Rate My Professor Deepak Ganesan

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, with a focus on ultra-low power wireless communication, novel platforms and algorithms for mobile and wearable health sensing, and learning on multi-modal sensor data. His projects include smart textiles, smart eyeglasses, backscatter communication, and detection of health signals such as drug use, smoking, overeating, and eye movements using low-power eye trackers and textile sensors. He has received the ACM Fellowship in 2021, NSF CAREER Award in 2006, IBM Faculty Award in 2008, UMass Junior Faculty Fellow in 2008, UMass Lilly Teaching Fellow in 2009, Best Paper Award at CHI 2013, Best Paper Runner-up at MobiCom 2014, and two Honorable Mentions at Ubicomp 2013. Key publications include "EkhoNet: High Speed Ultra Low-power Backscatter" (MobiCom 2014), "Textile Sensor Arrays for Fine-grained Interaction Detection" (MobiSys 2022), "Low-latency Speculative Inference" (MobiSys 2021), "Polymorphic Radios: Active-Passive Radios for Ultra-low Power Communication" (SIGCOMM 2018), and "PRESTO: Feedback-Driven Data Management in Sensor Networks" (NSDI 2006). Ganesan has served as program co-chair for ACM SenSys 2010 and IEEE SECON 2013.