I am currently employed at Advanced Micro Devices, Inc. as a Member of Technical Staff (MTS), where I focus on developing scalable, robust kernels for Generative AI models optimized for AMD's AI Engine Block. Previously, I have worked at Qualcomm AI Research as a Senior ML Engineer and Amazon Lab126 Hardware Compute Group as a SysDE ML Compiler Engineer. I graduated with two research focussed masters from University of Southern California in 2020 and an integrated dual degree from Indian Institute of Technology, Kharagpur in 2017. At present, I am concurrently finishing up my doctorate from University of Texas, Austin where my research focus is designing energy-efficient, robust, machine learning algorithms for generative AI edge applications.
I have a pet cat, Oliver. He is quite chonky 😄 and a very good boy. Check out his 
- Built the compiler stack that enabled seamless low-latency, high-throughput generative AI inference on the edge.
- Optimizing the software stack of inference devices that ensures AI computations on the edge while maininting throughput and reducing latency, eg. processing voice commands on device.
- Algorithms and architecture co-design for AI accelerators focussed towards training/inference with lesser compute/energy budget. Published a paper in ICASSP 2020.
