Christian Buus Michelsen

With a background in physics, I have a strong technical foundation in machine learning, applied data science, and mathematical modelling. During my Ph.D., at the Statens Serum Institut during the beginning of the COVID lockdown, and now as a Senior ML Engineer at TICRA, I have further strengthened my multidisciplinary problem-solving skills, including multiobjective and constrained optimization, developing and deploying ML methods in Python and Fortran, and building robust CI/CD infrastructure. I have practiced working in extremely high-performance environments with tight deadlines and a requirement for strong project management skills.

Senior ML Engineer TICRA, Copenhagen

2024 – Present

• Designed Bayesian Optimization methods for multiple and constrained objectives in Python and implemented them in Fortran production code.
• Established GitLab-based CI/CD infrastructure, including runners and automated testing and deployment pipelines.

Data Scientist Halfspace, Copenhagen

2022 – 2024

• Developed a Bayesian neural network to utilize uncertainties in forecasting and dynamic pricing models to reduce business risks; an Edelman Award winning project and 5x gold at Danish Digital Awards.
• Accelerated Better Collective’s football line-up building tool 16.6x using advanced methods from operations research (OR).
• Implemented bespoke GenAI solutions, including the use of RAGs and fine tuning LLMs, for multiple companies and NGOs.

Ph.D. student University of Copenhagen

2018 – 2022

• Developed statistical software in the field of ancient genomics using modern statistical methods, which led to frontpage in Nature.
• Used machine learning models to reduce the risk of being readmitted after a knee or hip operation.
• Applied deep learning techniques to classify ancient vs. modern DNA.
• Used Bayesian inference to estimate the size of loci in diffusion processes.

Researcher Statens Serum Institut, SSI

2020 – 2021

• Developed an agent-based model to predict the spread of COVID-19 as part of “Ekspertgruppen for matematiske modelberegninger” at SSI.
• Optimized the model to simulate the entire Danish population (5.8 million).

Science Educator Sorø Akademi / Astra

2019 – Present

• Interactive presentation of statistics and machine learning to high schoolers.

Exchange Program SISSA, Trieste, Italy

2021 – 2022

• Ph.D. exchange program at the International School for Advanced Studies.
• Worked with Professor Guido Sanguinetti, head of the Machine Learning and Systems Biology group at SISSA.

Master of Science in Physics University of Copenhagen, Denmark

2016 – 2020

• Applied machine learning methods to particle physics data from CERN.
• Attended the CERN School of Computing in Tel Aviv, Israel, in 2018. This is a two-week programme focused on advanced topics of scientific computing.
• Studied at University of Canterbury, New Zealand, from 2016-2017.

Bachelor of Science in Physics University of Copenhagen, Denmark

2013 – 2016

• Performed a Bayesian analysis of the radial velocities from stars orbiting black holes to quantify their general relativistic effects.

Board member Danish Data Science Community (DDSC)

2024 – Present

• Organize Data Science-related events in Denmark.

Main Organizer Julia Meetup

2022 – Present

• Initialised and organized Julia meetups in Copenhagen.

Judge Young Scientists competition (Unge Forskere)

2021 – 2022

• Evaluated and judged young students at the Unge Forskere competition.

In my spare time, I am a professional wedding photographer and outdoor enthusiast. When I am not kayaking at sea, hiking in the mountains or enjoying nature with my wife and two kids, I relax by editing the pictures from my travels or watching a new series on our couch in Holte.