About

Snehil Verma is a highly skilled Deep Learning Hardware Acceleration Engineer at Apple, with a strong background in Electrical and Computer Engineering. He is currently pursuing his M.Sc. in Electrical & Computer Engineering from the University of Texas at Austin, under the guidance of Prof. Lizy K. John, and is affiliated with the Laboratory for Computer Architecture (LCA). Snehil's research primarily focuses on Computer Architecture, with a specific emphasis on performance evaluation of Machine Learning workloads. He is an accomplished researcher, having proposed a new metric for benchmarking ML workloads from the perspective of comparing training hardware, conducted an extensive study on the impact of hardware infrastructure choices on deep learning performance for training, and analyzed and characterized the MLPerf [v0.5] training benchmark suite exposing various system-level trends. Snehil completed his bachelor's degree in Electrical Engineering from the prestigious Indian Institute of Technology Kanpur in 2014. During his academic career, he also served as a Graduate Research Assistant at the Cockrell School of Engineering, the University of Texas at Austin, where he was advised by Prof. Lizy K. John and affiliated with the Laboratory for Computer Architecture (LCA). He also served as a Graduate Teaching Assistant for EE382V - Hardware Architectures for Machine Learning, taught by Prof. Lizy K. John. Snehil's technical expertise is extensive, with a strong focus on Deep Learning, Machine Learning, Research Science, Artificial Intelligence, and Mobile. He has 3.20 years of relevant experience and is an accomplished researcher with a passion for exploring new technologies and experimenting with cutting-edge hardware and software. Overall, Snehil is a highly skilled and motivated professional who is committed to delivering high-quality results and driving innovation in the field of Computer Architecture.