Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions. - Song Ju; Shitian Shen; Hamoon Azizsoltani; Tiffany Barnes; Min Chi (EDM (Workshops), 2019)

Identifying Critical Pedagogical Decisions through Adversarial Deep Reinforcement Learning. - Song Ju; Guojing Zhou; Hamoon Azizsoltani; Tiffany Barnes; Min Chi (EDM, 2019)

Pick the Moment: Identifying Critical Pedagogical Decisions Using Long-Short Term Rewards. - Song Ju; Min Chi; Guojing Zhou (EDM, 2020)

Evaluating Critical Reinforcement Learning Framework in the Field. - Song Ju; Guojing Zhou; Mark Abdelshiheed; Tiffany Barnes; Min Chi (AIED (1), 2021)

InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem. - Markel Sanz Ausin; Hamoon Azizsoltani; Song Ju; Yeo-Jin Kim; Min Chi (IEEE BigData, 2021)

To Reduce Healthcare Workload: Identify Critical Sepsis Progression Moments through Deep Reinforcement Learning. - Song Ju; Yeo Jin Kim; Markel Sanz Ausin; Maria E. Mayorga; Min Chi (IEEE BigData, 2021)

Preparing Unprepared Students For Future Learning. - Mark Abdelshiheed; Mehak Maniktala; Song Ju; Ayush Jain; Tiffany Barnes; Min Chi (CogSci, 2021)

Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning. - Song Ju; Xi Yang 019; Tiffany Barnes; Min Chi (AIED (1), 2022)

HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare. - Ge Gao; Song Ju; Markel Sanz Ausin; Min Chi (AAMAS, 2023)

On Trajectory Augmentations for Off-Policy Evaluation. - Ge Gao; Qitong Gao; Xi Yang 019; Song Ju; Miroslav Pajic; Min Chi (ICLR, 2024)

Off-Policy Selection for Initiating Human-Centric Experimental Design. - Ge Gao; Xi Yang 019; Qitong Gao; Song Ju; Miroslav Pajic; Min Chi (NeurIPS, 2024)