Piggybacking Robots: Human-Robot Overtrust in University Dormitory Security. - Serena Booth; James Tompkin 001; Hanspeter Pfister; Jim Waldo; Krzysztof Gajos; Radhika Nagpal (HRI, 2017)

Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively. - Serena Booth; Christian Muise; Julie Shah (IJCAI, 2019)

Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI). - Tom Williams 001; Daniel Szafir; Tathagata Chakraborti; Soh-Khim Ong; Eric Rosen; Serena Booth; Thomas R. Groechel (HRI (Companion), 2020)

Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach. - Serena Booth; Ankit Shah 003; Yilun Zhou; Julie Shah (CoRR, 2020)

Bayes-Probe: Distribution-Guided Sampling for Prediction Level Sets. - Serena Booth; Yilun Zhou; Ankit J. Shah; Julie A. Shah (CoRR, 2020)

Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example. - Serena Booth; Yilun Zhou; Ankit Shah 003; Julie Shah (AAAI, 2021)

Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development. - Aspen K. Hopkins; Serena Booth (AIES, 2021)

RoCUS: Robot Controller Understanding via Sampling. - Yilun Zhou; Serena Booth; Nadia Figueroa; Julie Shah (CoRL, 2021)

The Irrationality of Neural Rationale Models. - Yiming Zheng; Serena Booth; Julie Shah; Yilun Zhou (CoRR, 2021)

IEEE P7001: A Proposed Standard on Transparency. - Alan F. T. Winfield; Serena Booth; Louise A. Dennis; Takashi Egawa; Helen F. Hastie; Naomi Jacobs; Roderick I. Muttram; Joanna I. Olszewska; Fahimeh Rajabiyazdi; Andreas Theodorou; Mark A. Underwood; Robert H. Wortham; et al. (Frontiers Robotics AI, 2021)

Do Feature Attribution Methods Correctly Attribute Features? - Yilun Zhou; Serena Booth; Marco Túlio Ribeiro; Julie Shah (AAAI, 2022)

Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning. - Serena Booth; Sanjana Sharma; Sarah Chung; Julie Shah; Elena L. Glassman (HRI, 2022)

The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. - Serena Booth; W. Bradley Knox; Julie Shah; Scott Niekum; Peter Stone 001; Alessandro Allievi (AAAI, 2023)

Aligning Robot Behaviors with Human Intents by Exposing Learned Behaviors and Resolving Misspecifications. - Serena Booth (HRI (Companion), 2023)

Variable Autonomy for Human-Robot Teaming (VAT). - Manolis Chiou; Serena Booth; Bruno Lacerda; Andreas Theodorou; Simon Rothfuß (HRI (Companion), 2023)

Quality-Diversity Generative Sampling for Learning with Synthetic Data. - Allen Chang; Matthew C. Fontaine; Serena Booth; Maja J. Mataric; Stefanos Nikolaidis (AAAI, 2024)

Learning Optimal Advantage from Preferences and Mistaking It for Reward. - W. Bradley Knox; Stephane Hatgis-Kessell; Sigurdur O. Adalgeirsson; Serena Booth; Anca D. Dragan; Peter Stone 001; Scott Niekum (AAAI, 2024)

Models of human preference for learning reward functions. - W. Bradley Knox; Stephane Hatgis-Kessell; Serena Booth; Scott Niekum; Peter Stone 001; Alessandro Gabriele Allievi (Trans. Mach. Learn. Res., 2024)

Building Blocks for Human-AI Alignment: Specify, Inspect, Model, and Revise - Serena Booth (2024)

AI Governance and Lessons Learned as an AI Policy Advisor in the United States Senate. - Serena Booth (AAAI, 2025)

Goals vs. Rewards: Towards a Comparative Study of Objective Specification Mechanisms. - Septia Rani; Serena Booth; Sarath Sreedharan (HRI, 2025)

Influencing Humans to Conform to Preference Models for RLHF. - Stephane Hatgis-Kessell; W. Bradley Knox; Serena Booth; Scott Niekum; Peter Stone 001 (CoRR, 2025)

Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners. - Calarina Muslimani; Kerrick Johnstonbaugh; Suyog Chandramouli; Serena Booth; W. Bradley Knox; Matthew E. Taylor (CoRR, 2025)