Shuangyin Li(李双印)
Text data mining, Spatio-temporal data mining, Contrastive learning, and Deep learning.

Education
· PhD, from 2011.9 to 2014.12 in School of Information Science & Technology, Sun Yat-sen University. Major: Data Mining & Artificial Intelligence.
· Master, from 2009.9 to 2011.6 in School of Information Science & Technology, Sun Yat-sen University. Major: Data Mining & Artificial Intelligence.
· Bachelor, from 2005.9 to 2009.7 in School of Information Science & Engineering, Lanzhou University. Major: Computer Science.

Research Interests
My research interests include Text data mining, Spatio-temporal data mining, Transfer learning, Topic modeling and Deep learning with real-world applications. My major publications focus on text mining and knowledge learning. I have directed in numerous research and development projects and, obtained over 2M grants from government funding agencies and industries. I have served as the reviewer member of many international journals and as a member of program committees for many international conferences.

Fundings
· “Research on Textual Polysemy Representation Learning based on Topic Modeling and Transfer Learning”, National Natural Science Foundation of China (No. 62006083). From 2021 to 2023, RMB 240,000.
· “Mathematical modeling and Distributed computing for Large-scale Complex Dynamic Graphs on Route Planning”, National Key Research and Development Program of China (2020YFA0712500). From 2021 to 2025, RMB 920,000.
· “Research on Knowledge Learning and Reasoning Problems Based on Reinforcement Learning”, Science and Technology Projects in Guangzhou (202102020654). From 2021 to 2023, RMB 50,000.
· “Key Research on Text Semantic Learning and Enhancing based on Probabilitisc Simplex”, Natural Science Foundation of Guangdong. From 2022 to 2025, RMB 100,000.
· “Research on Artificial Intelligence Team Building Design and Human Resources Recruitment Strategy”. From 2021 to 2022, RMB 1M.

Representative Publications
§ [CIKM]Shuangyin Li (co-first author& Corresponding author), Huahang Li, Yuncheng Jiang, Ganzen Zhao, "CoPatE: a novel Contrastive Learning Framework for Patent Embeddings", 31st ACM International Conference on Information and Knowledge Management(CIKM), 2022
§ [TKDD]Shuangyin Li, Yu Zhang, Rong Pan. "Bi-Directional Recurrent Attentional Topic Model". ACM Trans. KDD,2020.
§ [WWW]Shuangyin Li, Yu Zhang, Rong Pan and Kaixiang Mo. "Adaptive Probabilistic Word Embedding". TheWebConf 2020 (WWW2020)
§ [IJCAI]Shuangyin Li, Rong Pan and Jun Yan. "Self-paced Compensatory Deep Boltzmann Machine for Semi-Structured Document Embedding". IJCAI 2017.
§ [AAAI]Shuangyin Li, Yu Zhang, Rong Pan and Mingzhi Mao. "Recurrent Attentional Topic Model". AAAI 2017.
 
Selected Publications
2022:
§ [CIKM]Shuangyin Li(co-first author& Corresponding author), Huahang Li, Yuncheng Jiang, Ganzen Zhao, "CoPatE: a novel Contrastive Learning Framework for Patent Embeddings", 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
§ [INS]Shuangyin Li, Weiwei Chen, Yu Zhang, Rong Pan, Gansen Zhao, Zhenhua Huang, Yong Tang, "A Context-Enhanced Sentence Representation Learning method for Close Domains with Topic Modeling", Information Sciences, 2022.
§ [TMC]Haoyu Luo, Tianxiang Chen, Xuejun Li, Shuangyin Li (Corresponding author), Chong Zhang, Gansen Zhao, and Xiao Liu, "KeepEdge: A Knowledge Distillation Empowered Edge Intelligence Framework for Visual Assisted Positioning in UAV Delivery", IEEE Transactions On Mobile Computing.
§ [WWWJ]Shuangyin Li, Haoyu Luo, Gansen Zhao, Mingdong Tang and Xiao Liu. "bi-Directional Bayesian Probabilistic Model based Hybrid Grained Semantic Matchmaking for Web Service Discovery", World Wide Web - Internet and Web Information Systems.
§ [CBC]Chengchuang Lin, Hanbiao Chen, Jiesheng Huang, Jing Peng, Li Guo, ZhirongYang, Jiahua Du, Shuangyin Li (Corresponding author), AihuaYin, GansenZhao. "ChromosomeNet: A massive dataset enabling benchmarking and building basedlines of clinical chromosome classification". Computational Biology and Chemistry.
2021:
§ [KBS]Shuangyin Li, Rong Pan, Haoyu Luo, Xiao Liu, Gansen Zhao. "Adaptive Cross-contextual Word Embedding for Word Polysemy with Unsupervised Topic Modeling". Knowledge-Based Systems.
§ [WWW]Huijuan Wang, Shuangyin Li (Corresponding author), Rong Pan. "An Adversarial Transfer Network for Knowledge Representation Learning". TheWebConf 2021 (WWW2021) .
§ [TCBB]Runye Huang, Chengchuang Lin, Gansen Zhao, Shuangyin Li, et al. A Clinical Dataset and Various Baselines for Chromosome Instance Segmentation. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
§ [IJCNN]Kaixin Huang, Shuangyin Li (Corresponding author), et al,. "A novel chromosome instance segmentation method based on geometry and deep learning", IJCNN 2021.
2020:
§ [TKDD]Shuangyin Li, Yu Zhang, Rong Pan. "Bi-Directional Recurrent Attentional Topic Model". ACM Trans. KDD.
§ [Neurocomputing]Shuangyin Li, Heng Wang, Rong Pan, Mingzhi Mao. "MemoryPath: A deep reinforcement learning framework for incorporating memory component into knowledge graph reasoning". Neurocomputing.
§ [APPL INTELL]Wenshen Xu, Shuangyin Li (Corresponding author), Yonghe Lu. "Usr-mtl: an unsupervised sentence representation learning framework with multi-task learning". Applied Intelligence. 
§ [IEEE ICWS]Shuangyin Li, Haoyu Luo and Gansen Zhao. "An Effective Semantic Matchmaking Model for Web Service Discovery". IEEE ICWS 2020.
§ [WWW]Shuangyin Li, Yu Zhang, Rong Pan and Kaixiang Mo. "Adaptive Probabilistic Word Embedding". TheWebConf 2020 (WWW2020).
2019:
§ [EMNLP]Heng Wang, Shuangyin Li, Rong Pan and Mingzhi Mao. "Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning". EMNLP 2019.
2018:
§ [AAAI]Peifeng Wang, Shuangyin Li and Rong Pan. "Incorporating GAN for Negative Sampling in Knowledge Representation Learning". AAAI 2018.
§ [AAAI]Kaixiang Mo, Yu Zhang, Shuangyin Li, Jiajun Li and Qiang Yang. "Personalizing a Dialogue System with Transfer Reinforcement Learning". AAAI 2018.
2017:
§ [CIKM]Zhengjie Huang, Zi Ye, Shuangyin Li and Rong Pan. "Length Adaptive Recurrent Model for Text Classification". CIKM 2017.
§ [IJCAI]Shuangyin Li, Rong Pan and Jun Yan. "Self-paced Compensatory Deep Boltzmann Machine for Semi-Structured Document Embedding". IJCAI 2017.
§ [AAAI]Shuangyin Li, Yu Zhang, Rong Pan and Mingzhi Mao. "Recurrent Attentional Topic Model". AAAI 2017.
Before 2016:
§ [UAI]Shuangyin Li, Rong Pan, Yu Zhang, Qiang Yang. "Correlated Tag Learning in Topic Model". UAI 2016. 
§ [ICDM]Shuangyin Li, Guan Huang, Ruiyang Tan, Rong Pan. "Tag-Weighted Dirichlet Allocation". ICDM 2013. 
§ [IJCAI]Shuangyin Li, Jiefei Li, and Rong Pan. "Tag-Weighted Topic Model for Mining Semi-Structured Documents". IJCAI 2013.
 
Patents
More than 10 patents in China, CN201611194573.8, CN201710023633.8, CN201710506259.7, CN201710617657.6, CN202010542552.0, CN202010542528.7, CN202010507774.9, CN202010506557.8, CN202020435232.0, CN202020433676.0, et al.
 
Academic Activities
Journal Reviewer and Conference (Senior) PC Member:
· TPAMI, IEEE Transactions on Circuits and Systems for Video Technology, Knowledge-Based Systems, Scientific Reports, Mathematics, et al.
· AAAI(2016, 2019, 2020, 2021, 2022), IJCAI(2017, 2020), ACL(2020,2021,2022), AACL-IJCNLP(2020,2022), ACL-IJCNLP(2021), EMNLP(2015, 2016, 2017, 2019, 2020, 2021, 2022), NAACL-HLT(2018, 2021), EACL (2021), et al.
 
Courses
· Natural Language Processing & Natural Language Understanding, 2022 Fall, Major: Computer Science (CS2020), 2022 Spring, Major: Artificial Intelligence (AI2019), 2021 Fall, Major: Computer Science (CS2019).
· Mathematics Modeling,2021 Spring, Major: Computer Science (CS2019).
· Python, 2020 Spring, Major: Optical Information Science and Technology (2019). 2020 Fall, Major: National Scientific Base for Psychology (2019).