Abstract: In this talk, we describe two very different applications of Information and Coding Theory. The first is Wireless Packet Networks, where we turn collisions into opportunities by treating the received analog signal as a linear combination of the collided packets. These linear equations can then be used to greatly improve the network throughput in future phases of communications. We describe how the benefits of this approach depend on the delay in learning the channel state and on the spatial correlation of the communication links.
The second is Computer Memory Systems, where scaling down the feature size requires new coding strategies to prevent significant degradation to the lifetime of memory. We develop a new interface that acts as a bridge between theory and practice, making it possible to introduce coding schemes that extend the lifetime of Flash Memory. We derive a fundamental tradeoff between host-visible capacity and lifetime, and describe several operating points.
Bio: Alireza Vahid received his B.Sc. in Electrical Engineering from Sharif University of Technology, Iran. He obtained his M.Sc. and Ph.D. from the School of Electrical and Computer Engineering, Cornell University in 2012 and 2015 respectively, where he worked with Professor Salman Avestimehr. He is currently a Postdoctoral Fellow at Duke University, where he works with Professor Robert Calderbank. His research interests include Information and Coding Theory, Wireless Communications, Computer Architecture, and Memory Systems.
He received the Outstanding PhD Thesis Research Award in 2015, and the Director's Ph.D. Teaching Award in 2010 from Cornell University. He was the recipient of the Qualcomm Innovation Award in 2013, and the Jacobs Scholar Fellowship in 2009. He was ranked 2nd in the Iranian National Entrance Exam, and received the Silver Medal in the Iranian National Physics Olympiad.