Advancing Cutting-Edge Research and Education
At ARC Lab, we push the boundaries of innovation in autonomy, robotics, and connectivity to create impactful, real-world solutions. Located at the University of Washington's Department of Electrical and Computer Engineering, our lab is dedicated to advancing cutting-edge research and education to address some of the most pressing challenges in technology and society.
Robust Autonomous Systems
Our focus on robust autonomous systems enables us to develop state-of-the-art solutions that are paving the way for the future of autonomy and robotics.
Innovative Robotics Applications
We specialize in developing innovative applications for robotics that have the potential to revolutionize various industries and enhance connectivity.
Connectivity Solutions
At ARC Lab, we are at the forefront of creating advanced connectivity solutions that facilitate seamless communication and interaction in diverse environments.
Education and Outreach Initiatives
In addition to our research endeavors, we are actively involved in educational programs and outreach initiatives aimed at fostering the next generation of innovators in autonomy, robotics, and connectivity.
Publications
Sensemaking Without Mission Control: How a Grounded Onboard Assistant Redistributes the Cognitive Work of Fault Diagnosis
Nathan, G., Pasupathi, K., Shen, Y., Stafford, M., Shao, K., Mamishev, A., and Makhsous, S. SpaceCHI 2026, NASA Ames Research Center (Springer LNCS, in press)
Comparative Assessment of Common Geometries in DC Corona Electrohydrodynamic Actuators for Propulsion Applications.
Nathan, G., Stoyanov, I., Liu, Z., Makhsous, S., Mamishev, A., IEEE International Conference on Plasma Science (ICOPS) 2026, Lake Tahoe, NV. https://doi.org/10.1109/ICOPS53334.2026.11659944
Satellite Level GNSS Signal Integrity for Urban Air Mobility Systems.
Chan, S., Nathan, G., Anderson, E., and Makhsous, S.. 18th AIAA Pacific Northwest Section Technical Symposium, Seattle, 2026.
AETOS: Near-Field Urban Pollution Monitoring Using a Distributed Sensor Network and Backward–Forward Lagrangian Modeling: A Fireworks Case Study at Lake Union Seattle
Liu, Z., Nathan, G., Xu, X., Yang, M., Pasupathi, K., Mamishev, M., Tusty, T., Anderson, E., and Makhsous, S. Air 2026, 4(3), 16. https://doi.org/10.3390/air4030016
Translating AI from the Laboratory to the Flight Line: Building Trustworthy Autonomy for the Next Era of Airspace.
Nathan, G. 2025 IEEE New Era AI World Leaders Summit, Dec 2025.
Design and Deployment of a Hybrid Neural Network for Real-Time GPS Correction in Slow Moving, Low SWaP, UAV Flight Systems.
Nathan, G., Cucioglu, A., Makhsous, S., et al. GPS Solutions 29(3):153, 2025. https://doi.org/10.1007/s10291-025-01911-y
Bridging Educational Equity Gaps: A Systematic Review of AI-Driven and New Technologies for Students Living with Disabilities in STEM Education
Shao, K., Wilson, D., Cho, E., Tang, S., Ma, H., and Makhsous, S., ASEE CoNECD (Collaborative Network for Engineering and Computing Diversity) 2025, 2025.
Our Sponsors and Collaborators
