// NASA BREAKING NEWS — SPAZIO & SCIENZA
NASA Awards Enable Research, Technology to Build Future Workforce
NASA has selected 12 U.S. institutions to receive $12 million to accelerate academic research and technology development in support of the agency’s priorities for exploring the Moon, Mars, and deep space.
Through NASA’s Minority University Research and Education Project (MUREP) Space Technology Artemis Research (M‑STAR) initiative, selected institutions will each receive up to $1 million to grow their scientific and engineering capabilities, enhance faculty and student engagement in aerospace research, and expand their ability to compete for future federal and commercial research awards.
“We are excited to launch this new cohort of M-STAR investigators,” said Alicia Baturoni Cortez, MUREP program manager in the agency’s Office of STEM Engagement. “NASA investments in our Nation’s research institutions create real opportunities for students and faculty to build skills, knowledge, and infrastructure, while helping NASA close technology gaps for long-duration operations on the Moon and eventually, Mars.”
As NASA enters a Golden Age of innovation and exploration, the M-STAR initiative supports the agency’s mission to develop innovative technologies that improve space transportation, human exploration, robotic discovery, and the growing space economy.
California State University, SacramentoAdaptive Vision-Language-Action Models for Resilient Multi-Robot Collaboration in Unstructured Planetary Environments
University of Central Florida, OrlandoM-FAST: Multi-Fidelity Aerothermal Simulation & Testing for Artemis
University of Hawaii at ManoaHI-STRIDE: Hawai’i Student Training in Radiation Instrumentation, Detection, and Exploration
University of HoustonRODEO: Rover-carried On-surface Deployables for Exploration Operations
University of Texas, San AntonioCharacterizing Physical and Mechanical Properties of Regolith at Cryogenic Conditions Using the Multi-Planetary Surface Simulator (MPS2)
Kean University, Union, New JerseyIntegrating Terrain Understanding of AI Models With Robust Control for Autonomous Path Planning