Rasmus Halvgaard

Rasmus Halvgaard has a diverse work experience in the field of data science and research. Rasmus is currently employed as a Lead Data Scientist at Topsoe since 2022. Prior to this, they worked at Computas Danmark as a Senior Data Scientist from 2021 to 2022, where they assisted multiple organizations in making their data valuable. Rasmus'sexpertise ranged from fraud detection to Natural Language Processing.

Rasmus also has experience working at DHI, where they were an R&D Scientist in the Department of Emerging Technologies from 2016 to 2021. Rasmus played a significant role in implementing data-driven Machine Learning algorithms for water systems through research projects and client case studies. Rasmus contributed to the development of an Operational Model Predictive Control strategy to minimize overflows and optimize drinking water distribution in the city of Aarhus.

Furthermore, Rasmus worked as an Industrial Postdoc at the Technical University of Denmark and Krüger A/S from 2014 to 2016, where they implemented Smart Grid solutions in waste water systems using Model Predictive Control. During this time, they also spent a research stint at the University of California, Los Angeles, collaborating with Professor Lieven Vandenberghe on large-scale convex optimization algorithms for Smart Grids.

Earlier in their career, Rasmus served as a Teaching Assistant at the Technical University of Denmark from 2007 to 2010, where they assisted students in courses related to linear control design and digital signal processor programming. Rasmus also gained practical experience as an Electronics Developer at Prevas AB, a prominent electronics consultancy company, and as a Trainee at EADS Astrium, Europe's largest space company.

Overall, Rasmus Halvgaard has a strong background in data science, research, and innovation, with expertise in applying Machine Learning algorithms, developing operational strategies for water systems, and implementing Smart Grid solutions.

Rasmus Halvgaard has an extensive education history. Rasmus obtained a Doctor of Philosophy (PhD) in Applied Mathematics from DTU - Technical University of Denmark from 2010 to 2014. Prior to that, they completed a Master of Science (MSc) in Electrical Engineering from DTU - Technical University of Denmark from 2008 to 2010, and a Bachelor of Science (BSc) in Electrical Engineering from 2004 to 2007, also at DTU - Technical University of Denmark. Rasmus Halvgaard attended Espergærde Gymnasium from 2000 to 2003, where they completed their high school education, focusing on Mathematics, Physics, and IT.

Rasmus Halvgaard has also obtained various additional certifications throughout their career. Rasmus acquired a Professional Machine Learning Engineer certification from Google Cloud in July 2022. Rasmus also completed the How to Fix Bad Agile certification from LinkedIn in 2022. In 2019, Rasmus Halvgaard attended several training courses including the Open Data Science Conference (ODSC) Europe 2019, Convolutional Neural Networks in TensorFlow from Coursera, Python 3 from SoloLearn, Encapsulation and SOLID (C# object-oriented coding) from Pluralsight, and Scrum Master Fundamentals from Pluralsight. Additionally, they completed courses in C# programming, clean code writing, design patterns in C# and .NET, and git operations from various online platforms like Udemy and Pluralsight. Furthermore, Rasmus Halvgaard has completed courses in deep learning, machine learning, learning strategies, R programming, and writing in the sciences from renowned institutions such as DTU - Technical University of Denmark, Coursera, and Stanford University. In 2021, they obtained a Professional Google Cloud Data Engineer certification from Google.