Rate My Professor Janet Roveda

Janet Meiling Roveda is the Litton Industries John M. Leonis Distinguished Professor of Electrical and Computer Engineering at the University of Arizona, holding joint appointments as Professor of Biomedical Engineering, Professor of Nursing, and Professor at the BIO5 Institute. She earned her M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 1998 and 2000, respectively. Roveda's research specializations include robust VLSI circuit design, biomedical instrument design, smart grids, VLSI circuit modeling, design and analysis, low-power multi-core system design, microgrids, green energy systems, low-power system design, and battery design. She directs the NSF Industry/University Cooperative Research Center to Stream Healthcare In Place (C2SHIP), advancing wearable medical technologies and digital health solutions for at-home healthcare monitoring. Her work also extends to data-centric systems, reliable circuits, DNA computing, and synthetic biology, with applications in semiconductor manufacturing and energy solutions.

Roveda has garnered significant recognition for her contributions, including the NSF CAREER Award in 2005, the Presidential Early Career Award for Scientists and Engineers presented at the White House in 2006, the 2008 R. Newton Graduate Research Award from the electronic design automation community, and the 2007 University of Arizona Outstanding Achievement Award. Additional honors encompass the AIMBE College of Fellows election, the 2024 University of Arizona Women of Impact Award, Da Vinci Fellowship, best paper awards at ISQED 2010 and the Journal of Clean Energy in 2013, and nominations at ASPDAC 2010, ICCAD 2007, and ISQED 2005. With over 120 publications, key works include "Resilient distribution system by microgrids formation after natural disasters" (IEEE Transactions on Smart Grid, 2015), "Stability enhancement based on virtual impedance for DC microgrids with constant power loads" (IEEE Transactions on Smart Grid, 2015), "A deep learning-based algorithm for detection of cortical arousal during sleep" (Sleep, 2020), "Obstructive sleep apnea predicts 10-year cardiovascular disease related mortality in the Sleep Heart Health Study: a machine learning approach" (Journal of Clinical Sleep Medicine, 2021), and "Sleep patterns and sleep deprivation recorded by actigraphy in 4th-grade and 5th-grade students" (Sleep Medicine, 2020). Her leadership in research centers and innovations have advanced fields such as digital health, renewable energy, and biomedical engineering.