I am currently working in the Deep Learning- Algorithms and Infrastructure group at IBM Research -India. In particular, I am looking at efficient methods of compression of deep neural models from different domains (like images, videos and text) so as to reduce the inference time and memory footprint. This will enable complex models to be run efficiently on low resource systems like mobile/edge devices, or in shared enviroments like cloud.
Prior to this, I worked in the High Performance Computing group. The work mainly involved optimization and parallelization of different scientific applications on massively parallel architectures. Some of the projects on which I contributed include designing kernels for applications for the Exascale architecture, optimization of Graph500 and HPCC benchmarks (in particular RandomAccess) on Blue Gene/Q, parallelization of financial engineering applications and computational nanotechnology applications on clusters and distributed systems.
I am a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology, Delhi (IITD). My supervisors were Prof. Naveen Garg and Prof. Amit Kumar, and my thesis was in approximation algorithms for job scheduling problems. Prior to that, I completed my B.E. from Jadavpur University, Kolkata and my MTech. from Indian Institute of Technology, Kanpur (IITK). My master's thesis was in the area of formal languages.