Ma Jianbing. Doctor of Engineering, Professor; Email: mjb@cuit.edu.cn
Research and postgraduate enrollment direction:
1. Text information processing
2. Artificial Intelligence and Knowledge Representation
3. Smart weather
Profile:
Changjiang Scholar, Sichuan Distinguished Expert, and winner of Sichuan Emei Plan. The main research directions are: artificial intelligence knowledge representation, text information processing, intelligent weather.
In 2009, Dr. Ma Jianbing obtained a doctor's degree in artificial intelligence from Queen's University of England. From 2010 to 2012, he was engaged in intelligent monitoring research in the School of Computer Science of Queen's University of England. From 2013 to 2015, he served as a lecturer and associate researcher in the University of Coventry of England. From 2018 to 2019, he served as an expert in medical knowledge operation in Shanghai Senyi Medical Technology Co., Ltd. Dr. Ma Jianbing graduated from Tsinghua University with a master's degree and a bachelor's degree in 2007 and 2003.
Dr. Ma Jianbing has undertaken and participated in many projects, including the European Union Mary Curie Project, the British Fusion Fund Project, and the Sichuan Provincial Science and Technology Department Project. He has accumulated more than 2 million yuan in research funding, published more than 40 academic papers, including more than 10 SCI searches.
Currently undertaking scientific research projects:
1. Project of Science and Technology Department of Sichuan Province, "Research on Global Discovery of Key Technologies by Frontier Science and Technology", (2021YFG0345).
Current teaching:
"Introduction to Artificial Intelligence", undergraduate/postgraduate
"Data mining", postgraduate
"Professional frontier", undergraduate
Papers published in recent 5 years (* is the corresponding author):
Yanfei Xiang, Jianbing Ma*, Xi Wu. A Precipitation Nowcasting Mechanism for Real-World Data Based on Machine Learning, Mathematical Problems in Engineering, vol:2020, 1-11, 2020. IF: 1.009
Jianbing Ma. A Correspondence between Belief Function Combination and Knowledge Base Merging. International Journal of Approximate Reasoning,2019, 104:1-8. IF: 2.845
Ma, WJ, Liu, WR, Luo, XD, McAreavey, K, Jiang, YC, Ma, JB. A Dempster-Shafer theory and uninorm-based framework of reasoning and multiattribute decision-making for surveillance system, INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, volume:34, pages: 3077-3104. Nov. 2019. IF: 2.929
Dubois, D., Liu, W.,Ma, J.and Prade, H. The basic principles of uncertain information fusion. An organised review of merging rules in different representation frameworks. Information Fusion, Volume 32, Part A, November 2017, Pages 12–39. (IF: 13.669)
Pozos-Parra, P., Chavez-Bosquez, O., and Ma, J.Implementing ∆ps (PS-Merge) Belief Merging Operator for Belief Revision, Computation y Sistemas, 2017, 21(3):419-434. (IF: 0.52)
Ma, J., Liu, W. Miller, P. and Zhou, H. (2016) An Evidential Fusion Approach for Gender Profiling. Information Sciences, 333:10-20. (IF: 5.910)
M. Naiseh, N. Jiang, J. Ma and R. Ali., Explainable Recommendations in Intelligent Systems: Delivery Methods, Modalities and Risks. RCIS2020 - IEEE 14th International Conference on Research Challenges in Information Science, 2020.
M. Naiseh, N. Jiang, J. Ma and R. Ali. Personalising Explainable Recommendations: Literature and Conceptualisation, WorldCist'20 - 8th World Conference on Information Systems and Technologies, 2020.
B. Fan, N. Jiang, H. Dogan, R. Ali and J. Ma. An Ontological Approach to Inform HMI Designs for Minimising Driver Distractions with ADAS. BHCI, 2018.
B. Fan, J. Ma, N. Jiang, H. Dogan, and R. Ali. A rule-based Approach to Inform Improved HMI Designs for Minimising Driver Distractions with ADAS. IEEE SMC, 2018.