Chris Wegg

Senior Machine Learning Engineer @ Cape Analytics

About Chris Wegg

Chris Wegg is a Senior Machine Learning Engineer at CAPE Analytics in Munich, Germany, where he has worked since 2021. He holds a PhD in Physics from Caltech and has previously held research positions at the Max Planck Institute for Extraterrestrial Physics and CNRS.

Work at Cape Analytics

Chris Wegg has been employed at CAPE Analytics since 2021 as a Senior Machine Learning Engineer. In this role, he contributes to the development and implementation of machine learning models that enhance the company's capabilities in data analysis and predictive modeling. His work is based in Munich, Bavaria, Germany, where he applies his extensive knowledge in physics and machine learning to drive innovation within the organization.

Education and Expertise

Chris Wegg holds a Doctor of Philosophy (PhD) in Physics from Caltech. He also earned a Master of Science (MSci) in Physics from University College London (UCL). His educational background provides a strong foundation in analytical thinking and complex problem-solving, which are essential skills in the field of machine learning and data science.

Background

Before joining CAPE Analytics, Chris Wegg worked at the Max Planck Institute for Extraterrestrial Physics as a Postdoctoral Researcher from 2012 to 2020. During this eight-year tenure, he engaged in advanced research projects that contributed to the understanding of astrophysical phenomena. Additionally, he served as a Marie Curie Fellow at CNRS in Nice, France, from 2018 to 2020, further expanding his research experience in a collaborative international environment.

Professional Experience

Chris Wegg has accumulated significant professional experience in the field of physics and machine learning. His roles at prestigious institutions such as the Max Planck Institute and CNRS demonstrate his commitment to research and development. His experience as a Senior Machine Learning Engineer at CAPE Analytics allows him to leverage his background in physics to solve complex problems in data analytics and machine learning.

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