About

Nageshwar Singh is an ambitious and results-oriented software engineering professional with a keen interest in signal processing, processor architecture, deep learning, and neural networks. He has a proven track record of thriving in small budget and start-up environments and is a continuous learner. Nageshwar has over 6 years of relevant experience in the field and is currently working as an Engineer at Cerebras Systems. Nageshwar's experience includes development of deep learning and image processing kernels for performance-intensive processors such as DSP and vector processors. He has also worked on assembly and intrinsic programming, including SIMD and VLIW. Additionally, Nageshwar has experience in developing C# and C++ based desktop software, including WPF, Crystal Report, and SQL. He has also worked on TI's TDA2xx board bring-up with 4 x AR12xx radar module for multi-mode radar systems and developed active noise cancellation (ANC) systems, specifically on modeling the secondary path on DSP board (TI C6713) and Matlab. Nageshwar is enthusiastic about machine learning and deep learning, algorithms, digital signal processing for audio, image, and video processing, digital communication systems, and web technologies. He has previously worked as a Software Engineer II at AMD and as a Senior Software Engineer at Pathpartner Technology, where he developed deep learning inference and training kernels on Tensor Processing Unit (GPU like highly vectorized processor), intrinsic vector programming with C++ reference implementation using native C++ framework for linking the kernels, and optimized radar algorithms on VLIW-8 DSP C66xx and linear assembly optimizations. Nageshwar holds a Master of Technology (M.Tech.) degree in Digital Electronics and Advance Communication from Manipal Institute of Technology and a Bachelor of Engineering (B.E.) degree in Electronics and Communications Engineering from Gujarat Technological University. He completed his HSC and SSC from Delhi Public School - Ahmedabad. Nageshwar's tech stack includes software engineering, deep learning, SQL, image processing, machine learning, neural networks, web technologies, artificial intelligence, CNN, normalization, and testing.