Assistant Professor
Department of Electrical Engineering and Computer Science
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South Dakota State University Daktronics Eng. Hall 123 Brookings, SD 57007 |
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| (605) 688-6304 | |
| Kaiqun.Fu@sdstate.edu | |
| Google Scholar |
Dr. Kaiqun Fu is an Assistant Professor in Department of Electrical Engineering and Computer Science (EECS), South Dakota State University (SDSU), Brookings, SD. He received his Ph.D. degree from the Virginia Tech, in 2021, and the M. S. degree from Virginia Tech in 2016. He worked on research projects involving urban perception with deep learning, traffic impact analysis for smart cities, and emerging technologies prediction. His research and teaching focus on Spatial Data Mining, Machine Learning, Deep Learning, GeoAI, Social Media Analysis, and Urban Computing.
Before that, he holds a Bachelor of Science in Electrical Engineering in the direction of Electronic Communication Engineering.
Education
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Ph.D. in Computer Science, 2021
Virginia Tech -
M.S. in Computer Science, 2016
Virginia Tech
Recent Pulication
- TKDD Citation Forecasting with Multi-Context Attention-Aided Dependency Modeling
Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu
ACM Transactions on Knowledge Discovery from Data (2024).
Paper | Slides - IEEE BigData RoadFormer: Road-Anchored Adversarial Dynamic Graph Transformer for Unlimited-Range Traffic Incident Impact Prediction
Yanshen Sun, Kaiqun Fu, Chang-Tien Lu
Proceedings of the IEEE International Conference on Big Data (2023).
Paper | Slides - IEEE BigData Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices
Shengkun Wang, YangXiao Bai, Taoran Ji, Kaiqun Fu, Linhan Wang, Chang-Tien Lu
Proceedings of the IEEE International Conference on Big Data (2023).
Paper | Slides - ASONAM ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction
Shengkun Wang, YangXiao Bai, Kaiqun Fu, Linhan Wang, Chang-Tien Lu, Taoran Ji
Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (2023).
Paper | Slides - NAPS ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction
Tara Aryal, Pooja Aslami, Niranjan Bhujel, Hossein Moradi Rekabdarkolaee, Kaiqun Fu, Timothy M Hansen
2023 North American Power Symposium (NAPS) (2023).
Paper | Slides - AAAI Exploration on Physics-Informed Neural Networks on Partial Differential Equations
Hoa Ta, ShiWen Wong, Nathan McClanahan, Jung-Han Kimn and Kaiqun Fu
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23) (2023).
Paper | Slides - AAAI PanTop: Pandemic Topic Detection and Monitoring System
Yangxiao Bai and Kaiqun Fu
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23) (2023).
Paper | Slides - SDM Early Forecasting Of The Impact Of Traffic Accidents Using A Single Shot Observation
Guangyu Meng, Qisheng Jiang, Kaiqun Fu, Beiyu Lin, Chang-Tien Lu and Zhqian Chen
Proceedings of the 2022 SIAM International Conference on Data Mining (SDM) (2022).
Paper | Slides - Journal Detecting Anomalous Traffic Behaviors With Seasonal Deep Kalman Filter Graph Convolutional Neural Networks
Yanshen Sun, Yen-Cheng Lu, Kaiqun Fu, Fanglan Chen and Chang-Tien Lu
Journal of King Saud University-Computer and Information Sciences (2022).
Paper | Slides - ICANN Multi-view Cascading Spatial-temporal Graph Neural Network For Traffic Flow Forecasting
Zibo Liu, Kaiqun Fu and Xiaotong Liu
International Conference on Artificial Neural Networks (2022).
Paper | Slides - Book Chapter Metro Transit Disruptions Detection Using Social Media Mining And Graph Convolution
Omer Zulfiqar, Yi-Chun Chang, Po-Han Chen, Kaiqun Fu, Chang-Tien Lu, David Solnick and Yanlin Li
International Conference on Artificial Neural Networks (2022).
Paper | Slides - ITSC Granger Causal Inference for Interpretable Traffic Prediction
Lei Zhang, Kaiqun Fu, Taoran Ji and Chang-Tien Lu
IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (2022).
Paper | Slides
Full List of Papers