Xiaoshi Zhong

Name: Zhong Xiaoshi
Discipline: Computer Science and Technology
Title: Assistant Professor
Contact number:
E-mail: xszhong@bit.edu.cn
Address: Building Center, No.5 Zhongguancun South Street, Haidian District, Beijing Personal Information
Zhong Xiaoshi, Ph.D., pre-appointed Assistant Professor, Special Associate Researcher, Master supervisor, School of Computer Science, Beijing Institute of Technology, selected as the national Overseas Talent Introduction Program youth project. He graduated from Beijing University of Aeronautics and Astronautics, majoring in computer science and technology. He received his Ph.D. in computational Linguistics and Bioinformatics from Nanyang Technological University, Singapore, under the tutelage of Erik Cambria (IEEE Fellow) and Jagath Rajapakse (IEEE Fellow). Before studying for the doctoral degree, I received more than two years of academic training from Jeff Hong (Chair Professor), a top scholar in the field of operations research and simulation optimization, in Hong Kong University of Science and Technology and City University of Hong Kong. Professor Hong greatly influenced my academic thinking and research taste. His current research interests include data analysis, complex systems and computational linguistics. He has published many papers in the top computer conferences ACL and WWW and some important journals, and published a monograph in English.
Enrollment plan: Recruit 2 ~ 4 postgraduate students every year, and welcome senior outstanding undergraduates to join the research group.

Research Direction
Data Analysis, Complex Systems, Computational Linguistics

Personal Information
Zhong Xiaoshi, Ph.D., pre-appointed Assistant Professor, Special Associate Researcher, Master supervisor, School of Computer Science, Beijing Institute of Technology, selected as the national Overseas Talent Introduction Program youth project. He graduated from Beijing University of Aeronautics and Astronautics, majoring in computer science and technology. He received his Ph.D. in computational Linguistics and Bioinformatics from Nanyang Technological University, Singapore, under the tutelage of Erik Cambria (IEEE Fellow) and Jagath Rajapakse (IEEE Fellow). Before studying for the doctoral degree, I received more than two years of academic training from Jeff Hong (Chair Professor), a top scholar in the field of operations research and simulation optimization, in Hong Kong University of Science and Technology and City University of Hong Kong. Professor Hong greatly influenced my academic thinking and research taste. His current research interests include data analysis, complex systems and computational linguistics. He has published many papers in the top computer conferences ACL and WWW and some important journals, and published a monograph in English.
Enrollment plan: Recruit 2 ~ 4 postgraduate students every year, and welcome senior outstanding undergraduates to join the research group.

Personal Information
Zhong Xiaoshi, Ph.D., pre-appointed Assistant Professor, Special Associate Researcher, Master supervisor, School of Computer Science, Beijing Institute of Technology, selected as the national Overseas Talent Introduction Program youth project. He graduated from Beijing University of Aeronautics and Astronautics, majoring in computer science and technology. He received his Ph.D. in computational Linguistics and Bioinformatics from Nanyang Technological University, Singapore, under the tutelage of Erik Cambria (IEEE Fellow) and Jagath Rajapakse (IEEE Fellow). Before studying for the doctoral degree, I received more than two years of academic training from Jeff Hong (Chair Professor), a top scholar in the field of operations research and simulation optimization, in Hong Kong University of Science and Technology and City University of Hong Kong. Professor Hong greatly influenced my academic thinking and research taste. His current research interests include data analysis, complex systems and computational linguistics. He has published many papers in the top computer conferences ACL and WWW and some important journals, and published a monograph in English.
Enrollment plan: Recruit 2 ~ 4 postgraduate students every year, and welcome senior outstanding undergraduates to join the research group.

代表性学术成果
[1] Xiaoshi Zhong, Muyin Wang, and Hongkun Zhang. Is Least-Squares Inaccurate in Fitting Power-Law Distributions? The Criticism is Complete Nonsense. In Proceedings of the ACM Web Conference 2022 (WWW), pages 2748-2758, Virtual Event, Lyon, France, 2022. Research-track paper with oral presentation, acceptance rate: 17.7% (323/1822).
[2] Xiaoshi Zhong, Erik Cambria, and Amir Hussain. Does Semantics Aid Syntax? An Empirical Study on Named Entity Recognition and Classification. In Neural Computing and Applications, 34(11): 8373-8374, 2022. (SCI, IF: 5.606)
[3] Xiaoshi Zhong and Erik Cambria. Time Expression and Named Entity Recognition. In Book Series Socio-Affective Computing, Volume: 10, Springer Nature, 2021. ISBN: 978-3-030-78961-9.
[4] Xiaoshi Zhong and Jagath C. Rajapakse. Graph Embeddings on Gene Ontology Annotations for Protein-Protein Interaction Prediction. In BMC Bioinformatics, 21(16): 1-17, 2020. (SCI, IF: 3.242)
[5] Xiaoshi Zhong, Erik Cambria, and Amir Hussain. Extracting Time Expressions and Named Entities with Constituent-based Tagging Schemes. In Cognitive Computation, 12(4): 844-862, 2020. (SCI, IF: 5.418)
[6] Xiaoshi Zhong, Rama Kaalia, and Jagath C. Rajapakse. GO2Vec: Transforming GO Terms and Proteins to Vector Representations via Graph Embeddings. In BMC Genomics, 20(9): 1-10, 2019. (SCI, IF: 3.730)
[7] Xiaoshi Zhong and Erik Cambria. Time Expression Recognition Using a Constituent-based Tagging Scheme. In Proceedings of the 2018 World Wide Web Conference (WWW), pages 983-992, Lyon, France, 2018. Research-track paper with oral presentation, acceptance rate: 14.7% (170/1155).
[8] Xiaoshi Zhong, A.Sun, and Erik Cambria. Time Expression Analysis and Recognition Using Syntactic Token Types and General Heuristic Rules. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL), pages 420-429, Vancouver, Canada, 2017. Full paper with oral presentation, full oral rate: 15.6% (117/751).
所获奖励