Nirmal Rai, Ph.D. has held various roles throughout their career. Nirmal started out as a Graduate Research Assistant at The University of Iowa from 2010 to 2015. Afterward, they worked as a Research Scientist at IIHR-Hydroscience & Engineering from 2015 to 2020, where they developed machine learning frameworks and computational mechanics platforms for modeling materials under supersonic flow conditions. Nirmal also served as a Postdoctoral Research Scholar at IIHR-Hydroscience & Engineering from 2015 to 2016, focusing on multi-physics modeling and uncertainty quantification of shock-induced chemical reactions.
Following their time at IIHR-Hydroscience & Engineering, Dr. Rai joined Los Alamos National Laboratory as a Computational Physicist (Director's Fellow) in 2020. There, they designed a machine learning-based multi-scale modeling framework for explosives and developed novel machine learning-based surrogates for micro-structural explosives formulations.
Currently, Dr. Rai works at VIZIO as an Applied Engineering Research & Data Scientist since 2021. Nirmal'smain responsibilities involve developing a large scale A/B testing platform and researching innovative approaches to enhance VIZIO's core data technology feature related to automated content recognition.
Nirmal Rai, Ph.D., completed their education in a chronological manner. Nirmal obtained their Doctor of Philosophy (Ph.D.) degree in Mechanical Engineering from the University of Iowa between 2010 and 2015. Prior to that, from 2005 to 2009, they pursued their Bachelor of Technology (BTech) in Production Engineering from the National Institute of Technology Calicut.
In addition to their formal education, Nirmal Rai has also obtained certifications in the field of neural networks and deep learning. In August 2020, they completed the course "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" from Coursera. Furthermore, they also completed the course "Neural Networks and Deep Learning" from Coursera in June 2020.
December, 2021 - present