CV
Education
- B.S. in Computer Science, Shandong University, China (2010 - 2014)
- M.S. in Computer Science (GPA: 3.97, Distinguished Academic Achievement), George Mason University (2015 - 2018)
- Ph.D. in Computer Science, Emory University (2018 - 2022)
Work Experience
Teaching Experience
- Graduate Teaching Assistant @ George Mason University
- IT 664 Information: Representation, Processing and Visualization (2019 Fall - 2020 Spring)
- IT 664, IT 724, and IT 734 (2019 Spring)
- IT 664 Information: Representation, Processing and Visualization (2018 Fall)
- IT 314 Database Management (2018 Spring)
- IT 214 Database Fundamentals (2017 Fall)
- CS450 and CS550 Database concepts (2015 Fall - 2017 Spring)
Selected Publications
- Conference Papers
- Siyi Gu, Yifei Zhang, Yuyang Gao, Xiaofeng Yang, Liang Zhao. DESSA: Explanation Iterative Supervision via Saliency-guided Data Augmentation. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).
- Tong Sun, Yuyang Gao, Shubham Khaladkar, Sijia Lu, Liang Zhao, Young-Ho Kim, Ray Hong. DeepFuse: Designing Direct Feedback Loops between Humans and Convolutional Neural Networks through Local Explanations. Proceedings of the ACM on Human-Computer Interaction (CSCW 2023).
- Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. Saliency-Augmented Memory Completion for Continual Learning. SIAM International Conference on Data Mining (SDM 2023).
- Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment. Proceedings of the ACM on Human-Computer Interaction (CSCW 2022), to appear. [paper] [code]
- Yuyang Gao, Tong Sun, Guangxi Bai, Siyi Gu, Sungsoo Hong, and Liang Zhao. RES: A Robust Framework for Guiding Visual Explanation. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), to appear. [paper] [code]
- Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. GNES: Learning to Explain Graph Neural Networks. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%). [paper] [code]
- Yuyang Gao, Lingfei Wu, Houman Homayoun, and Liang Zhao. DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, Nov 2019. [paper]
- Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting. Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), (acceptance rate: 16.2%), Hawaii, USA, Feb 2019. [paper] [code]
- Junxiang Wang, Yuyang Gao, Andreas Zufle, Jingyuan Yang, and Liang Zhao. Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features. In Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), regular paper (acceptance rate: 8.9%), Singapore, Nov 2018. [paper] [code]
- Yuyang Gao and Liang Zhao. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), New Orleans, US, Feb 2018. [paper] [code]
- Journal Papers
- Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. 2022. Functional Connectivity Prediction with Deep Learning for Graph Transformation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255). [paper] [code]
- Yuyang Gao, Giorgio Ascoli, Liang Zhao. Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning. Neural Networks, (impact factor: 8.05), 144 (2021) 49–60. [paper] [code]
- Yuyang Gao, Tanmoy Chowdhury (co-first author), Lingfei Wu, Liang Zhao. Modeling Health Stage Development of Patients with Dynamic Attributed Graphs in Online Health Communities. IEEE Transactions on Knowledge and Data Engineerings (TKDE), (impact factor: 4.935), 2021. [paper] [code]
- Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Fanny Ye, Chang-tien Lu, and Naren Ramakrishnan. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), 2021. [paper] [code]
- Yuyang Gao, Giorgio Ascoli, Liang Zhao. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. Frontiers in Neurorobotics, (impact factor: 2.574), 2021. [paper] [code]
- Yuyang Gao, Wei Liang, Yuming Shi and Qiuling Huang. Comparison of directed and weighted co-occurrence networks of six languages. Physica A: Statistical Mechanics and its Applications, (impact factor: 2.243), 393:579–589, 2014. [paper]
Academic Activities & Services
- 2023
- Served as PC Member for KDD 2023 (02/2023)
- 2022
- Technical Paper Presenter at KDD 2022, Washington DC (08/2022)
- Served as Independent Reviewer of Journals TNNLS and TKDD (06/2022)
- Served as PC Member for KDD 2022 (3/2022)
- Served as Independent Reviewer for JMLR (3/2022)
- Served as Independent Reviewer for TKDD (3/2022)
- Served as Independent Reviewer for TOIS (3/2022)
- Served as PC Member for CSCW 2022 (2/2022)
- 2021
- Served as PC Member for DLG and GCLR workshops @ AAAI 2022 (10/2021)
- Served as PC Member for AAAI 2022 (08/2021)
- Served as Independent Reviewer for TOIS (07/2021)
- Served as Independent Reviewer for TNNLS (06/2021)
- Served as PC Member for DLG workshop @ KDD 2021 (06/2021)
- 2020
- Served as PC Member for DLG workshop @ AAAI 2021 (12/2020)
- Served as Independent Reviewer for IJIS (06/2020)
- Invited talk at CN3 seminar talk at Krasnow Institute - George Mason University (06/2020)
- Served as Independent Reviewer of TKDD (06/2020)
- Served as PC Member for DLG workshop @ KDD 2020 (05/2020)
- Served as Independent Reviewer for TKDD (02/2020)
- 2019
- Served as PC Member for DLGMA workshop @ AAAI 2020 (12/2019)
- Presented our paper @ ICDM 2019, Beijing, China (11/2019)
- Served as Publicity Chair for DeepSpatial workshop @ ICDM 2019 (11/2019)
- Presented our paper @ AAAI 2019, Hawaii (02/2019)
- 2018
- Presented our paper @ AAAI 2018, New Orleans (02/2018)
Rewards
