Prof. Mrityunjoy Chakraborty has done FNASc, FNAE and is the INAE Chair Professor (2019-2021), He is the Professor in Electronics and Electrical Communication Engineering from the Indian Institute of Technology Kharagpur . He joined the Institute in 2005 as a Lecturer.
He Compleated his graduation from Jadavpur University and Masters from IIT Kanpur and PhD from the IIT Delhi.
The research interests of Prof. Chakraborty include Digital and Adaptive Signal Processing, VLSI Signal Processing, Compressive Sensing, Applied Linear Algebra and DSP applications to communications, speech and audio processing. The major contributions made by him in these are as follows :
A. He has been the first to show how the block floating point (BFP) data format which provides floating-point like high dynamic range at fixed-point like low complexity, can be used for realizing adaptive filters. This is a major breakthrough, as before this, the usage of BFP was limited only to fixed coefficient filters.
B. He made a seminal theoretical contribution by showing that for multitonal signals, the filter weights in LMS-based adaptive filters can actually converge to their optimal values absolutely and not just in mean unlike for general signals.
C. In compressive sensing (CS), he developed new upper bound relations for convergence of the generalized orthogonal matching pursuit. Recently, he has determined iteration bounds for convergence of two important CS recovery algorithms, namely, CoSaMP and subspace pursuit.
D. He has been the first to introduce CORDIC and also canonic-signed-digit format to reduce multiplicative complexities substantially in adaptive filters.
E. His latest contributions include development of novel sparse adaptive filters based on convex combination and L1 norm regularization principles.
Apart from the above, his other contributions include development of novel adaptive filters for estimating and tracking the delay of sinusoids for applications in radar and sonar, pipelined architectures for adaptive decision feedback equalizers, new algorithms for multichannel ARMA modeling and filtering, and fast algorithms for cyclostationary processes.