Andrés Saavedra Ruiz is a fifth-year PhD student in the Bioengineering graduate program at the University of Puerto Rico, Mayagüez campus. His doctoral research focuses on the development of bacteriological water quality tools using electronics, microfluidics, and artificial intelligence. Currently, he is working on the development of a portable and self-loading microfluidic device prototype equipped with sensors to collect, test, and obtain bacteriological results from water samples in a few hours. His research has significant implications for water quality monitoring, especially in low-resource areas. By providing a quick and reliable method for detecting bacteriological water contamination, Andrés' work has the potential to improve the health and wellbeing of communities worldwide. Andrés holds a degree in electronic engineering from the Antonio Nariño University in Colombia. During his time there, he designed a control system to increase the production of compost derived from Coffee. Later, he pursued his master's studies in Electrical Engineering at the University of Puerto Rico, Mayagüez campus where he applied artificial intelligence algorithms to predict the presence of microbubbles from electrical signals detected by a piezoelectric sensor; this work was patented. His areas of interest include water quality, biosensors, control systems, digital signal processing, and artificial intelligence.

Dr. Pedro J. Resto-Irizarry is a Professor of Mechanical Engineering at the University of Puerto Rico Mayagüez. He holds a BS in Mechanical Engineering. His MS research was in Materials Science and PhD research in Biomedical Engineering. He completed his graduate studies at the University of Wisconsin-Madison, where he also undertook a postdoctoral fellowship in the Biochemistry Department. His research focuses on the development of biosensors for applications in human, animal, and environmental health. Current projects led by Dr. Resto-Irizarry include the use of Raman Spectroscopy and Artificial Intelligence (AI) for monitoring cell culture media, the creation of electrochemical sensors using biomarker-specific polymers to monitor cardiac troponin in human saliva, and the development of a microfluidic biosensor employing a defined substrate assay, photosensors, and AI for the rapid (<3 hours) detection of bacteriological contamination in environmental water samples. He teaches undergraduate and graduate courses in Mechatronics, Dynamics and Controls, and Biomedical Engineering topics.