Wireless health sensing, ubiquitous computing, wireless communication, embedded systems, energy harvesting, and machine learning for sensor data.
Professor Ganesan's research is at the intersection of low-power sensing and communication, networked systems, and machine learning to enable pervasive sensing at scale for societal applications. His recent work includes the design of ultra-low passive radios for wearables, novel wearable technologies such as low-power eye trackers to monitor health signals, and robust detection of important health targets such as drug use, smoking, and over-eating. He is a thrust lead on the NIH funded MD2K Center for Excellence on Mobile Sensor-to-Knowledge and on the executive committee of the Center for Personal Health Monitoring at UMass Amherst.
Ph.D., Computer Science, University of California, Los Angeles (2004), M.S., Computer Science, University of Southern California, Los Angeles (2000), B.Tech., Computer Science, Indian Institute of Technology, Madras (1998). During his PhD studies, he was part of the Center for Embedded Networked Sensing at UCLA, and interned at Intel Research at Berkeley and the Mobile Information and Communication Systems Center at EPFL. Professor Ganesan joined the faculty in the University of Massachusetts Amherst College of Information and Computer Sciences in 2004 as an Assistant Professor, and was promoted to Associate Professor in 2010.
Professor Ganesan received the NSF CAREER Award in 2006 and the IBM Faculty Award in 2008. He was selected as a UMass Junior Faculty Fellow in 2008, and a UMass Lilly Teaching Fellow in 2009. He was a Program co-chair for ACM SenSys 2010, IEEE SECON 2013, and co-founded the ACM HotWireless workshop in 2014. His recent work has been recognized by a Best Paper Award Runner-up at Mobicom 2014, a Best Paper Award at CHI 2013, and two honorable mentions at Ubicomp 2013.