BIMSA > Hai Hua Xie
Assistant Professor Hai Hua Xie

Group: Artificial Intelligence and Machine Learning

Office: A3-1-306

Email: haihua.xie@bimsa.cn

Research Field: Machine Learning, Natural Language Processing

Webpage: https://bimsa.net/people/haihuaxie/

CV

Biography

Dr. Haihua Xie receives a Ph.D. in Computer Science at Iowa State University in 2015. Before joining BIMSA in Oct. 2021, Dr. Xie worked in the State Key Lab of Digital Publishing Technology, Peking University from 2015-2021. His research interests include Natural Language Processing and Knowledge Service. He published more than 20 papers and obtained 7 invention patents. In 2018, Dr. Xie was selected in the 13th batch of overseas high-level talents in Beijing and was hornored as a "Beijing Distinguished Expert".

Research Interest

  • Professional Knowledge Processing, Knowledge Mining and Knowledge Services
  • Knowledge Graph and Knowledge Base Construction, Knowledge Base Data Verification
  • Text Big Data Analytics
  • User Behavior Data Analysis, User Intent Speculation and User New Requirements Mining

Education Experience

  • 2009 - 2015      Iowa State University      Computer Science      Doctor
  • 2006 - 2009      Tsinghua University      Software Engineering      Master
  • 2002 - 2006      Nanjing University of Posts and Telecommunications      Electronical Information Science and Technology      Bachelor

Work Experience

  • 2021 -      BIMSA      Assistant Professor
  • 2017 - 2021      State Key Laboratory of Digital Publishing Technology of Founder Group      Senior Algorithm Researcher, Person in charge of knowledge service direction, Postdoctoral Supervisor
  • 2015 - 2017      Peking University      Postdoc
  • 2015 - 2017      Founder Group      Algorithm Researcher

Honors and Awards

  • 2019      Zhongguancun High-end leading talents
  • 2019      Outstanding postdoctoral fellows (20 in total), 20th Anniversary of Postdoctoral Workstation in Zhongguancun Science and Technology Park
  • 2018      The 13th Batch of Overseas High-level Talents and Specially Appointed Experts of Beijing

Publication

  • [1] Huzhi Xue, Butian Zhao, Haihua Xie, Zeyu Sun, RankLLM:A multi-criteria decision-making method for LLM performance evaluation in sentiment analysis (2025)
  • [2] Haihua XIE, Yinzhu CHENG, Yaqing WANG, Miao HE, Mingming SUN, RD-MCSA: A Multi-Class Sentiment Analysis Approach Integrating In-Context Classification Rationales and Demonstration (2025)
  • [3] Huzhi Xue, Butian Zhao, Haihua Xie, Jun Wang, An integrated multi-criteria decision-making approach with unknown weight information under probabilistic dual-hesitant Pythagorean fuzzy environment and its application to supplier selection (2024)
  • [4] 张涛, 汤珂, 谢海华, 基于文本分析的首席经济学家信心指数的构建与宏观预测, accepted by 管理科学学报 (2024)
  • [5] Haihua Xie, Miao He, Xiaoming Zhang, Lin Liu, and Philip S. Yu, OpenNOD: Opinion Dynamics Modelling in Open Network Environments, submitted to IEEE Transactions on Knowledge and Data Engineering (2024)
  • [6] Huzhi Xue, Haihua Xie, and Carl K. Chang, Assessing AI adoption for enhancing healthcare supply chain resilience: A novel hybrid interval-valued q-rung orthopair fuzzy MCDM, , 50-57 (2024)
  • [7] Haihua XIE, Xuefei CHEN, Xiaoqing LYU, and Lin LIU, A Generalized Strategy of Chinese Grammatical Error Diagnosis Based on Task Decomposition and Transformation, , 135-147 (2023)
  • [8] Lin Liu, Haihua Xie, Jingwei Yang, and Yanni Li, Building Smart Systems to Satisfice User Intention in Situ: A Look Back to the Future, , 262-271 (2023)
  • [9] Haihua Xie, Xiaoqing Lyu, and Xuefei Chen, String editing based Chinese grammatical error diagnosis, , 5335-5344 (2022)
  • [10] 张涛,汤珂,谢海华, 基于自然语言处理的高频经济学家信心指数构建和宏观预测, 第三届中国宏观经济学者论坛(2022)
  • [11] XIE Haihua, CHEN Xuefei, DU Yimin, Lyu Xiaoqing, TANG Zhi, A Semi-supervised Method for Chinese Key Phrase Extraction Based on Statistical Features and Graph Model, Chinese Journal of information, 36(4), 57-65 (2022)
  • [12] XIE Haihua, CHEN Zhiyou, CHENG Jing, Lyu Xiaoqing, TANG Zhi. Chinese Grammar Error Detection based on Data Enhancement and Multi-task Feature Learning. Chinese Journal of information, 2022, 36(12): 16-23.
  • [13] XIE Haihua, CHEN Zhiyou, CHENG Jing, Lyu Xiaoqing, TANG Zhi, Chinese Grammar Error Detection based on Data Enhancement and Multi-task Feature Learning, Proceedings of The Nineteenth China National Conference on Computational Linguistics (CCL 2020), 36(12), 16-23 (2020)
  • [14] Nuo Xu, Haihua Xie, Dongyan Zhao, A novel joint framework for multiple Chinese events extraction, China National Conference on Chinese Computational Linguistics, CNCL, 174-183 (2020)
  • [15] Jianwei Li, Yongtao Wang, Haihua Xie, and Kai-Kuang Ma, Learning a single model with a wide range of quality factors for JPEG image artifacts removal, IEEE Transactions on Image Processing, 29, 8842-8854 (2020)
  • [16] Haihua Xie, Zhiyou Chen, Yabo Li, Shaoling Jing, Xiaoqing Lyu, Zhi Tang, Sembrs: a semantic analysis based book retrieval approach, 2020 IEEE conference on multimedia information processing and retrieval (MIPR), 101-104 (2020)
  • [17] Shaoling Jing, Shibo Hong, Dongyan Zhao, Haihua Xie, Zhi Tang, Combining Impression Feature Representation for Multi-turn Conversational Question Answering, Chinese Computational Linguistics: 19th China National Conference, CCL 2020, Hainan, China, October 30–November 1, 2020, Proceedings 19, 57-69 (2020)
  • [18] Haihua XIE, Aolin LI, Yabo LI, Zhiyou CHEN, Jing CHENG, Xiaoqing LYU, Zhi TANG, CPLM-CSC: Character-based Pre-trained Language Model for Chinese Spelling Checking and Correction, Proceedings of The Eighteenth China National Conference on Computational Linguistics (CCL 2019). (2019)
  • [19] Haihua XIE, Aolin LI, Yabo LI, Jing CHENG, Zhiyou CHEN, Xiaoqing LYU, Zhi TANG, Automatic Chinese Spelling Correction based on Character-based Pre-trained Contextual Representations, Proceedings of The 8th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC 2019). (2019)
  • [20] Haihua Xie, Xiaoqing Lyu, Xuefei Chen, Jinle Tong, Zhi Tang, ES-ESens: Detection of Event Sentences Based on Evaluation of the Explicitness and Significance of Information, 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 32-35 (2019)
  • [21] Yitao Liu, Xiaoqing Lyu, Haihua Xie, Xiaotong Yan, Bei Wang, Zhi Tang, A method for improving the reliability of causal inference from large-scale data in biomedicine, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 693-696 (2018)
  • [22] Haihua XIE, Xiaoqing LYU, Zhi TANG, Clustering Analysis-Based Approach to Detecting Entity Mixture in Knowledge Bases, Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries, 395-396 (2018)
  • [23] Haihua XIE, Jingwei YANG, Carl K. CHANG, Lin LIU, A statistical analysis approach to predict user's changing requirements for software service evolution, Journal of Systems and Software, 132, 147-164 (2017)
  • [24] Haihua XIE, Xiaoqing LYU, Zhi TANG, Mao YE, A methodology to evaluate triple confidence and detect incorrect triples in knowledge bases, Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries, 16th, 251-252 (2016)
  • [25] Haihua XIE, Xiaoqing LYU, Zhi TANG, Xiaojun HUANG, Detection of Entity Mixture in Knowledge Bases Using Hierarchical Clustering, Natural Language Understanding and Intelligent Applications: 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, Proceedings 24, 288-299 (2016)
  • [26] Haihua XIE, Carl K. CHANG, Detection of new intentions from users using the CRF method for software service evolution in context-aware environments, 2015 IEEE 39Th annual computer software and applications conference, 2, 71-76 (2015)
  • [27] Haihua XIE, Carl K. CHANG, Hua MING, Kai-Shin LU, The Concepts and Ontology of SiSL: A Situation-Centric Specification Language, , 385-391 (2012)
  • [28] Haihua XIE, Observable context-based user intention specification in context-aware environments, 2011 IEEE 35th Annual Computer Software and Applications Conference, 712-715 (2011)
  • [29] Haihua XIE, Lin LIU, Jingwei YANG, *-prefer: optimizing requirements elicitation process based on actor preferences, Proceedings of the 2009 ACM symposium on Applied Computing, 347-354 (2009)
  • [30] X Haihua, C Zhiyou, C Jing, L Xiaoqing, T Qi, Chinese grammar error detection method based on data augmentation and multi task feature learning [J], Chinese Journal of Information Science, 36(12), 36-43 (2022)
  • [31] J Li, Y Wang, H Xie, KK Ma, Learning local and global priors for JPEG image artifacts removal, IEEE Signal Processing Letters, 27, 2134-2138 (2020)
  • [32] N Xu¹, H Xie, Check for updates A Novel Joint Framework for Multiple, Chinese Computational Linguistics (2020)
  • [33] H Xie, Z Chen, J Cheng, X Lyu, Z Tang, 基于数据增强和多任务特征学习的中文语法错误检测方法 (Chinese Grammar Error Detection based on Data Enhancement and Multi-task Feature Learning), Chinese National Conference on Computational (2020)
  • [34] H Xie, A Li, Y Li, J Cheng, Z Chen, X Lyu, Z Tang, Automatic chinese spelling checking and correction based on character-based pre-trained contextual representations, Natural Language Processing and Chinese Computing: 8th CCF International … (2019)
  • [35] H Xie, J Yang, CK Chang, Using Conditional Random Fields in Detection of New Intentions for Software Service Evolution, Journal of Systems and Software, 132, 147-164 (2017)
  • [36] H Xie, X Lu, Z Tang, X Huang, Detect Incorrect Triples in Knowledge Base Based on Triple Confidence Evaluation, International Conference on Industrial and Business (2017)
  • [37] H Xie, Detection of new intentions from users for software service evolution in human-centric context-aware environments using Conditional Random Fields, Iowa State University (2015)
  • [38] X Bai, F Belli, E Bertino, CK Chang, A Elçi, C Seceleanu, H Xie et al., COMPSAC 2012 Trustworthy Software Systems for the Digital Society (2012)
  • [39] T Li, T Li, H Xie, L Liu, I*-Prefer: A Tool for Preference Model-Driven Decision Making., iStar, 15, 151-153 (2011)
  • [40] W Ma, L Liu, H Xie, H Zhang, J Yin, Preference Model Driven Services Selection. In van Eck, Pascal; Gordijn, Jaap, and Wieringa, Roel, editors, Advanced Information Systems Engineering, volume 5565 of Lecture …, Springer (2009)
  • [41] B Wen, H Xie, P Hu, J Ma, Y Chen, K Yu, B Dang, C Leung, G Dimauro et al., ICDH 2024 Workshop on Innovations in Digital Health
  • [42] H Xue, H Xie, B Zhao, J Wang, An Integrated Multi-Criteria Decision-Making Approach with Unknown Weight Information Under Probabilistic Dual-Hesitant Pythagorean Fuzzy Environment and its Application to …

 

Update Time: 2025-06-30 16:05:28