教育经历
2004年，美国麻省理工学院媒体实验室, 机器学习, 获博士学位；
2000年，美国马里兰大学, 电子与计算机工程, 获硕士学位；
1998年，中国科学院自动化研究所, 模式识别与人工智能, 获硕士学位；
1995年，华中科技大学, 自动控制, 获学士学位；
工作经历
2023年至今，上海科学智能研究院，院长；
2021年至今，复旦大学, 人工智能创新与产业研究院, 教授/院长；
蚂蚁集团， 副总裁、首席AI科学家、达摩院金融智能负责人；
淘宝(中国)软件有限公司， 副总裁；
美国普渡大学，计算机科学系、生物系，终身（副）教授；
美国麻省理工学院CSAIL实验室与怀特黑德生物医学研究所，博士后；
研究方向
大规模机器学习，深度学习，贝叶斯推理，概率图模型；
生物信息学, 基因组及蛋白组学，大脑图像分析；
智能风控，智能营销，搜索推荐。
主要成果
曾领导构建了阿里巴巴第一个大规模分布式机器学习平台，获2015年阿里技术最高奖；主导构建了蚂蚁集团的超大规模图神经学习与隐私计算平台，图神经学习平台获得中国人工智能科技最高奖吴文俊科技一等奖。领导蚂蚁AI 团队用AI 技术及相关产品赋能多项金融业务，包括智能风控、智能理赔、资金优化与智能客服等。推动并领导了全国高校算力第一的复旦大学CFFF 智算平台的建设。作为评委会主席创办了首个国内综合性科学智能大赛“世界科学智能大赛”。
曾任JMLR 编辑，ICML、AISTATS 等领域主席。曾获美国科学基金NSF Career 奖、微软牛顿研究突破奖、威康信托基金会研究奖、2021年中国人工智能学会优秀科技工作者。其工作被经济学人、MIT 技术评论报道，被哈佛大学商学院收录为AI 创新落地案例。
招生专业
依托大数据学院招收博士研究生，招生专业为统计学、电子信息。依托计算机科学技术学院招收博士研究生，招生专业为数据科学。
发表论文
在人工智能和计算生物学顶会和刊物上发表论文100余篇，近5年论文如下：
1. Ziqi Liu，Zhengwei Wu，Zhiqiang Zhang，Jun Zhou, Shuang Yang, Le Song and Yuan Qi, Bandit Samplers for Training Graph Neural Networks, Advances in Neural Information Processing Systems (NeurIPS), 2020.
2. Xiaofu Chang, Xuqin Liu, Jianfeng Wen, Shuang Li, Yanming Fang, Le Song, Yuan Qi, Continuous-Time Dynamic Graph Learning via Neural Interaction Processes, In Proceedings of CIKM, 2020.
3. Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song. Cost-Effective Incentive Allocation via Structured Counterfactual Inference. In Proceedings of the Thirty-Forth AAAI Conference on Artificial Intelligence (AAAI-20), 2020.
4. Hui Li, Kailiang Hu, Shaohua Zhang, Yuan Qi, Le Song. Double Neural Counterfactual Regret Minimization. In Proceedings of The International Conference on Learning Representations (ICLR), 2020.
5. Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song， Efficient Probabilistic Logic Reasoning with Graph Neural Networks，In Proceedings of The International Conference on Learning Representations (ICLR), 2020.
6. Binbin Hu, Zhiqiang Zhang, Jun Zhou, Jingli Fang, Quanhui Jia, Yanming Fang, Quan Yu and Yuan Qi, Loan Default Analysis with Multiplex Graph Learning, CIKM, 2020.
7. S. Yang , Z. Zhang , J. Zhou , Y. Wang , W. Sun , X. Zhong , Y. Fang , Q. Yu , Y. Qi, Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining in Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), 2020.
8. C. Chen, J. Zhou, B. Wu, W. Fang, L. Wang, Y. Qi, X. Zheng, Practical Privacy Preserving POI Recommendation, ACM Transactions on Intelligent Systems and Technology, July 2020, Article No.: 52 https://doi.org/10.1145/3394138.
9. C．Liang，Z. Liu，B. Liu，J. Zhou，X. Li，S. Yang，Y. Qi， Uncovering Insurance Fraud Conspiracy with Network Learning， In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'19)， 2019.
10.C. Qu, S. Mannor, H. Xu, Y. Qi, L. Song, J. Xiong. Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning. NIPS, 2019.
11.X. Chen, S. Li, H. Li, S. Jiang, Y. Qi, and L. Song. Generative adversarial user model for reinforcement learning based recommendation system. In Proceedings of International Conference on Machine Learning (ICML), 2019.
12. Z. Liu， D. Wang， Q. Yu，Z. Zhang，Y. Shen，J. Ma，W. Zhong，J. Gu，J. Zhou，S. Yang，Y. Qi， Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing，In Proceedings of the 28th ACM International Conference on Information and Knowledge Management（CIKM '19）, 2019.
13. Dixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, Yuan Qi, A Semi-Supervised Graph Attentive Network for Financial Fraud Detection, In Proceedings of IEEE International Conference on Data Mining (ICDM), 2019.
14. Ya-Lin Zhang，Jun Zhou，Wenhao Zheng，Ji Feng，Longfei Li，Ziqi Liu，Ming Li，Zhiqiang Zhang，Chaochao Chen，Xiaolong Li，Yuan Qi，Zhi-Hua Zhou， Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud，ACM Transactions on Intelligent Systems and Technology，Vol. 10, No. 5，2019.
15. Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song, Generative Adversarial User Model for Reinforcement Learning Based Recommendation System. in Proceedings of the 36th International Conference on Machine Learning, 2019.
16. Ziqi Liu，Chaochao Chen，Longfei Li，Jun Zhou，Xiaolong Li，Le Song，Yuan Qi，GeniePath: Graph Neural Networks with Adaptive Receptive Paths，in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), USA, 2019.
17.B. Hu, Z. Zhang, C. Shi, J. Zhou, X. Li, Y. Qi，Cash-out user detection based on attributed heterogeneous information network with a hierarchical attention mechanism，in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), USA, 2019 .
18. Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong. Latent Dirichlet Allocation for Internet Price War, in Proceedings of he Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), USA, 2019.
19.Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan Qi, TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial. 45th International Conference on Very Large Data Bases (VLDB-19)， 2019.
20.Tong Yin, Xiaotie Deng, Yuan Qi, Wei Chu, Jing Pan, Xiang Yan, Junwu Xiong. Personalized Behavior Prediction with Encoder-to-Decoder Structure, IEEE International Conference on Networking, Architecture and Storage (NAS), 2018
21. Yuan Qi and Jing Xiao, Fintech: AI powers financial services to improve people's lives, Communications of the ACM, October, 2018.
22.Jianbin Lin; Zhiqiang Zhang; Jun Zhou; Xiaolong Li; Jingli Fang; Yanming Fang; Quan Yu; Yuan Qi，NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay，In Proceedings of IEEE International Conference on Big Data (Big Data)，2018.
