Hi, I am Tingsong Xiao (肖廷松 in Chinese). I am currently a Ph.D. student in Computer Science at the University of Florida, under the supervision of Dr. Zhe Jiang. My research interests include deep learning (especially Graph Neural Networks), explainable/interpretable AI, and event prediction. Check my CV for more details.
Previously, I got my bachelor’s degree in Data Science and Big Data Technology at the University of Electronic Science and Technology of China (UESTC) in 2021. During my undergraduate, I studied recommendation algorithms with Dr. Jie Shao. Later, I was admitted to UESTC for Master’s degree without an entrance examination due to excellence. I worked on Graph Neural Networks and Interpretable AI under the supervision of Dr. Xiaofeng Zhu and Dr. Xiaoshuang Shi.
I won the MICCAI 2022 Student Travel Award (Top 2%) in 2022 and the China National Scholarship (Top 1%) in 2020.
If you are interested, feel free to email me at xtstars1998 AT gmail DOT com.
Publications (In Press)
A Hierarchical Spatial Transformer for Large Numbers of Point Samples in Continuous Space
Wenchong He, Zhe Jiang, Tingsong Xiao.
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
- This paper introduces a transformer architecture for spatial modeling problems with irregularly spaced sample points.
- We use a quadtree structure to reduce the computational requirements of the transformer and introduce a decoder mechanism to quantify uncertainty.
Spatial Knowledge-Infused Hierarchical Learning: An Application in Flood Mapping on Earth Imagery
Zelin Xu, Tingsong Xiao, Wenchong He, Yu Wang, and Zhe Jiang.
ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2023)
- Our paper introduces a novel approach called Spatial Knowledge-Infused Hierarchical Learning for improved flood mapping using Earth imagery.
- The methodology uniquely integrates spatial knowledge and hierarchical learning to tackle issues of feature importance, accuracy, and data complexity.
M-GCN: Multi-scale Graph Convolutional Network for 3D Point Cloud Classification PDF Link
Jing Hu, Xincheng Wang, Ziheng Liao, Tingsong Xiao* (* corresponding author).
IEEE International Conference on Multimedia and Expo (ICME 2023)
- The paper introduces a novel multi-scale graph convolutional network (M-GCN) to efficiently process and summarize 3D point clouds by extracting local geometric features across multiple scales.
Dual-Graph Learning Convolutional Networks for Interpretable Alzheimer’s Disease Diagnosis PDF Link
Tingsong Xiao, Lu Zeng, Xiaoshuang Shi, Xiaofeng Zhu, Guorong Wu.
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022)
- Our dGLCN is the first work to consider dual-graph learning by comprehensively capturing the correlations among the data to improve the generalizability and interpretability.
- Early Accepted; Oral Paper; MICCAI 2022 Student Travel Award.
Graph Convolutional Network with Sample and Feature Weights for Alzheimer’s Disease Diagnosis PDF Link
Lu Zeng, Hengxin Li, Tingsong Xiao, Fumin Shen, Zhi Zhong.
Information Processing & Management (IP&M 2022)
- The proposed method considers the feature importance by assigning different weights to the features for solving the Training Set Bias (TSB) issue.
Enhanced Multi-source Review-Based Model for Rating Prediction PDF Link
Xiaochen Wang, Tingsong Xiao, Jie Shao.
International Conference on Knowledge Science, Engineering and Management (KSEM 2021)
MRMRP: Multi-source Review-Based Model for Rating Prediction PDF Link
Xiaochen Wang, Tingsong Xiao, Jie Tan, Deqiang Ouyang, Jie Shao.
International Conference on Database Systems for Advanced Applications (DASFAA 2020)
- 2022.09 - Present: Ph.D. in Computer Science, GPA: 3.89/4.0, University of Florida, USA.
- 2017.09 - 2021.06: Bachelor’s Degree in Computer Science, GPA: 3.92/4.0, University of Electronic Science and Technology of China (UESTC), Chengdu, China.
- 2014.09 - 2017.06: Anyang No. 1 Senior High School, Henan Province, China.
Honors and Awards
Gartner Group Graduate Fellowship, Apr. 2023
Awarded to excellent graduate students at the University of Florida.
MICCAI 2022 Student Travel Award, Mar. 2022
Awarded to the first-author students of the highest-quality MICCAI papers.
China National Scholarship, Oct. 2020
Recognition for being among the best students, awarded by the Ministry of Education of China.
Honorable Mention in Mathematical Contest in Modeling, Feb. 2020
Ranked in the top 21% in the contest administered by COMAP and sponsored by SIAM and INFORMS.
First-Class Scholarship at UESTC, Sep. 2020
Awarded to top students based on excellent overall performance ranking at UESTC.
Outstanding Graduate at UESTC, May 2021
Awarded for having the best overall performance upon graduating from UESTC.
Excellent Postgraduate Recommendation, June 2021
Granted admission to UESTC for a master’s degree without an entrance examination due to academic excellence.
Journal and Conference Reviewers
- IEEE Transactions on Image Processing (TIP)
- Information Processing & Management (IP&M)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)