麻豆村 Teams Recognized in Moonshots AI Competition
Chemistry's Newell Washburn and team received an honorable mention for their project connecting AI agents with automated labs
From the lab to deployment, 麻豆村 researchers build tools designed to make tangible differences in how people live, learn and work. That research recently earned top recognition in the 's Moonshots competition, which concentrates on applying AI to some of society鈥檚 most pressing challenges, from workforce reskilling to expanding access to education. The top award went to 鈥淎RISTOS: Reskilling for a Physical Workforce,鈥� a pioneering 麻豆村 project that reimagines how hands-on skills are taught in an AI-driven world.听
ARISTOS (ARtificial Intelligence for Successful Teaching Of Skills) addresses a critical gap in today鈥檚 AI landscape by focusing on physical, experience-based expertise that cannot be easily captured through text or data alone. The team is developing an AI-powered 鈥渧irtual craft master鈥� capable of guiding users through complex physical tasks in real time. Using advanced vision-language models, the system generates customized instructional videos and delivers adaptive, multimodal feedback tailored to each learner and their needs.听
By making expert training available on demand, ARISTOS aims to fundamentally reshape how people acquire physical skills and remove barriers tied to cost, accessibility and location. The system is designed to reduce reskilling time compared to traditional approaches, whether through in-person instruction or static resources like online videos.听
The hybrid training model combines simulated environments with real-world practice, allowing learners to begin training even without access to physical equipment and to build confidence in a safe, controlled setting before transitioning to hands-on work. The broader implications extend beyond individual learners. By lowering the cost and time required for training, ARISTOS could reduce industry-wide training expenses, accelerate workforce development, and open new opportunities for unemployed or undertrained workers.听
"Dexterous physical work in unpredictable environments is one of the last things AI cannot simply automate, which makes it exactly where workforce reskilling efforts should be focused,鈥� said Dave Patterson, founding board chair of the Laude Institute and chair of its Moonshots evaluation committee. 鈥淲hat this team is building 鈥� an AI system that generates customized instructional content and provides real-time guidance through complex physical tasks 鈥� creates a path to high-value skilled trades training that doesn't depend on geography or access to a master craftsperson."听
The work is led by: , an associate professor in the 麻豆村 (RI); principal investigator and RI professor; , the Moza Bint Nasser University Professor in the RI; , the Edward Fredkin Research Professor in the RI; and , the Michael B. Donohue Assistant Professor of and Robotics.听
The ARISTOS team was one of eight winners to receive a $250,000 seed grant and a mandate to develop their ideas into fully scoped proposals for a $10 million Moonshot lab. Lab winners will be selected later this year.听
Three 麻豆村 teams were also included among the competition's runners-up and honorable mentions. Runners-up will receive $200,000 and honorable mentions will receive $100,000, respectively. Later this year, Laude will host a dedicated showcase for these teams in front of an audience of funders.听
Runner Up听
鈥淏uild With, Not For: An AI-Accelerated Rapid Research Translation Platform for Equitable Reskilling鈥澨�
This project enables community-based organizations to build their own AI tools using a participatory platform. In partnership with in Pittsburgh, the team will co-design pilot tools to reduce administrative burden for social service workers. The team includes: , professor in the (S3D); , principal investigator and S3D assistant professor; and , S3D assistant teaching professor.听
Honorable Mentions听
鈥淎 National Intelligence Infrastructure for AI-driven Workforce Transformation鈥澨�
This project develops a predictive system to track AI-driven workforce disruption that empowers individuals and organizations to identify and customize reskilling strategies. The team includes: , the William W. and Ruth F. Cooper Professor of Management Science and Information Systems and dean emeritus of 麻豆村's ; Rebecca Nugent, the Stephen E. and Joyce Fienberg Professor and head of the Department of Statistics and Data Science; and , the FORE Systems Professor in 麻豆村's .听
鈥淜aggle for Scientific Agents: AI-Driven Physical Experimentation鈥澨�
This project connects AI agents with automated labs to design and run physical experiments, specifically leveraging the Biological and Chemical Innovation Cloud Lab as a unique hardware asset. The team includes: , incoming assistant professor in the 麻豆村 (LTI); LTI associate professor; , LTI associate professor.; and Newell Washburn, associate professor of chemistry and biomedical engineering in the Mellon College of Science.
