陈奇
助理教授 人工智能与先进计算学院 Qi.Chen02@xjtlu.edu.cn
人工智能与先进计算学院助理教授
发表文献
    Q. Chen, W. Wang, K. Huang, and F. Coenen, "Zero-shot Text Classification via Knowledge Graph Embedding for Social Media Data." IEEE Internet of Things Journal, 2021.
    Q. Chen, W. Wang, K. Huang, S. De, and F. Coenen, "Multi-modal Generative Adversarial Networks for Traffic Event Detection in Smart Cities." Expert Systems with Applications, 2021.
    Q. Chen, W. Wang, X. Huang, and H. Liang, "Attention-based Recurrent Neural Network for Traffic Flow Prediction." Journal of Internet Technology, 21(3), 831-839, 2020.
    Q. Chen, W. Wang, F. Wu, S. De, R. Wang, B. Zhang, and X. Huang, "A survey on an emerging area: Deep learning for smart city data." IEEE Transactions on Emerging Topics in Computational Intelligence, 3(5), 392-410, 2019.
    会议论文： Q. Chen, W. Wang, K. Huang, S. De, and F. Coenen, "Adversarial Domain Adaptation for Crisis Data Classification on Social Media." 2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), pp. 282-287, 2020.
    Q. Chen, W. Wang, K. Huang, S. De, and F. Coenen, "Multi-modal Adversarial Training for Crisis-related Data Classification on Social Media." IEEE International Conference on Smart Computing (SMARTCOMP), pp. 232-237, 2020.
查看全部
研究领域
自然语言处理：基于深度学习的文本分类问题，社交媒体数据分析，外部知识图谱的融合等
智慧城市应用：城市传感器数据挖掘，社交媒体数据融合，智能交通，自然灾害分析等应用
应用场景
对企业里获取的大量传感器数据或文本数据进行数据挖掘和知识发现
工作经历
2022年至今 - 助理教授，西交利物浦大学
教育背景
博士，计算机科学，利物浦大学， 2021
硕士，计算机科学，斯蒂文斯理工学院，2017
本科，信息与计算科学，西交利物浦大学，2015
科研项目
1.Low-carbon natural wind distributed intelligent control system for the indoor environment of large buildings
2.Suzhou Multimodal Big Data Innovation Application Lab
3.Intelligent Multimodal Data Analysis for Digital Twin Cities
4.Knowledge-Enriched Transfer Learning in Natural Language Processing
5.Learning from natural language with knowledge base integration
产学研合作
to be updated
专利项目
基于时空特征融合预测的视频异常检测方案 CN119380237B

更多文章请点击链接Google Scholar