First UMN-Led NSF Convergence Accelerator to Develop Water Quality Sensor Platform Enabled by AI
![five headshots of faculty members in a grid with one square that is a maroon background with a gold M](/sites/cse.umn.edu/files/styles/webp_scaled/public/2024-NSFConvergence_Accelerator_0.jpg.webp?itok=0FQqsHte)
The primary research team includes University of Minnesota College of Science and Engineering faculty Cara Santelli (earth and environmental sciences), Tianhong Cui (mechanical engineering), Yao-Yi Chiang (computer science and engineering), Chang Ge (computer science and engineering), and John Sartori (electrical and computer engineering).
ME Professor Tianhong Cui is part of a team of scientists and engineers selected as NSF Convergence Accelerator Phase 1 awardees for chemical water sensing. The team is the first from the University of Minnesota to lead a Convergence Accelerator project, a program that provides funding from NSF to solve societal challenges through convergence research and innovation to accelerate projects toward tangible solutions that make a difference.
The University of Minnesota team is developing Aquasense, a low-cost, compact, easy-to-use, rapid water quality sensor platform enabled by artificial intelligence (AI).