My work spans computer vision, human-robot interaction, and disaster response. A continuously updated list is on my Google Scholar profile.
Thomas Manzini, Priyankari Perali, Raisa Karnik, Stephen Johnson, and Robin Murphy. Looks Can Be Deceiving: Annotator and Reviewer Performance Across Imagery Sources in Crowd-Sourced Aerial Damage Assessment. In Proceedings of the 2026 AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2026. (To appear)
Atif Mohammed Ashraf, Priyankari Perali, Hyun-Gee Jei, Joseph W. Hendricks, Thomas Manzini, Vanessa Nasr, S. Camille Peres, Farzan Sasangohar, Maryam Zahabi, and Robin Murphy. Investigating a Real-Time Adaptive Procedure System. Human-Intelligent Systems Integration, 2026.
Priyankari Perali*, Thomas Manzini*, Raisa Karnik, and Robin Murphy. A Benchmark Dataset for Spatially Aligned Road Damage Assessment in Small Uncrewed Aerial Systems Disaster Imagery. In Proceedings of the AAAI Conference on Artificial Intelligence, 2026. (*equal contribution)
Thomas Manzini, Priyankari Perali, and Robin Murphy. Deploying Rapid Damage Assessments from sUAS Imagery for Disaster Response. In The Thirty-Eighth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2026.
Priyankari Perali and Robin Murphy. Unprompted Touch with Touch Surface Characteristics: A Survey. ACM Transactions on Human-Robot Interaction, 15(1):1–30, 2025.
Priyankari Perali*, Thomas Manzini*, Robin Murphy, and David Merrick. Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene. In 2025 IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 2025. (*equal contribution)
Priyankari Perali*, Thomas Manzini*, Raisa Karnik, Mihir Godbole, Hasnat Abdullah, and Robin Murphy. Non-Uniform Spatial Alignment Errors in sUAS Imagery From Wide-Area Disasters. In 2025 IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 2025. (*equal contribution)
Thomas Manzini, Priyankari Perali, Jayesh Tripathi, and Robin Murphy. Now You See It, Now You Don't: Damage Label Agreement in Drone & Satellite Post-Disaster Imagery. In Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT), pages 1998–2008, 2025.
Thomas Manzini, Priyankari Perali, and Robin R. Murphy. Three Challenges in Utilizing Machine Learning to Predict Human Behavior from Observational Data. In Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI), pages 737–739, 2024.
Priyankari Perali*, Lance G. Fletcher*, Andrew Beathard, and Jason M. O'Kane. A Visibility-Based Escort Problem. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4804–4811. IEEE, 2023. (*equal contribution)
Thomas Manzini, Priyankari Perali, Raisa Karnik, and Robin Murphy. CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery. arXiv:2407.17673, 2024.
* denotes equal contribution.