Applied Causal Inference for Data Science · Columbia University
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This is an introductory and applied course in Casual Inference .
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This is an introductory and applied course in Casual Inference .
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Introduction to reinforcement learning course series by MIT Online.
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Advanced seminar exploring supervised learning, unsupervised learning, learning theory, reinforcement learning.
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An applied course on reinforcement learning for large language models, covering the full workflow from autoregressive sampling and policy-gradient foundations to hardware-aware rollout systems and modern group-based policy optimization methods.
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Published in Proceedings of the Annual Meeting of the Cognitive Science Society, 2025
Recommended citation: Xu, G., & Corter, J. E. (2025). Extracting Latent Dimensions from Multidimensional Response Timing Data. Proceedings of the Annual Meeting of the Cognitive Science Society. https://escholarship.org/uc/item/7wm1k7cv
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Published in Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026
Recommended citation: Xu, G., & Corter, J. E. (2026). Graph RAG for Automated Short Answer Grading with Feedback: Bridging Pedagogical Needs and Technical Capabilities. Proceedings of the AAAI Conference on Artificial Intelligence, 40(48), 40916-40924. https://doi.org/10.1609/aaai.v40i48.42125
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arXiv preprint, 2026
Accepted to The 40th Annual Conference on Neural Information Processing Systems, 2026
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HUDM 6055: Latent Structure Analysis, Teachers College, Columbia University, 2022
HUDM 5123: Linear Models Experimentl Dsgn, Teachers College, Columbia University, 2024
HUDM 4120: Introduction to Statistics, Teachers College, Columbia University, 2024
HUDM 5059: Psychological measurement, Teachers College, Columbia University, 2025