OBSERVE
THE
EVERYDAY
DESIGN THE EXPERIENCE
I design to reduce friction in everyday interactions.
U LAM.
Hi, I'm
PUBLICATIONS
Emergency departments (EDs) are fast-paced, dynamic, safety-critical spaces where clinicians are overworked and underpaid. To support clinicians, researchers are exploring the contextualization and development of clinically assistive robots (CARs) that can assume non-critical tasks to reduce clinician overload. In this article, we introduce Clinically Assistive Robot System for Emergency Medicine (CAR-EM), collaboratively developed with ED clinicians. CAR-EM includes an autonomous robot and a task specification interface. It completes tasks by leveraging control synthesis, a framework that automatically transforms high-level tasks into control while providing guarantees and feedback. We conducted a feasibility study across two different hospital EDs, where interprofessional clinicians tasked the robot to perform patient assessments and item deliveries. Clinicians found the system easy to use, and particularly helpful to offload busywork. This work demonstrates control synthesis as a feasible tool to develop autonomy for robots in safety-critical spaces, and identifies considerations for failure interventions. We also discuss ethical considerations for deploying robots in hospitals, including healthcare worker displacement and work disruption. Thus, our work: (1) highlights the unique requirements of situating robots in real world hospital EDs, and (2) demonstrates a novel approach leveraging guarantees and feedback from control synthesis methods to successfully implement context-specific CAR behaviors. Through this work, we aim to further research for safer and more reliable robots in real world, uncertain environments.
@article{10.1145/3797263,
author = {Jayaraman, Sandhya and Violette, Andrew and Lou, U Lam and Mani, Sruti and Prakash, Divya and Oyama, Leslie and Coyne, Christopher and Kress-Gazit, Hadas and Riek, Laurel},
title = {CAR-EM: A Synthesis-Based Clinically Assistive Robot System for Emergency Medicine},
year = {2026},
issue_date = {May 2026},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {15},
number = {3},
url = {https://doi.org/10.1145/3797263},
doi = {10.1145/3797263},
abstract = {Emergency departments (EDs) are fast-paced, dynamic, safety-critical spaces where clinicians are overworked and underpaid. To support clinicians, researchers are exploring the contextualization and development of clinically assistive robots (CARs) that can assume non-critical tasks to reduce clinician overload. In this article, we introduce Clinically Assistive Robot System for Emergency Medicine (CAR-EM), collaboratively developed with ED clinicians. CAR-EM includes an autonomous robot and a task specification interface. It completes tasks by leveraging control synthesis, a framework that automatically transforms high-level tasks into control while providing guarantees and feedback. We conducted a feasibility study across two different hospital EDs, where interprofessional clinicians tasked the robot to perform patient assessments and item deliveries. Clinicians found the system easy to use, and particularly helpful to offload busywork. This work demonstrates control synthesis as a feasible tool to develop autonomy for robots in safety-critical spaces, and identifies considerations for failure interventions. We also discuss ethical considerations for deploying robots in hospitals, including healthcare worker displacement and work disruption. Thus, our work: (1) highlights the unique requirements of situating robots in real world hospital EDs, and (2) demonstrates a novel approach leveraging guarantees and feedback from control synthesis methods to successfully implement context-specific CAR behaviors. Through this work, we aim to further research for safer and more reliable robots in real world, uncertain environments.},
journal = {J. Hum.-Robot Interact.},
month = apr,
articleno = {63},
numpages = {22},
keywords = {Human–Robot Interaction, Clinically Assistive Robots, Acute Care, Formal Methods, Control Synthesis}
}
Academic procrastination is detrimental to many students’ academic performance, well-being, and learning abilities. Acceptance and Commitment Therapy (ACT) interventions, including our own in-person workshop, have been effective in reducing academic procrastination. To offer a more accessible yet useful alternative for large student populations, we developed ClearMind, a smartphone-based application grounded in ACT. It comes with interactive activities to help students manage academic procrastination. This paper reports our qualitative study on user perception and attitudes toward using ClearMind. The data was collected from two focus group meetings and analyzed using inductive and deductive thematic analysis. Our results indicate that the participants found ClearMind both useful and easy to use, with many expressing a willingness to continue using it and recommend it to others. Feedback from this study sheds light on how to refine its features to better align with students’ academic needs. Future work will involve conducting a large-scale quantitative study, in order to further evaluate its effectiveness in reducing academic procrastination and its long-term impact on academic performance.
@inproceedings{li2025exploring,
title={Exploring Student Use of an ACT-based Mobile Application and its Impact on Reducing Procrastination},
author={Li, Yiqing and Yu, Jiaen and Lou, U Lam and Yu, Dingyi and Levin, Michael and Klimczak, Korena S and Liao, Soohyun Nam},
booktitle={2025 ASEE Annual Conference \& Exposition},
year={2025}
}
