Sunita Gopal

Sunita Gopal has a diverse range of work experiences in the field of deep learning and data science. Their most recent position was as a Deep Learning Engineer at Flux Auto, starting in August 2022. Prior to that, they worked as a Data Scientist at aiConomix from July 2021 to December 2021.

Before joining aiConomix, Sunita gained practical experience as a Deep Learning working student at Tarsier from November 2019 to October 2020. In this role, they designed a real-time system for detecting static objects in drone detection videos and developed a system to evaluate the performance of drone detection models under various environmental conditions.

During their time at the Technical University of Munich, Sunita completed their Master's Thesis, focusing on diverse multi-modal medical image synthesis using GANs. Sunita successfully designed a generative adversarial network capable of homogenizing MRI images from different scanners and handling multi-modal MRI data. Their results outperformed other state-of-the-art methods in preserving structural and pathological information while reducing noise.

Additionally, Sunita worked as a Working Student Machine Learning at Linde from June 2019 to October 2019, and as a Student at the Technical University of Munich ROBOY from October 2018 to February 2019.

Sunita Gopal has pursued their education in a chronological pattern. Between 2013 and 2017, they attended Sir M Visvesvaraya Institute Of Technology, where they completed their Bachelor's degree. Following this, they enrolled at the Technical University of Munich in 2017, where they are currently studying for their Master's degree in Informatics.