Publications

Conference

  1. G. Gao, Q. Gao, X. Yang, S. Ju, M. Pajic, M. Chi. “On Trajectory Augmentations for Off-Policy Evaluation.” 12th International Conference on Learning Representations (ICLR). 2024. (31% acceptance rate; 2251/7262 full papers)
  2. G. Gao, X. Yang, M. Chi. “Get A Head Start: On-demand Pedagogical Policy Selection in Intelligent Tutoring.” 38th AAAI Conference on Artificial Intelligence (AAAI). 2024. (23.7% acceptance rate; 2342/9862 full papers)
  3. Q. Gao, G. Gao, J. Dong, V. Tarokh, M. Chi, M. Pajic. “Off-Policy Evaluation for Human Feedback.” 37th Conference on Neural Information Processing Systems (NeurIPS). 2023. (26.1% acceptance rate; 3221/12343 full papers) [PDF]
  4. X. Yang, G. Gao, M. Chi. “Hierarchical Apprenticeship Learning for Disease Progression Modeling.” 32nd International Joint Conference on Artificial Intelligence (IJCAI). 2023. (15% acceptance rate; 685/4566 full papers) [Paper | PDF]
  5. Q. Gao, G. Gao, M. Pajic, M. Chi. “Variational Latent Branching Model for Off-Policy Evaluation.” In International Conference on Learning Representations (ICLR). 2023. (31.8% acceptance rate; 1584/4955 full papers) [Paper | PDF | Code]
  6. G. Gao, S. Ju, MS. Ausin, M. Chi. “HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare.” 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2023. (23.3% acceptance rate; 237/1015 full papers) [Paper | PDF]
  7. G. Gao, Q. Gao, X. Yang, M. Pajic, M. Chi. “A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification.” 31st International Joint Conference on Artificial Intelligence (IJCAI). 2022. (14.9% acceptance rate; 679/4535 full papers) [Paper | PDF | Code]
  8. G. Gao, F. Khoshnevisan, M. Chi. “Reconstructing Missing EHRs Using Time-Aware Within- and Cross-Visit Information for Septic Shock Early Prediction” 10th IEEE International Conference on Healthcare Informatics (ICHI). 2022. (14.9% acceptance rate; 10/67 full papers-Analytics track) [Paper | PDF | Code]
  9. G. Gao, S. Marwan, and T.W. Price. “Early Performance Prediction using Interpretable Patterns in Programming Process Data.” 52nd ACM Technical Symposium on Computer Science Education (SIGCSE). 2021. (30.7% acceptance rate; 170/554 full papers) [Paper | PDF | Slides | Cliffnotes]
  10. S. Marwan, G. Gao, S. Fisk, T.W. Price, and T. Barnes. “Adaptive Immediate Feedback Can Improve Novice Programming Engagement and Intention to Persist in Computer Science.” 16th annual ACM International Computing Education Research (ICER), 2020. (22.7% acceptance rate; 27/119 full papers)[Paper | PDF]
  11. T.W. Price, D. Hovemeyer, K. Rivers, G. Gao, A.C. Bart, A.M. Kazerouni, B. Becker, A. Petersen, L. Gusukuma, S.H. Edwards and D. Babcock. “ProgSnap2: A Flexible Format for Programming Process Data.” 25th Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE). 2020. (27.6% acceptance rate; 72/261 full papers) [Paper | PDF]
  12. W. Wang, Y. Rao, R. Zhi, S. Marwan, G. Gao and T.W. Price. “The Step Tutor: Supporting Students through Step-by-Step Example-Based Feedback.” 25th Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE). 2020. (27.6% acceptance rate; 72/261 full papers)
  13. G. Gao, Y. Chen, H. Tang. “How Users Distinguish Trees Within a Virtual Environment.” International Conference on Human-Computer Interaction. 2018. [Paper]

Workshop

  1. T.W. Price, G. Gao. “Lightning Talk: Curating Analyses for Programming Log Data.” SPLICE 2019 workshop Computing Science Education Infrastructure: From Tools to Data at 15th ACM International Computing Education Research Conference. 2019. [PDF]

Posters, Extended Abstracts, and Discussions in Conference Proceedings

  1. G. Gao, M. Chi. “Trace Augmentation with Missing EHRs for Sepsis Treatments.” Poster. IEEE 11th International Conference on Healthcare Informatics (ICHI). 2023.