Krishna Narayanan

Research - My research interests are in the application of information theory, coding theory and signal processing for building reliable communication networks and reliable storage systems in the presence of unreliable channels, components or physical media. I am interested both in the theoretical and applied aspects of research in this area. Some of our recent research has applications in 5G wireless communications, data science, data storage, and high-speed fiber-optic communications. A high level description of some of my current projects is available here.

My current research projects include - (i) design of novel uncoordinated massive multiple access paradigms for 5G wireless communications and the Internet of Things, (ii) ML based design of communication systems (joint source-channel coding, revisiting non-linear estimation problems in communications through the lens of machine learning) (iii) signal processing for big data - exploring connections between sparse signal recovery and coding theory, fast algorithms for sparse recovery in high-dimensional spaces, Group testing for COVID detection (iv) analyzing graph structured data - graph neural networks, (v) coded distributed computing. My research has been funded through many external research grants, several of them from the National Science Foundation. Our research group's web page will give detailed information about my research interests, sponsors, students, collaborators, publications, preprints and recent presentations. Please visit our research page.

Teaching - During Spring 2021, I am teaching a graduate course on Advanced Wireless Communications. Recently, I have taught courses on Mathematical methods in Signal Processing, Probabilistic Graphical Models Probabilistic graphical models and Applied Data Science. In the past, I have taught graduate and undergraduate level courses on digital communications, signals and systems, digital signal processing, both basic and advanced channel coding, information theory and wireless communications. I enjoy interacting with students both in the class room and in our research group. I have been an early adopter of the flipped style of teaching. My personal thoughts and statement about teaching can be found here.

Service - I served as an Associate Editor for Coding Techniques for the IEEE Transactions on Information Theory from 2017-2019 and as one of the technical program co-chairs for the 2018 IEEE Information Theory Workshop. I have also been elected to the board of governors of the Information Theory Society to serve from 2016-2018. I served as the area editor for the coding theory and applications area of the IEEE transactions on communications until 2012 and I was one of the Technical program chairs for the 2010 IEEE International Symposium on Information Theory (ISIT 2010)that was recently held in Austin, Texas. I have served on the editorial board of the IEEE Transactions on Wireless Communications and the IEEE Communications Letters. I have been on the technical program committee for several conferences in the past. At Texas A&M University, I served as the Director of Graduate Studies in the ECEN department from 2012-2014.

Selected Honors- I was the recipient of the 2001 National Science Foundation career award, the 2022 Joint Communications Society and Information Theory society paper award, the 2006 and 2020 best paper awards from the IEEE data storage technical committee within COMSOC, the Association of Former Students college-level teaching award at Texas A&M University and the 2014 Professional Progress in Engineering award from the Iowa State University given to an outstanding alumnus under the age of 46 each year. I also received the Dean's excellence award from the College of Engineering and the outstanding professor in the ECE department awards in 2015. In 2016, I gave a keynote lecture at the ICC workshop on massive uncoordinated multiple access and I was one of the lecturers at the North American School on Information Theory, Australian School on Information Theory and the East Asian School on Information Theory. I was elected Fellow of the IEEE for contributions to coding theory and its applications to wireless communications and data storage.

Recent News

• June 2022 - Received the 2022 Joint Communications Society and Information Theory Society paper award for our paper - Vamsi K. Amalladinne, Jean-Francois Chamberland, and Krishna R. Narayanan, "A Coded Compressed Sensing Scheme for Unsourced Multiple Access," IEEE Transactions on Information Theory, vol. 66, no. 10, pp. 6509-6533, October 2020.
• May 2022 - I have taken a new responsibility as the Associate Director for Educational Initiatives at Texas A&M Institute for Data Science (TAMIDS)
• May 2022 - NSF RINGS grant on Resilient Wireless Systems for Future Uplink Traffic through Cell Free, Loosely Coordinated Access
• Aug 2021 - New NSF grant on Unsourced Random Access and Inference in Large Dimensional Spaces with J.-F. Chamberland and Y. Polyanksiy
• July 2021 - Presented a tutorial at ISIT on Unsourced Random Access - Information Theory and Coding
• June 2020 - NSF award on Codes for Numerically-Stable Large-Scale Distributed Computing
• May 2020 - NSF RAPID award on Group Testing for COVID Detection
• Received of the 2020 Data Storage Best Paper award from IEEE Comsoc for our paper D. Kim, K.R. Narayanan, and J. Ha, “Symmetric Block-wise Concatenated BCH Codes for NAND Flash Memories,” published in IEEE Transactions on Communications, October 2018