E- Mail：jianmin@ustc.edu.cn
个人主页：http://staff.ustc.edu.cn/~jianmin/
实验室主页：http://ai.ustc.edu.cn
主要研究方向：认知机器人，深度强化学习，知识表示与推理。
吉建民，中国科学技术大学副教授，硕士生导师。在中国科学技术大学计算机学院获得学士、博士学位，曾任香港科技大学博士后，阿尔伯塔大学、卡内基梅隆大学访问学者。主要研究方向为认知机器人、知识表示与推理、深度强化学习。连续10年负责中科大“可佳”“佳佳”机器人认知模块，并获世界冠军。在人工智能、机器人顶级期刊和会议发表论文多篇。长期担任JAIR、AAAI、IJCAI、AAMAS、KR、ICRA等国际顶级期刊和会议（高级）程序委员会委员。
主要工程项目：
“可佳”、“佳佳”机器人认知系统 http://ai.ustc.edu.cn/
中国家用服务机器人仿真测试平台 http://www.wrighteagle.org/homesimulation/
获奖情况：
认知技术被《Artificial Intelligence》评为机器人认知方面十年最佳技术成果（Best Technique Solution）；
获得第23届国际人工智能联合大会（IJCAI-13）最佳自主机器人奖（Best Autonomous Robotics Video）
十篇代表性论著：
Jianmin Ji, Fangfang Liu, and Jia-Huai You*. Well-founded operators for normal hybrid MKNF knowledge bases. Theory and Practice of Logic Programming 17.5-6, pages 889-905, 2017.
Jianmin Ji, Hai Wan*, Kewen Wang, Zhe Wang, Chuhan Zhang, and Jiangtao Xu. Eliminating Disjunctions in Answer Set Programming by Restricted Unfolding. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), pages 1130-137, 2016.
Jianmin Ji, Yisong Wang*, and Jiahuai You. On Forgetting Postulates in Answer Set Programming. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI-15), pages 3076-3083, 2015.
Jianmin Ji, Hai Wan*, Ziwei Huo, and Zhenfeng Yuan. Simplifying a Logic Program Using Its Consequences. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI-15), pages 3069-3075, 2015.
Jianmin Ji, Hai Wan*, and Peng Xiao. On Elementary Loops and Proper Loops for Disjunctive Logic Programs. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), pages 1518-1524, 2015.
Jianmin Ji, Hai Wan*, Ziwei Huo, and Zhenfeng Yuan. Splitting a Logic Program Revisited. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), pages 1511-1517, 2015.
Jianmin Ji and Fangzhen Lin*. Position Systems in Dynamic Domains. Journal of Philosophical Logic (JPL) 44(2), pages 147-161, 2015.
Jianmin Ji and Xiaoping Chen*. A Weighted Causal Theory for Acquiring and Utilizing Open Knowledge. International Journal of Approximate Reasoning (IJAR) 55(9), pages 2071-2082, 2014.
Jianmin Ji, Hai Wan*, Peng Xiao, Ziwei Huo, and Zhanhao Xiao. Elementary Loops Revisited. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), pages 1063-1069, 2014.
Xiaoping Chen, Jianmin Ji*, and Fangzhen Lin. Computing loops with at most one external support rule. ACM Transactions on Computational Logic (TOCL) 14(1), pages 3-37, 2013.