Nishit Kumar

Nishit Kumar has a long and varied work experience in the field of machine learning and AI. Nishit is currently working as the Engineering Lead, Machine Learning and AI at Informed.IQ since 2021. Prior to this, they worked at June (acquired by Weber-Stephen Products LLC) as a Software Engineer - Machine Intelligence from 2018-2021, where they co-developed and improved June's flagship Food Recognition features of June oven. From 2017-2018, they were a Senior Software Engineer - Computer Vision and Machine Learning at Automation Anywhere, where they developed a CNN/RNN model for image-to-text application with the performance goal of exceeding "human-level" accuracy. From 2016-2017, they worked as a Software Engineer - Computer Vision and Machine Learning at Innit. From 2007-2016, they worked as the Director of Engineering at SiBEAM, Inc. where they led a team of 25+ engineers providing technical mentorship, product and project directions, and delivered multiple generations of ICs. Finally, from 1997-2007, they worked as a Principal Engineer at Zoran, where they implemented and verified numerous sub-systems inside digital TV ICs that implemented a variety of audio, video, and graphics algorithms.

Nishit Kumar's education history includes a Bachelor's degree in Computer Science from the Indian Institute of Technology, Bombay from 1985 to 1989, a Master's degree in Computer Science from the Indian Institute of Technology, Kanpur from 1990 to 1992, and a Ph.D. in Computer Science from the University of Central Florida from 1992 to 1997. Kumar also holds numerous certifications from Coursera and Udemy, including Sequence Models, Convolution Neural Networks, Structuring Machine Learning Projects, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Neural Networks and Deep Learning, Neural Networks for Machine Learning, Python for Data Science and Machine Learning Bootcamp, Introduction to Computer Vision, Deep Learning and TensorFlow, Heterogeneous Parallel Programming, Graph Analytics for Big Data, Hadoop Platform and Application Framework, Introduction to Big Data Analytics, Machine Learning With Big Data, Introduction to Big Data, and Machine Learning.