Veeravalli selected as IEEE SPS Distinguished Lecturer
ECE Professor Venugopal Varadachari Veeravalli has been selected as a 2010 Distinguished Lecturer from the IEEE Signal Processing Society. Veeravalli, who was nominated for the honor, will serve from January 1, 2010, until December 31, 2011.
Each chapter of the IEEE Signal Processing Society is given a budget to invite one of 10 distinguished lecturers to speak. As a distinguished lecturer, Veeravalli will travel to chapters all over the world to present one of five topics from his recent work in sensor networks and wireless communication.
“I think it’s going to be a lot of fun. I’m hoping to be invited by universities that I haven’t yet visited,” Veeravalli said.
Veeravalli said he expects to give a lecture approximately once every two months.
Information about his presentation, as well as the other IEEE SPS Distinguished Lecturers is available at the IEEE Signal Processing Society website. This site will contain sample presentation slides from Veeravalli’s presentations.
The following are overviews of Veeravalli’s presentations:
“Quickest change detection with distributed sensors and its applications”
The quickest change detection problem arises in applications such as surveillance, intrusion detection, and system monitoring. For example, quickest change detection procedures could be used to predict the onset of epilepsy attack in a patient, or to monitor cracks in a bridge to predict an impending faiure.
“Smart sleeping policies for inference in sensor networks”
This topic deals with designing sleeping policies to make a sensor network more energy efficient. Wireless sensors are set to sleep often to save their battery lives. Veeravalli is working on designing smart sleeping policies so sensors will come awake only when they are needed.
“Distributed regression and estimation in sensor networks”
This lecture discusses how information can be processed in a distributed manner in a sensor network towards the goal of estimating unknown parameters in the observations received by the sensors. For example, if there was a fire in an office building, sensors would collaborate to locate the heat source.
“Dynamic spectrum access with learning for cognitive radio”
Cognitive radio is a form of wireless communication, where a user of the wireless spectrum can detect which channels are being used by others and which ones are free, and transmit information on vacant channels while avoiding occupied ones. This lecture is on efficient dynamic detection algorithms for cognitive radio.
“Interference management in wireless networks”
Breaking the interference barrier is an important step in achieving higher throughput in wireless networks. This lecture is on new techniques for managing interference in wireless networks, including some recent rcsults from Veeravalli’s group on the capacity of two user interference channels, an information theory problem that has been open for more than 30 years.