Rajat Mani Thomas

Rajat Mani Thomas has a diverse work experience spanning several industries and roles. Rajat Mani is currently working as an A.I. lead at Serket, where they lead a team focused on delivering video analytics solutions for livestock monitoring and other agro-tech markets. In 2022, they also served as a Technology Advisor at Reset Technologies BV.

Prior to that, Rajat held the role of Research Assistant Professor at AMC - Academic Medical Center starting from 2019. Rajat Mani also co-founded and served as CEO of Spectrum AI from 2020 to 2022.

Rajat's previous roles include being a Deep Learning engineer at Machine2Learn from 2019 until 2022. Rajat Mani worked as a Deep Learning Scientist at AMC Medical Research BV from 2016 to 2019, focusing on deep learning for large-scale medical image processing and network analysis.

Rajat also gained experience in the field of Artificial Intelligence through their role as an Artificial Intelligence Researcher at NASA - National Aeronautics and Space Administration in 2018, where they worked with a team on reviving a failed instrument on a NASA satellite using Deep Learning techniques.

Prior to that, Rajat worked as a Researcher at Netherlands Institute for Neuroscience from 2011 to 2016. Rajat Mani also served as a Postdoctoral Researcher at Canadian Institute for Theoretical Astrophysics from 2010 to 2012 and as a Visiting Researcher at Tokyo University of Science from 2009 to 2010.

Rajat Mani Thomas earned a PhD in Astrophysics from the University of Groningen from 2005 to 2009. Prior to that, they completed their Masters in Radio Astronomy and Space Science at Chalmers University of Technology from 2003 to 2005. Rajat Mani obtained a Bachelor's degree in Electronics and Communication from Visvesvaraya Technological University from 1999 to 2003. Rajat completed their high school education at Kendriya Vidyalaya from 1987 to 1999, specializing in Physics, Chemistry, Maths, and Computer Science. Additionally, they hold an edX Verified Certificate for Computational Probability and Inference from an unspecified date.