Nico Wintergerst

Nico Wintergerst has a diverse work experience in various scientific and research roles. Nico worked at relayr as a Data Scientist from May 2020 to September 2020, then as an AI Team Lead from October 2020 to January 2021, and currently as a Staff AI Research Engineer since January 2021. Prior to that, they were a Postdoctoral Researcher at the Niels Bohr Institute, University of Copenhagen, from October 2017 to May 2020. Before that, they worked as a Postdoctoral Fellow at Stockholm University from November 2014 to September 2017, where they conducted research on dark matter, quantum field theory, and cosmology, utilizing both analytical and numerical simulations. Nico started their professional career as a PhD student in Theoretical Physics at LMU - Ludwig-Maximilians-Universität München in April 2010, working on their thesis titled "Faces of Gravity: From Classical Cosmology to Quantum Black Holes." During this time, they combined insights from gravity and atomic physics to contribute to the understanding of black hole physics by conducting complex hydrodynamical simulations of structure formation in cosmology, coding from scratch in C++.

Nico Wintergerst obtained their Diplom degree in Physics from Heidelberg University from 2003 to 2009. After that, they pursued a Doctor of Philosophy (PhD) in Theoretical Physics at Ludwig-Maximilians-Universität München from 2010 to 2014. Additionally, they have obtained multiple certifications, including the "Microsoft Certified: Azure Data Fundamentals" and "Microsoft Certified: Azure Data Scientist Associate" from Microsoft in 2022 and 2021 respectively. Nico Wintergerst has also completed several online courses, such as "Convolutional Neural Networks in TensorFlow," "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning," "Natural Language Processing in TensorFlow," "Sequences, Time Series and Prediction," "TensorFlow in Practice Specialization," "R Programming," "Convolutional Neural Networks," "Deep Learning Specialization," "Sequence Models," "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Neural Networks and Deep Learning," and "Structuring Machine Learning Projects" offered by Coursera in 2019 and 2020.