| 2026 | AAAI | Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study. | Calvin Isley, Joshua Gilbert, Evangelos Kassos, Michaela Kocher, Allen Nie, Emma Brunskill, Benjamin W. Domingue, Jake Hofman, Joscha Legewie, Teddy Svoronos, Charlotte Tuminelli, Sharad Goel |
| 2026 | CHI | Bloom: Designing for LLM-Augmented Behavior Change Interactions. | Matthew Jrke, Defne Gen, Valentin Teutschbein, Shardul Sapkota, Sarah Chung, Paul Schmiedmayer, Maria Ines Campero, Abby C. King, Emma Brunskill, James A. Landay |
| 2026 | CHI | Can LLM-Simulated Practice and Feedback Upskill Human Counselors? A Randomized Study with 90+ Novice Counselors. | Ryan Louie, Raj Sanjay Shah, Ifdita Hasan Orney, Juan Pablo Pacheco, Emma Brunskill, Diyi Yang |
| 2025 | AAAI | Cost-Aware Near-Optimal Policy Learning. | Joy He-Yueya, Jonathan Lee, Matthew Jrke, Emma Brunskill |
| 2025 | AIED | Human Tutoring Improves the Impact of AI Tutor Use on Learning Outcomes. | Ashish Gurung, Jionghao Lin, Jordan Gutterman, Danielle R. Thomas, Alex Houk, Shivang Gupta, Emma Brunskill, Lee G. Branstetter, Vincent Aleven, Kenneth R. Koedinger |
| 2025 | CHI | GPTCoach: Towards LLM-Based Physical Activity Coaching. | Matthew Jrke, Shardul Sapkota, Lyndsea Warkenthien, Niklas Vainio, Paul Schmiedmayer, Emma Brunskill, James A. Landay |
| 2025 | LAK | Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data. | Ge Gao, Amelia Leon, Andrea Jetten, Jasmine Turner, Husni Almoubayyed, Stephen Fancsali, Emma Brunskill |
| 2025 | LAK | Exploring the Benefit of Customizing Feedback Interventions For Educators and Students With Offline Contextual Multi-Armed Bandits. | Joy Yun, Allen Nie, Emma Brunskill, Dorottya Demszky |
| 2024 | EDM | Evaluating and Optimizing Educational Content with Large Language Model Judgments. | Joy He-Yueya, Noah D. Goodman, Emma Brunskill |
| 2024 | EMNLP | Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles. | Ryan Louie, Ananjan Nandi, William Fang, Cheng Chang, Emma Brunskill, Diyi Yang |
| 2024 | ICLR | Adaptive Instrument Design for Indirect Experiments. | Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill |
| 2024 | LAK | Estimating the Causal Treatment Effect of Unproductive Persistence. | Amelia Leon, Allen Nie, Yash Chandak, Emma Brunskill |
| 2024 | LAK | Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. | Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger |
| 2024 | SIGCSE | Brief, Just-in-Time Teaching Tips to Support Computer Science Tutors. | Alan Y. Cheng, Ellie Tanimura, Joseph Tey, Andrew C. Wu, Emma Brunskill |
| 2024 | SIGCSE | A Fast and Accurate Machine Learning Autograder for the Breakout Assignment. | Evan Zheran Liu, David Yuan, Ahmed Ahmed, Elyse Cornwall, Juliette Woodrow, Kaylee Burns, Allen Nie, Emma Brunskill, Chris Piech, Chelsea Finn |
| 2023 | AAAI | Model-Based Offline Reinforcement Learning with Local Misspecification. | Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill |
| 2023 | AIED | Towards the Future of AI-Augmented Human Tutoring in Math Learning. | Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott A. Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing |
| 2023 | AIED | Understanding the Impact of Reinforcement Learning Personalization on Subgroups of Students in Math Tutoring. | Allen Nie, Ann-Katrin Reuel, Emma Brunskill |
| 2022 | AAAI | Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning. | Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill |
| 2022 | UAI | Offline policy optimization with eligible actions. | Yao Liu, Yannis Flet-Berliac, Emma Brunskill |
| 2021 | AISTATS | Online Model Selection for Reinforcement Learning with Function Approximation. | Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill |
| 2021 | ITS | Automatic Adaptive Sequencing in a Webgame. | Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill |
| 2021 | IUI | EnglishBot: An AI-Powered Conversational System for Second Language Learning. | Sherry Ruan, Liwei Jiang, Qianyao Xu, Zhiyuan Liu, Glenn M. Davis, Emma Brunskill, James A. Landay |
| 2020 | AAAI | Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. | Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill |
| 2020 | AISTATS | Sublinear Optimal Policy Value Estimation in Contextual Bandits. | Weihao Kong, Emma Brunskill, Gregory Valiant |
| 2020 | AISTATS | Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. | Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric |
| 2020 | EDM | Towards Suggesting Actionable Interventions for Wheel Spinning Students. | Tong Mu, Andrea Jetten, Emma Brunskill |
| 2020 | ICML | Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling. | Yao Liu, Pierre-Luc Bacon, Emma Brunskill |
| 2020 | ICML | Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. | Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez |
| 2020 | ICML | Learning Near Optimal Policies with Low Inherent Bellman Error. | Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill |
| 2019 | CHI | QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge. | Sherry Ruan, Liwei Jiang, Justin Xu, Bryce Joe-Kun Tham, Zhengneng Qiu, Yeshuang Zhu, Elizabeth L. Murnane, Emma Brunskill, James A. Landay |
| 2019 | HCOMP | Not Everyone Writes Good Examples but Good Examples Can Come from Anywhere. | Shayan Doroudi, Ece Kamar, Emma Brunskill |
| 2019 | ICLR | Learning Procedural Abstractions and Evaluating Discrete Latent Temporal Structure. | Karan Goel, Emma Brunskill |
| 2019 | ICML | Policy Certificates: Towards Accountable Reinforcement Learning. | Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill |
| 2019 | ICML | Combining parametric and nonparametric models for off-policy evaluation. | Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez |
| 2019 | ICML | Separable value functions across time-scales. | Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill |
| 2019 | ICML | Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds. | Andrea Zanette, Emma Brunskill |
| 2019 | LAK | Fairer but Not Fair Enough On the Equitability of Knowledge Tracing. | Shayan Doroudi, Emma Brunskill |
| 2019 | UAI | Fake It Till You Make It: Learning-Compatible Performance Support. | Jonathan Bragg, Emma Brunskill |
| 2019 | UAI | Off-Policy Policy Gradient with Stationary Distribution Correction. | Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill |
| 2018 | ICML | Decoupling Gradient-Like Learning Rules from Representations. | Philip S. Thomas, Christoph Dann, Emma Brunskill |
| 2018 | ICML | Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs. | Andrea Zanette, Emma Brunskill |
| 2018 | IJCAI | Importance Sampling for Fair Policy Selection. | Shayan Doroudi, Philip S. Thomas, Emma Brunskill |
| 2018 | ITA | Efficient Exploration Through Bayesian Deep Q-Networks. | Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar |
| 2018 | UIST | Shared Autonomy for an Interactive AI System. | Sharon Zhou, Tong Mu, Karan Goel, Michael S. Bernstein, Emma Brunskill |
| 2017 | AAAI | Where to Add Actions in Human-in-the-Loop Reinforcement Learning. | Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic |
| 2017 | AAAI | Importance Sampling with Unequal Support. | Philip S. Thomas, Emma Brunskill |
| 2017 | AAAI | Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing. | Philip S. Thomas, Georgios Theocharous, Mohammad Ghavamzadeh, Ishan Durugkar, Emma Brunskill |
| 2017 | AISTATS | Trading off Rewards and Errors in Multi-Armed Bandits. | Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu |
| 2017 | EDM | The Misidentified Identifiability Problem of Bayesian Knowledge Tracing. | Shayan Doroudi, Emma Brunskill |
| 2017 | IJCAI | Sample Efficient Policy Search for Optimal Stopping Domains. | Karan Goel, Christoph Dann, Emma Brunskill |
| 2017 | UAI | Importance Sampling for Fair Policy Selection. | Shayan Doroudi, Philip S. Thomas, Emma Brunskill |
| 2016 | AAAI | Offline Evaluation of Online Reinforcement Learning Algorithms. | Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic |
| 2016 | AISTATS | A PAC RL Algorithm for Episodic POMDPs. | Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill |
| 2016 | CHI | Toward a Learning Science for Complex Crowdsourcing Tasks. | Shayan Doroudi, Ece Kamar, Emma Brunskill, Eric Horvitz |
| 2016 | CHI | Interface Design Optimization as a Multi-Armed Bandit Problem. | James Derek Lomas, Jodi Forlizzi, Nikhil Poonwala, Nirmal Patel, Sharan Shodhan, Kishan Patel, Kenneth R. Koedinger, Emma Brunskill |
| 2016 | EDM | Sequence Matters, But How Do I Discover How? Towards a Workflow for Evaluating Activity Sequences from Data. | Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill |
| 2016 | EDM | Sequence Matters, But How Exactly? A Method for Evaluating Activity Sequences from Data. | Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill |
| 2016 | ICML | Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning. | Philip S. Thomas, Emma Brunskill |
| 2016 | ICML | Energetic Natural Gradient Descent. | Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill |
| 2016 | IJCAI | Questimator: Generating Knowledge Assessments for Arbitrary Topics. | Qi Guo, Chinmay Kulkarni, Aniket Kittur, Jeffrey P. Bigham, Emma Brunskill |
| 2016 | IJCAI | Efficient Bayesian Clustering for Reinforcement Learning. | Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic |
| 2016 | IJCAI | Latent Contextual Bandits and their Application to Personalized Recommendations for New Users. | Li Zhou, Emma Brunskill |
| 2015 | AAAI | Concurrent PAC RL. | Zhaohan Guo, Emma Brunskill |
| 2015 | AAAI | The Queue Method: Handling Delay, Heuristics, Prior Data, and Evaluation in Bandits. | Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic |
| 2015 | EDM | Towards Understanding How to Leverage Sense-making, Induction/Refinement and Fluency to Improve Robust Learning. | Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill |
| 2015 | EDM | From Predictive Models to Instructional Policies. | Joseph Rollinson, Emma Brunskill |
| 2014 | AAAI | Quantifying Uncertainty in Batch Personalized Sequential Decision Making. | Vukosi Marivate, Jessica Chemali, Emma Brunskill, Michael L. Littman |
| 2014 | CHI | Towards automatic experimentation of educational knowledge. | Yun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popovic |
| 2014 | EDM | Trading Off Scientific Knowledge and User Learning with Multi-Armed Bandits. | Yun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popovic |
| 2014 | ICML | Online Stochastic Optimization under Correlated Bandit Feedback. | Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill |
| 2014 | ICML | PAC-inspired Option Discovery in Lifelong Reinforcement Learning. | Emma Brunskill, Lihong Li |
| 2013 | EDM | Predicting Player Moves in an Educational Game: A Hybrid Approach. | Yun-En Liu, Travis Mandel, Eric Butler, Erik Andersen, Eleanor O'Rourke, Emma Brunskill, Zoran Popovic |
| 2013 | EDM | Estimating Student Knowledge from Paired Interaction Data. | Anna N. Rafferty, Jodi L. Davenport, Emma Brunskill |
| 2013 | ICTD | Towards operationalizing outlier detection in community health programs. | Ted McCarthy, Brian DeRenzi, Joshua Evan Blumenstock, Emma Brunskill |
| 2013 | MDM | Understanding Sequential Decisions via Inverse Reinforcement Learning. | Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo J. F. Rossetti, Joo Barros, Ramayya Krishnan |
| 2013 | PAKDD | Modeling Social Information Learning among Taxi Drivers. | Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel M. Ni |
| 2013 | UAI | Sample Complexity of Multi-task Reinforcement Learning. | Emma Brunskill, Lihong Li |
| 2012 | AAMAS | Bayes-optimal reinforcement learning for discrete uncertainty domains. | Emma Brunskill |
| 2012 | EDM | The Impact on Individualizing Student Models on Necessary Practice Opportunities. | Jung In Lee, Emma Brunskill |
| 2012 | EDM | Policy Building - An Extension To User Modeling. | Michael Yudelson, Emma Brunskill |
| 2012 | UAI | Incentive Decision Processes. | Sashank Jakkam Reddi, Emma Brunskill |
| 2011 | AIED | Faster Teaching by POMDP Planning. | Anna N. Rafferty, Emma Brunskill, Thomas L. Griffiths, Patrick Shafto |
| 2011 | EDM | Estimating Prerequisite Structure From Noisy Data. | Emma Brunskill |
| 2011 | EDM | Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System. | Emma Brunskill, Stuart Russell |
| 2010 | AAAI | PUMA: Planning Under Uncertainty with Macro-Actions. | Ruijie He, Emma Brunskill, Nicholas Roy |
| 2010 | UAI | RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains. | Emma Brunskill, Stuart Russell |
| 2009 | ICRA | Where to go: Interpreting natural directions using global inference. | Yuan Wei, Emma Brunskill, Thomas Kollar, Nicholas Roy |
| 2009 | ICTD | Evaluating the accuracy of data collection on mobile phones: A study of forms, SMS, and voice. | Somani Patnaik, Emma Brunskill, William Thies |
| 2008 | ISAIM | Continuous-State POMDPs with Hybrid Dynamics. | Emma Brunskill, Leslie Pack Kaelbling, Toms Lozano-Prez, Nicholas Roy |
| 2008 | UAI | CORL: A Continuous-state Offset-dynamics Reinforcement Learner. | Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy |
| 2007 | AAAI | Continuous State POMDPs for Object Manipulation Tasks. | Emma Brunskill |
| 2007 | IROS | Topological mapping using spectral clustering and classification. | Emma Brunskill, Thomas Kollar, Nicholas Roy |
| 2007 | IROS | Collision detection in legged locomotion using supervised learning. | Finale Doshi, Emma Brunskill, Alexander C. Shkolnik, Thomas Kollar, Khashayar Rohanimanesh, Russ Tedrake, Nicholas Roy |
| 2005 | ICRA | SLAM using Incremental Probabilistic PCA and Dimensionality Reduction. | Emma Brunskill, Nicholas Roy |
| 2001 | HotOS | Building peer-to-peer systems with Chord, a distributed lookup service. | Frank Dabek, Emma Brunskill, M. Frans Kaashoek, David R. Karger, Robert Morris, Ion Stoica, Hari Balakrishnan |