任高级研究员。他主要的研究领域包括数据挖掘与机器学习，特别是时空数据建模、自监督学习与基础模型、决策优化方法与人工智能体，及其在医疗健康、推荐系统与金融等领域的应用。他在数据挖掘与机器学习领域顶级会议与期刊发表了四十余篇论文，包括NeurIPS、ICLR、KDD、SIGIR、AAAI等；同时，他长期为NeurIPS、KDD等会议担任程序委员，并为JMLR、TKDE等期刊担任评审，著有《推荐系统：前沿与实践》。任侃在浙江大学获得计算机科学与技术工学学士学位，在上海交通大学获得计算机科学与技术博士学位。

更多信息请参考个人主页：https://www.saying.ren/ 

Selected Publications

• MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks, L. Zhang, Y. Zhang, K. Ren (corresponding), D. Li, Y. Yang
  The 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024).

• ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling, Y. Chen, K. Ren (corresponding), Y. Wang, Y. Fang, W. Sun, D. Li.
  The 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

• Learning Topology-Agnostic EEG Representations with Geometry-Aware Modeling, K. Yi, Y. Wang, K. Ren (corresponding), D. Li.
  The 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

• 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.