About

Mayank Sharma is a professional with 7 years of experience in the field of Computer Vision and Machine Learning for Natural Language Processing (NLP). He is currently working as a Computer Vision Lead at Wobot, where he is responsible for developing edge computer vision algorithms and neural model compression/optimization for edge devices. Mayank is skilled in Python, Keras, Theano, Object-Oriented Programming, Bayesian Machine Learning, PyTorch, Logistic Regression, Linear Regression, Linear Algebra, Probability & Statistics, and TensorFlow. He is also familiar with full-stack development using the MEAN stack and beginner-level programming using C and Rust. In his previous role as Lead Machine Learning at Loconav, Mayank led the efforts for the ML team and worked on neural network model compression, including quantization and pruning, to enable them to run on low-end devices. He also came up with a multitask learning architecture for multiple ADAS tasks and built DMS modules for driver assistance. Prior to that, he worked as Lead Machine Learning at Bytelearn.com. Mayank holds a Bachelor of Engineering (Hons) degree in Chemical Engineering from Birla Institute of Technology and Science, Pilani, and a Masters degree in Computer Science from The University of Texas at Austin. His technical skills include Computer Vision, ML, NLP, Deep Learning, Python, PyTorch, Keras, OpenCV, TensorFlow, AI, Software Engineer, Neural Networks, Research Scientist, MongoDB, Javascript, Data Scientist, Kafka, Backend, and Senior Software Engineer. Mayank has a relevant experience of 6.78 years.