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Rahul Chandnani has a diverse work experience in the field of machine learning and data science. Rahul started their career as a Software Engineer at Ovrlod from March 2015 to August 2016, where they worked on CMS-based web development and custom web applications. Following this, they interned as a Machine Learning Research Intern at the Laboratory Hubert Curien from March 2017 to June 2017, focusing on machine learning problems involving sequential and unbalanced data.

In 2018, Rahul joined Worldline Global as a Machine Learning Research Intern for their Master's thesis, where they reviewed techniques to overcome Catastrophic Forgetting in Continuous Learning and adapted those techniques in a boosting setting. Later that year, they also joined Teraki GmbH as a Data Scientist from November 2018 to March 2023.

Their current role, starting in 2023, is as a Machine Learning/Deep Learning Researcher at Diametos GmbH. The exact duration of their role at Diametos GmbH is not provided. Overall, Rahul has demonstrated expertise in machine learning research and data science throughout their career.

Rahul Chandnani completed their Bachelor of Engineering (BE) in Computer and Information System Engineering from NED University of Engineering and Technology, where they studied from 2011 to 2014. Following this, they proceeded to pursue a Master's degree in Machine Learning and Data Mining (MLDM) from Université Jean Monnet Saint-Etienne from 2016 to 2018. In addition to their formal education, Rahul obtained certifications in "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" and "Neural Networks and Deep Learning" from Coursera in May 2018 and April 2018 respectively.