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NRT-AI: RESPONSIVE AND RESILIENT AI FOR AUTONOMOUS SYSTEMS ENGINEERING (RAISE) -ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING ENABLED TECHNOLOGIES ARE RAPIDLY GROWING AREAS OF NATIONAL PRIORITY AND ECONOMIC SIGNIFICANCE. AUTONOMOUS SYSTEMS ARE ENGINEERED SYSTEMS WHICH USE AI AND MACHINE LEARNING TO SENSE, COMMUNICATE, REACT, AND ADAPT IN UNPREDICTABLE ENVIRONMENTS. AUTONOMOUS SYSTEMS ARE BECOMING VITAL IN A WIDE RANGE OF SYSTEMS, INCLUDING SMART INFRASTRUCTURE, TRANSPORTATION SYSTEMS, INTERNET-OF-THINGS TECHNOLOGIES, AND BIOMEDICAL AND HEALTH APPLICATIONS. HOWEVER, ADVANCES IN TECHNOLOGY HAVE OUTPACED THE METHODS USED TO TEACH THESE SKILLS . MOST GRADUATE TRAINING FOR AUTONOMOUS SYSTEMS ENGINEERING DOES NOT PROVIDE STUDENTS WITH THE NECESSARY INTERDISCIPLINARY FOUNDATION. FURTHERMORE, TRAINING IN ETHICAL CONSIDERATIONS IS CRITICAL TO EMBRACING A HUMAN-CENTRIC APPROACH. THIS NATIONAL SCIENCE FOUNDATION RESEARCH TRAINEESHIP (NRT) AWARD TO THE UNIVERSITY OF NEW MEXICO WILL 1) TRAIN STUDENTS IN STATE-OF-THE-ART RESEARCH IN AI AND AUTONOMY, 2) PROVIDE OPPORTUNITIES FOR STUDENTS TO INTEGRATE THEIR KNOWLEDGE OF LEARNING AND AI, AS WELL AS KNOWLEDGE OF THE HUMAN CONTEXT, INTO THE ENGINEERING DESIGN PROCESS, AND 3) BROADEN PARTICIPATION OF UNDER-REPRESENTED AND FIRST-GENERATION STUDENTS. THE PROJECT ANTICIPATES TRAINING 70-80 MS AND PHD STUDENTS, INCLUDING 25 FUNDED TRAINEES, FROM ELECTRICAL AND COMPUTER ENGINEERING, COMPUTER SCIENCE, MECHANICAL ENGINEERING, CIVIL ENGINEERING, AND ORGANIZATIONAL AND INFORMATIONAL LEARNING SCIENCES. SOME OF THE MOST PRESSING CHALLENGES IN AUTONOMOUS SYSTEMS ARE THE NEED FOR RESILIENCE AND ROBUSTNESS TO ERRORS, AND THE NEED FOR RESPONSIVITY TO THE HUMAN CONTEXT, INCLUDING PRACTITIONER AWARENESS OF BROADER SOCIETAL IMPLICATIONS. THIS PROJECT WILL CREATE NOVEL THEORY, METHODS, TOOLS, AND IMPLEMENTATIONS FOCUSED ON ADDRESSING THESE CHALLENGES, ALONG FOUR INTERDISCIPLINARY RESEARCH THRUSTS: 1) SPACE AND DEFENSE AUTONOMY, 2) ALGORITHMIC FAIRNESS, 3) ROBOTICS AND INTELLIGENT SWARMS, AND 4) DISTRIBUTED LEARNING FOR EXTREME-SCALE SYSTEMS. TWO PRIMARY GOALS OF THE PROJECT ARE TO DEVELOP STUDENT PROFICIENCY IN INTERDISCIPLINARY TECHNICAL FOUNDATIONS, INCLUDING MACHINE LEARNING, CONTROL THEORY, ROBOTICS AND INTELLIGENT SYSTEMS, AND OPTIMIZATION, AND TO DEVELOP STUDENT AWARENESS OF THE HUMAN CONTEXT OF AI AND AUTONOMOUS SYSTEMS. THE PROJECT WILL DEVELOP A NEW GRADUATE CERTIFICATE IN AI AND AUTONOMOUS SYSTEMS, WHOSE CORNERSTONE IS A TWO-SEMESTER PROJECT-BASED DESIGN COURSE THAT EMPLOYS AN ETHICS-AS-DESIGN APPROACH. THE PROJECT WILL ALSO FEATURE RESEARCH INTERNSHIPS WITH INDUSTRY AND GOVERNMENT LABS TO BUILD EXPOSURE TO NON-ACADEMIC PIPELINES, AND TO HELP MOTIVATE THE STUDENTS? RESEARCH. ADDITIONAL PROJECT GOALS INCLUDE FOSTERING STUDENTS? PROFESSIONAL DEVELOPMENT THROUGH ACTIVITIES THAT FOCUS ON COMMUNICATION, TEAMWORK, AND MENTORING. THE NSF RESEARCH TRAINEESHIP (NRT) PROGRAM IS DESIGNED TO ENCOURAGE THE DEVELOPMENT AND IMPLEMENTATION OF BOLD, NEW POTENTIALLY TRANSFORMATIVE MODELS FOR STEM GRADUATE EDUCATION TRAINING. THE PROGRAM IS DEDICATED TO EFFECTIVE TRAINING OF STEM GRADUATE STUDENTS IN HIGH PRIORITY INTERDISCIPLINARY OR CONVERGENT RESEARCH AREAS THROUGH COMPREHENSIVE TRAINEESHIP MODELS THAT ARE INNOVATIVE, EVIDENCE-BASED, AND ALIGNED WITH CHANGING WORKFORCE AND RESEARCH NEEDS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

Project Grant (B) · National Science Foundation · to University of New Mexico (UEI F6XLTRUQJEN4) · data as of 2026-09-30

Source: USAspending.gov prime award transactions and FSRS subaward reports, as loaded by SpendQuery (data as of 2026-09-30). Amounts are obligations (money committed), not outlays. The official record on USAspending.gov ↗