Alyssa Kubota

I am a PhD student with the Contextual Robotics Institute in the Computer Science and Engineering Department at UC San Diego. I am advised by Dr. Laurel Riek in the Healthcare Robotics Lab. My research unites robotics and artificial intelligence to create technology that helps people in need.



Kubota, A., Pei, R., Sun, E., Cruz-Sandoval, D., Kim, S., and Riek, L.D. "Get SMART: Collaborative Goal Setting with Cognitively Assistive Robots." In Proceedings of the 18th Annual ACM/IEEE Conference on Human Robot Interaction (HRI). 2023. [Acceptance rate: 25%] [PDF]
Kubota, A., Cruz-Sandoval, D., Kim, S., Twamley, E., and Riek, L.D. "Cognitively Assistive Robots at Home: HRI Design Patterns for Translational Science." In Proceedings of the 17th Annual ACM/IEEE Conference on Human Robot Interaction (HRI). 2022. [Acceptance rate: 25%] [PDF]

Best Design Paper Award Honorable Mention

Kubota, A., Pourebadi, M., Banh, S., Kim, S., and Riek, L. D. "Somebody That I Used to Know: The Risks of Personalizing Robots for Dementia Care". In Proceedings of We Robot, 2021. [Acceptance Rate: 15%] [PDF]
Kubota, A. and Riek, L. D. "Methods for Robot Behavior Adaptation for Cognitive Neurorehabilitation". Annual Review of Control, Robotics, and Autonomous Systems, 2021. [PDF Preprint] [e-print URL]
Kubota, A. and Riek, L. D. "Behavior Adaptation for Robot-Assisted Neurorehabilitation". In Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction (HRI) Pioneers Workshop, 2021. [Acceptance Rate: 37%] [PDF]
Banh, S., Zheng, E., Kubota, A., and Riek, L. D. "A Robot-based Gait Training System for Post-Stroke Rehabilitation". In Companion of the ACM/IEEE International Conference on Human-Robot Interaction (HRI Companion) Late Breaking Reports Workshop, 2021. [PDF]
Kubota, A., Peterson, E. I. C., Rajendren, V., Kress-Gazit, H., and Riek, L. D. "JESSIE: Synthesizing Social Robot Behaviors for Personalized Neurorehabilitation and Beyond". In Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, 2020. [Acceptance Rate: 24%] [PDF]
Taylor, A., Lee, H. R., Kubota, A., and Riek, L. D. "Coordinating Clinical Teams: Using Robots to Empower Nurses to Stop the Line". In Proceedings of the ACM Conference on Computer-Supported Cooperative Work (CSCW), 2019. [Acceptance Rate: 30%] [PDF]

Best Paper Award Honorable Mention (Top 5% of submissions)

Kubota, A., Iqbal, T., Shah, J. A., and Riek, L. D. "Activity recognition in manufacturing: The roles of motion capture and sEMG+inertial wearables in detecting fine vs. gross motion". In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2019. [PDF]
Frank, A. E., Kubota, A., and Riek, L. D. "Wearable activity recognition for robust human-robot teaming in safety-critical environments via hybrid neural networks". In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019. [PDF]


Autonomous Robots for Delivering Longitudinal Health Interventions

UC San Diego
I am developing robots to deliver an existing clinical intervention to people with cognitive impairments at home. Over the past several years, I developed CARMEN (Cognitively Assistive Robot for Motivation and Neurorehabilitation), which administers compensatory cognitive training (CCT) to people with cognitive impairments. I am engaging with stakeholders to co-design and evaluate these systems.

Control Synthesis for Accessible Robot Programming

UC San Diego
In healthcare contexts, it is critical that end users, clinicians, and family members are able to program robots without advanced skills in robotics or programming. Thus, I developed JESSIE (Just Express Specifications, Synthesize, and Interact), a robotic system which enables novice programmers to program social robots by expressing high-level specifications and control synthesis approaches. JESSIE is open source to support reproducibility in robotics.

Human-Robot Teaming in Safety Critical Environments

UC San Diego
Through this project, we explored multi-human, multi-robot collaboration in safety-critical environments such as emergency departments and manufacturing settings. These environments contain privacy-sensitive information, so placing robots with visual sensors in these areas may introduce security and privacy concerns. However, robots still need the capability to perceive and understand activity in these environments in order to interact meaningfully. Therefore, we explored the integration of non-visual wearable sensors with machine learning algorithms in order to perform human activity recognition and model workflow.

Computing for Active Transportation

Harvey Mudd College
While working together with members of the surrounding community, I developed a “walking school bus” routing program designed to help students safely and easily meet to walk to school together. The program integrates Google Maps and OpenStreetMaps APIs to automatically determine where students should meet to minimize travel time for students and parents. By comparing expected travel times with and without the program, I found that this program would have many benefits: it reduces the time parents spend driving their children to school, helps improve the health of students who participate, and reduces traffic and thereby air pollution around the school.


University of California, San Diego

Doctor of Philosophy, Computer Science

Anticipated Graduation: June 2023

University of California, San Diego

Master of Science, Computer Science

December 2020

Harvey Mudd College

Bachelor of Science, Computer Science

May 2017

Let's connect!

Send me an email: akubota [at]
And find me at the following sites: