Alex Dimakis (UT Austin)
Title: Coding Theory for Large-Scale Storage
Modern distributed storage systems are deploying coding techniques to introduce high reliability with limited storage overhead. It was recently discovered that network coding techniques can improve the maintenance (rebuild) properties of such distributed coded systems compared to standard Reed-Solomon codes. We will cover the developing theory and practice of distributed storage codes. We will focus on recent developments and connections to locally decodable codes. Finally, we will discuss recent implementations running over Hadoop.
Alex Dimakis is an Assistant Professor at the Electrical and Computer Engineering department, University of Texas at Austin. From 2009 until 2012 he was with the Viterbi School of Engineering, University of Southern California. He received his Ph.D. in 2008 and M.S. degree in 2005 in electrical engineering and computer sciences from UC Berkeley and the Diploma degree from the National Technical University of Athens in 2003. During 2009 he was a CMI postdoctoral scholar at Caltech. He received an NSF Career award in 2011, a Google faculty research award in 2012 and the Eli Jury dissertation award in 2008. He is the co-recipient of several best paper awards including the joint Information Theory and Communications Society Best Paper Award in 2012. He is currently serving as an associate editor for IEEE Signal Processing letters.
His research interests include information theory, signal processing, and networking, with a current focus on distributed storage and machine learning algorithms.