Name: Li Xin
Discipline: Computer Science and Technology
Title: Associate Professor, Doctoral Supervisor
Tel: (86) 139-114 - o CRH (54) + CRH (51) + CRH (48) + CRH (55) < br > E-mail: xinli@bit.edu.cn
Address: Room 1O3O, Central Teaching Building, Beijing Institute of Technology, No.5 Zhongguancun South Street, Haidian District, Beijing Personal Information
Li Xin, Ph.D., Postdoctoral Fellow.
He received his bachelor's degree and master's degree from Jilin University under the supervision of Professor Sun Jigui. Dr. William K. Cheung and Prof. Jiming Liu at Hong Kong Baptist University. Once visited University of Waterloo, Canada as a visiting scholar (Host: Prof. Pascal Poupart, Senior Visiting Scholar, University of Technology Sydney, Australia (Host: Prof. Ivor W. Tsang). At present, he is mainly engaged in the theoretical research and technical application of data mining, deep learning, reinforcement learning and presentation learning. In recent years, as the first author and corresponding author, he has published several academic papers in well-known international conferences and journals in the field of artificial intelligence and machine learning such as ICML, IJCAI, AAAI, ECML-PKDD, IEEE TCYB, TOIS, TKDE. He was Assistant Managing Editor of The IEEE Intelligent Informatics Bulletin from 2010 to 2019.
In terms of student guidance, we encourage and recommend students to exchange visits. The graduate students under our guidance have visited Hong Kong Baptist University, Hong Kong Polytechnic University, Stanford University in the United States, and University of Technology Sydney in Australia. The master students under the guidance have published many CCF Class A conference papers, CCF Class A /SCI Region I journal papers, and won national scholarships. Graduate programs include Microsoft, Ali, ByteDance, Tencent, Jingdong, Meituan, Didi and other well-known enterprises, or China Merchants Bank (head office), Industrial and Commercial Bank of China (head office), Institute of Electronics, Institute of Information and Industry of the Chinese Academy of Sciences, Ministry of Foreign Affairs and other enterprises and institutions.

Research Direction
Machine learning, deep (reinforcement) learning, presentation learning theory and applications, including:
Complex network data mining, urban computing, medical and public health applications, such as disease diagnosis/prediction;
And the application of deep learning/deep reinforcement learning technology in the field of industrial big data and robotics.

Personal Information
Li Xin, Ph.D., Postdoctoral Fellow.
He received his bachelor's degree and master's degree from Jilin University under the supervision of Professor Sun Jigui. Dr. William K. Cheung and Prof. Jiming Liu at Hong Kong Baptist University. Once visited University of Waterloo, Canada as a visiting scholar (Host: Prof. Pascal Poupart, Senior Visiting Scholar, University of Technology Sydney, Australia (Host: Prof. Ivor W. Tsang). At present, he is mainly engaged in the theoretical research and technical application of data mining, deep learning, reinforcement learning and presentation learning. In recent years, as the first author and corresponding author, he has published several academic papers in well-known international conferences and journals in the field of artificial intelligence and machine learning such as ICML, IJCAI, AAAI, ECML-PKDD, IEEE TCYB, TOIS, TKDE. He was Assistant Managing Editor of The IEEE Intelligent Informatics Bulletin from 2010 to 2019.
In terms of student guidance, we encourage and recommend students to exchange visits. The graduate students under our guidance have visited Hong Kong Baptist University, Hong Kong Polytechnic University, Stanford University in the United States, and University of Technology Sydney in Australia. The master students under the guidance have published many CCF Class A conference papers, CCF Class A /SCI Region I journal papers, and won national scholarships. Graduate programs include Microsoft, Ali, ByteDance, Tencent, Jingdong, Meituan, Didi and other well-known enterprises, or China Merchants Bank (head office), Industrial and Commercial Bank of China (head office), Institute of Electronics, Institute of Information and Industry of the Chinese Academy of Sciences, Ministry of Foreign Affairs and other enterprises and institutions.

Personal Information
Li Xin, Ph.D., Postdoctoral Fellow.
He received his bachelor's degree and master's degree from Jilin University under the supervision of Professor Sun Jigui. Dr. William K. Cheung and Prof. Jiming Liu at Hong Kong Baptist University. Once visited University of Waterloo, Canada as a visiting scholar (Host: Prof. Pascal Poupart, Senior Visiting Scholar, University of Technology Sydney, Australia (Host: Prof. Ivor W. Tsang). At present, he is mainly engaged in the theoretical research and technical application of data mining, deep learning, reinforcement learning and presentation learning. In recent years, as the first author and corresponding author, he has published several academic papers in well-known international conferences and journals in the field of artificial intelligence and machine learning such as ICML, IJCAI, AAAI, ECML-PKDD, IEEE TCYB, TOIS, TKDE. He was Assistant Managing Editor of The IEEE Intelligent Informatics Bulletin from 2010 to 2019.
In terms of student guidance, we encourage and recommend students to exchange visits. The graduate students under our guidance have visited Hong Kong Baptist University, Hong Kong Polytechnic University, Stanford University in the United States, and University of Technology Sydney in Australia. The master students under the guidance have published many CCF Class A conference papers, CCF Class A /SCI Region I journal papers, and won national scholarships. Graduate programs include Microsoft, Ali, ByteDance, Tencent, Jingdong, Meituan, Didi and other well-known enterprises, or China Merchants Bank (head office), Industrial and Commercial Bank of China (head office), Institute of Electronics, Institute of Information and Industry of the Chinese Academy of Sciences, Ministry of Foreign Affairs and other enterprises and institutions.

Representative Academic Achievements
The following articles are listed in reverse order by year of publication (* corresponding author)
CCF A/B Conference Papers
[1] Hongyu Zang, Xin Li*, Mingzhong Wang, “SimSR: Simple Distance-Based State Representations for Deep Reinforcement Learning”, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Pages:8997-9005, February, 2022, virtual, Canada.
[2] Li Zhang, Xin Li, Mingzhong Wang, Andong Tian, “Off-Policy Differentiable Logic Reinforcement Learning”, ECML/PKDD (2) 2021: 617-632, Sept.2021, Basque Country, Spain.
[3] 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, February, 2020, New York City, USA.
[4] 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.
[5] 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.
[6] 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.
[7] 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., 2017, Melbourne, Australia. The Source Code:https://github.com/luoxiaolin521/MNE < br > [8] 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., 2017, Melbourne, Australia. The Source Code:https://github.com/skyhejing/IJCAI2017 < br > [9] 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. The Source Code:https://github.com/skyhejing/AAAI2016 < br > [10] 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, out of 2016, New York City, USA. The Source Code:https://github.com/ColaLL/AcrossNetworkEmbeddingSynthetic < br > [11] 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 Papers
[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
Journal Articles (Selected)
[1] Huiting Hong, Xin Li*, Yuangang Pan, Ivor W. Tsang: Domain-Adversarial Network Alignment. IEEE Trans.Knowl.Data Eng.34 (7): 3211-3224 (2022) (CCF Class A Journal)
[2] Xin Li, et al. On improving knowledge graph facilitated simple question answering system. Neural Comput. Appl. 33(16): 10587-10596 (2021)
[3] Huiting Hong, Xin Li*, Mingzhong Wang: GANE: A Generative Adversarial Network Embedding. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2325-2335 (2020) (SCI Zone 1)
[4] Xin Li, et al.: Next and Next New POI Recommendation via Latent Behavior Pattern Inference. ACM Trans. Inf. Syst. 37(4): 46:1-46:28 (2019) (CCF Class A Journal)
[5] Xin Li, William K. Cheung, Jiming Liu, "Improving POMDP’s Tractability Via Belief Compression and Clustering", IEEE Transaction on Systems, Man and Cybernetics -- Part B 40(1):125-136 (2010) (SCI Region 1)
Awards received
In 2019, Beijing Institute of Technology excellent Master's degree thesis (Hong Huiting, Li Shengnan), instructor
In 2018, Excellent Master's thesis of Beijing Institute of Technology (Liu Lin), Instructor
In 2017, the third prize of the National College Student Information Security Competition, Instructor
In 2016, Excellent Master's thesis of Beijing Institute of Technology (Chen Jialiang), Instructor
Outstanding MOOC Teachers of Chinese Universities in 2015
In 2014, Bochuang Cup National College Students Embedded Internet of Things Design Competition, first prize in North China, second prize in the National Finals, instructor