个人简历

个人信息
　　礼欣，博士，博士后。
　　吉林大学学士、硕士，师从孙吉贵教授。香港浸会大学(Hong Kong Baptist University)博士、博士后，师从Dr. William K. Cheung 与 Prof. Jiming Liu。曾作为访问学者访问University of Waterloo, Canada (Host: Prof. Pascal Poupart)，作为高级访问学者访问University of Technology Sydney, Australia (Host: Prof. Ivor W. Tsang). 目前主要从事数据挖掘、深度学习、强化学习、表示学习的相关理论研究和技术应用。近年来以第一作者及通讯作者身份在ICML、IJCAI、AAAI、ECML-PKDD、IEEE TCYB、TOIS、TKDE等人工智能、机器学习领域的知名国际会议和期刊发表若干篇学术论文。自2010-2019年担任The IEEE Intelligent Informatics Bulletin, Assistant Managing Editor。
　　在学生指导方面，鼓励并推荐学生交流访问，指导的研究生同学曾赴香港浸会大学、香港理工大学、美国斯坦福大学、澳大利亚悉尼科技大学访问。指导的硕士研究生发表多篇CCF A类会议论文，CCF A类/SCI一区期刊论文，并获得国家奖学金。毕业研究生去向包括微软、阿里、字节跳动、腾讯、京东、美团，滴滴等知名企业，或中国招商银行(总行)，中国工商银行(总行)，中科院电子所，中科院信工所，中国外交部等企事业单位

研究领域

机器学习、深度(强化)学习、表示学习理论及应用，包括：
　　复杂网络数据挖掘、城市计算、医疗及公共卫生领域的应用，如：疾病诊断/预测；
　　以及深度学习/深度强化学习技术在工业大数据、机器人领域的应用"承担科研情况
　　作为项目负责人、子课题负责人，获得基金支持的项目包括：
　　2018.01 - 2021.12 国家自然科学基金面上项目：61772074，项目负责人
　　2017.09 - 2020.09 国家重点研发计划，网络空间安全重点专项，**发现与**预测项目，子课题负责人
　　2014.01 - 2016.12 国家自然科学基金青年项目：61300178，项目负责人
　　2013.01 - 2017.08 国家重点基础研究发展计划(973项目)：社交网络分析与网络信息传播，子课题负责人
　　2012.01 - 2014.12 教育部博士点新教师基金：20111101120030，项目负责人
　　2012.01 - 2013.12 北京理工大学基础研究基金，项目负责人
　　2010.01 - 2011.12 符号计算与知识工程教育部重点实验室对外开放基金项目，项目负责人
　　作为主要参与人参与的其他项目还包括：
　　自然科学基金重点项目：无源感知网路基础理论与关键技术(61432015)"

近期论文

代表性学术成果
　　CCF A/B类会议论文
　　[1] Li Zhang, Xin Li*, et al. “Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal”, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Pages: 6778-6785, Aug., 2019, February, 2020, New York City, USA.
　　[2] Rui Ye, Xin Li*, et al. “A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment”, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), Pages: 4135-4141, Aug., 2019, Macao, China.
　　[3] Jing He, Xin Li*, Lejian Liao, et al, “Inferring Continuous Latent Preference on Transition Intervals for Next Point-of-Interest Recommendation”, ECML/PKDD (2) 2018: 741-756, Sept. 2018, Dublin, Ireland.
　　[4] Shengnan Li, Xin Li*, et al. “Non-translational Alignment for Multi-relational Networks”, in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), Pages: 4180-4186, Aug., 2018, Stockholm, Sweden.
　　[5] Lin Liu, Xin Li*, William K. Cheung, Chengcheng Xu, “A Structural Representation Learning for Multi-relational Networks”, in Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Pages: 4047-4053, Aug., 2017, Melbourne, Australia. Source Code：https://github.com/luoxiaolin521/MNE
　　[6] Jing He, Xin Li*, Lejian Liao, “Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking”, in Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Pages: 1837-1843, Aug., 2017, Melbourne, Australia. Source Code：https://github.com/skyhejing/IJCAI2017
　　[7] Jing He, Xin Li*, Lejian Liao, Dandan Song, William K. Cheung, Inferring A Personalized Next Point-of-Interest Recommendation Model with Latent Behavior Patterns, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Pages: 137-143, February, 2016, Phoenix, Arizona USA. Source Code：https://github.com/skyhejing/AAAI2016
　　[8] Li Liu, William K. Cheung, Xin Li*, Lejian Liao, “Aligning Users Across Social Networks Using Network Embedding”, in Proceedings of the 25th International Joint Conf0erence on Artificial Intelligence (IJCAI), Pages: 1774-1780, July, 2016, New York City, USA. Source Code：https://github.com/ColaLL/AcrossNetworkEmbeddingSynthetic
　　[9] Xin Li*, William K. Cheung, Jiming Liu, Zhili Wu, “A Novel Orthogonal NMF-Based Belief Compression for POMDPs”, in Proceedings of 24th International Conference on Machine Learning (ICML), Pages: 537 -544 Corvallis, OR, US, 2007.
　　
　　arXiv论文
　　[1] Pengfei Zhu, Xin Li*, Pascal Poupart, “On Improving Deep Reinforcement Learning for POMDPs ”. CoRR abs/1704.07978(2017) . Source Code：https://github.com/bit1029public/ADRQN
　　[2] Huiting Hong, Xin Li*, et al.“GANE: A Generative Adversarial Network Embedding”. CoRR abs/1805.07324 (2018) .
　　
　　期刊论文
　　[1] Xin Li, Dongcheng Han, Jing He, Lejian Liao, Mingzhong Wang: Next and Next New POI Recommendation via Latent Behavior Pattern Inference. ACM Trans. Inf. Syst. 37(4): 46:1-46:28 (2019) (CCF A类期刊)
　　[2] Xin Li, et al., “Deep trajectory: a deep learning approach for mobile advertising in vehicular networks”, Neural Computing and Applications (NCAA), 31(7): 2813-2825 (2019)
　　[3] Jing He, Xin Li*, Lejian Liao, “Next Point-of-Interest Recommendation via a Category-aware Listwise Bayesian Personalized Ranking”, Journal of Computational Science (JOCS), 28: 206-216 (2018)
　　[4] Xin Li, Mingming Jiang, Huiting Hong, Lejian Liao, “Time-aware Personalized Point-of-Interest Recommendation via High-order Tensor Factorization”, ACM Trans. Inf. Syst. 35(4): 31:1-31:23 (2017) (CCF A类期刊)
　　[5] Meng Zhou, Xin Li*, Lejian Liao, “On preventing location attacks for Urban Vehicular Networks” , Mobile Information System (MIS), Volume 2016, Pages:1-13, December 2016
　　[6] Jialiang Chen, Xin Li*, William K. Cheung, Kan Li, “Effective Successive POI Recommendation Inferred with Individual Behavior and Group Preference”, Neurocomputing 210: 116-129 (2016)
　　[7] Chunshan Li, William K. Cheung, Yunming Ye, Xiaofeng Zhang, Dian-Hui Chu, Xin Li: The Author-Topic-Community model for author interest profiling and community discovery. Knowledge and Information System (KAIS) 44(2): 359-383 (2015) (CCF B类期刊)
　　[8] Xin Li, William K. Cheung, Jiming Liu, \
　[1] IEEE, CCF 会员
　　[2] The IEEE Intelligent Informatics Bulletin, Assistant Managing Editor (2010-2019)
　　[3] IUCC 2015, HENA 2016, CIKM 2017, 2019, AAAI 2018, 2019, IJCAI 2018, 2019, NeurIPS 2019 PC member
　　[4] TKDE, TOC, TNNLS, TOIS, TNSM, 电子学报等期刊审稿人