Mary Pourebadi, Ph.D.
Mary Pourebadi, Ph.D.
Pronouns: she, her, hers
Lecturer of Computer Science
College of Sciences
Department of Computer Science
San Diego, CA
BIO
Mary Pourebadi, Ph.D. is a Lecturer in the Department of Computer Science at San Diego State University (SDSU) and an Advisor at the James Silberrad Brown Center for Artificial Intelligence (JSBC-AI). Her research lies at the intersection of applied artificial intelligence, robotics, and human–robot interaction (HRI), with a focus on building embodied AI systems that can autonomously and adaptively interact with people in real-world environments.
Dr. Pourebadi earned her Ph.D. in Computer Science and Engineering from the University of California, San Diego (UC San Diego), where she developed expressive and interactive robotic systems for healthcare and education. Her research emphasized human-grounded, data-driven models of behavior, enabling robotic systems—such as robotic patient simulators—to support realistic, safe, and adaptive interaction in human-facing settings beyond the laboratory. At SDSU, her current research advances multimodal and embodied AI for autonomous robotic systems, integrating large language models (LLMs) and vision–language models (VLMs) with perception, reasoning, and control to enable closed-loop decision-making under real-world constraints.
Dr. Pourebadi’s work has been recognized at premier robotics, computing, and healthcare venues, including the flagship ACM/IEEE International Conference on Human-Robot Interaction (HRI), ACM HEALTH journal, AAAI AI‐HRI, IEEE FG, RSS, IPCV, AHA, ICIS, HICSS, NDSS, and QRS, and has received multiple honors recognizing her leadership, mentorship, and community impact, including the ACM Certificate of Recognition, CRA-W/GPSA Award, ACM Tapia Awards, and multiple Grace Hopper Celebration awards.
In addition to her research, Dr. Pourebadi teaches undergraduate and graduate courses in robotics, machine learning, AI for Business Applications, and advanced programming languages. She emphasizes hands-on, systems-oriented learning and mentors students across disciplines, with a strong commitment to inclusive excellence and student-centered research.
EDUCATION
Ph.D., University of California San Diego (UC San Diego), 2023
Major: Computer Science and Engineering
RESEARCH
Dr. Pourebadi directs The CARE Lab, where she leads ongoing research projects in robotics and embodied artificial intelligence. Her research also builds on prior work and collaborations across academic labs and interdisciplinary research centers, which inform the current directions of CARE Lab research.
The CARE Lab (Cognition, Adaptation & Reasoning for Embodied AI) conducts research at the intersection of robotics, multimodal AI, and intelligent agent design. The lab focuses on how embodied systems perceive, reason, and interact in real world environments, with students contributing through exploratory research in multimodal memory, adaptive dialogue, and socially aware robot control.
Click to the next page to more about ongoing and emerging projects in The CARE Lab.
TEAM
This team includes undergraduate/graduate students and academic collaborators who work with Dr. Pourebadi as teaching assistants, research assistants, or both, contributing to instruction and research across her courses and The CARE Lab.
PUBLICATIONS
Elkins, A., Singh, S., Pourebadi, M., Amadasun, U., Abhari, K. (2026)
"Designing Socially Grounded Data Pipelines for Training and Operating Socially Intelligent Robots: Challenges and Future Directions". Hawaii International Conference on System Sciences (HICSS).
Elkins, A., Singh, S., Pourebadi, M., Amadasun, U., Abhari, K. (2025)
"Training Socially Intelligent Robots with Large Behavior Models: Challenges, Strategies, and Future Research Opportunities". International Conference on Information Systems (ICIS).
Homayouni, H., Pourebadi, M., Dabhi, S. N., Nguyen, S. T., Badlani, P. P., Hashemi, M., Shirazi, H. (2024)
“Towards Comprehensive Functional Testing in ETL Processes: A Classification Framework and Empirical Validation on a Real-World Data Warehouse,” 24th IEEE International Conference on Software Quality, Reliability, and Security (QRS) [Acceptance rate: 23.81%].
Homayouni, H., Pourebadi, M., Shirazi, H. (2024)
"Federated Multimodal Medical Data Generation," The Network and Distributed System Security Symposium (NDSS) [Acceptance rate: 20%].
Pourebadi, M., Riek, L.D. (2022)
"Facial Expression Modeling and Synthesis for Patient Simulator Systems: Past, Present, and Future," ACM Transactions on Computing for Healthcare (HEALTH) journal 3(2), 1-32.
Kubota, A., Pourebadi, M., Banh, S., Kim, S., Riek, L.D. (2021) "Somebody That I Used to Know: The Risks of Personalizing Robots for Dementia Care," We Robot 2021. [Acceptance rate: 15%].
Pourebadi, M., and Riek, L.D. (2020)
"Stroke Modeling and Synthesis for Robotic and Virtual Patient Simulators," AAAI Fall Symposium on Artificial Intelligence in Human-Robot Interaction: Trust & Explainability in Artificial Intelligence for Human-Robot Interaction (AAAI AI-HRI).
Pourebadi, M., Gonzalez, C. G., LaBuzetta, J. N., Meyer, B. C., Suresh, P., Riek, L. D. (2020)
"Mimicking Acute Stroke Findings With a Digital Agent," International Stroke Conference (ISC), American Heart Association Journal (AHA ISC).
Ghayoumi, M., and Pourebadi, M. (2019)
"Fuzzy Knowledge-Based Architecture for Learning and Interaction in Social Robots'', AAAI Fall Symposium on Artificial Intelligence and Human-Robot Interaction: Service Robots in Human Environments (AAAI AI-HRI).
Moosaei, M., Pourebadi, M., and Riek, L.D. (2019)
"Modeling and Synthesizing Idiopathic Facial Paralysis'', IEEE International Conference on Automatic Face and Gesture Recognition (FG). [Acceptance rate: 20%]
Pourebadi, M., and Riek, L.D. (2018)
"Expressive Robotic Patient Simulators for Clinical Education," Robots 4 Learning workshop at the 13th Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI).
Pourebadi, M., Pourebadi, M. (2016)
"MLP Neural Network Based Approach for Facial Expression Analysis," 20th International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV). [Acceptance rate: 24%]
Ghayoumi, M., Khan, J., Pourebadi, M., Bauer, E., Hossain, A. (2016) "Follower Robot with an Optimized Gesture Recognition System," Socially & Physically Assistive Robotics For Humanity workshop at Robotics: Science and Systems (RSS).
CONTACT US
If you are a motivated graduate or undergraduate student interested in volunteering for research in the CARE Lab, feel free to contact Dr. Pourebadi directly.