Dr. Neelesh B Mehta (Indian Institute of Science, Bangalore) Speaker Bio: Neelesh B. Mehta received his B. Tech degree in Electronics and Communications Engineering from the Indian Institute of Technology (IIT) Madras, in 1996, and M.S. and Ph.D. degrees in Electrical Engineering from the California Institute of Technology, Pasadena, USA, in 1997 and 2001, respectively. He is an Associate Professor in the Department of Electrical Communication Engineering at the Indian Institute of Science (IISc), Bangalore. Prior to joining IISc, he served as a research scientist in USA from 2001 to 2007 in AT&T Research Labs, Broadcom Corporation, and Mitsubishi Electric Research Labs (MERL). His research focuses on wireless communications. He has worked on topics related to cellular communication standards, energy harvesting and green wireless sensor networks, cognitive radio, cooperative communications, multiantenna technologies, and multiple access protocols. He currently serves as a Member-at-Large on the Board of Governors of the IEEE Communications Society. He served as the Director of Conference Publications on the board during 2012-13. He is a Fellow of the Indian National Academy of Engineering (INAE) and the National Academy of Sciences India (NASI). He is also a recipient of the NASI-Scopus Young Scientist award and the INAE Young Engineer award. He serves as an editor of the IEEE Transactions on Communications AND IEEE Wireless Communication Letters, and an Executive Editor of the IEEE Transactions on Wireless Communications. Title: Max Function Computation in Green Energy Harvesting Wireless Sensor Networks Abstract: Wireless sensor networks find applications in surveillance, health, home automation, environmental and industrial monitoring. Two aspects make the design of these networks different and challenging. Firstly, sensor networks are evaluated by the efficacy with which they sense and aggregate data about the parameters of interest, and not by the amount of data they transport. Secondly, their design needs to be energy-efficient in order to ensure a long lifetime of operation. We study the problem of max function computation in energy harvesting wireless sensor networks, and analyze how the above two aspects drive network design. In these networks, the sensor nodes harvest green renewable energy from the environment for their sensing, processing, and communication tasks. While energy harvesting promises perpetual lifetime, it also leads to several new design trade-offs due to the random and the sporadic nature of the energy harvested by the nodes. Specifically, for a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in estimation cycle, we analyze the mean of the absolute error between the maximum sensor reading and that estimated by the network. We optimize the transmit power, the number of scheduled nodes per cycle, and quantization. We also highlight the crucial role of channel state information and the energy cost of acquiring it on system design. We also briefly discuss how novel multiple access-based opportunistic selection algorithms can significantly enhance the energy efficiency and rate of data aggregation in multi-hop sensor networks.