Master’s student in Artificial Intelligence at the Norwegian University of Science and Technology (NTNU), currently on exchange at UC Berkeley, with a B.Sc. in Computer Science. My work centers on machine learning, bio-inspired optimization, and decision-making under uncertainty, with a particular interest in finance. I spent the summer of 2026 as the sole machine learning developer on a data-quality product at Aize, and I built an equity selection system that has been trading live since June 2026. My master’s thesis explores bio-inspired artificial intelligence for portfolio optimization under uncertainty. Having lived 13 years in Canada, the United States, and the United Arab Emirates, I have developed strong cross-cultural communication skills and native fluency in English and Norwegian.
M.Sc. in Artificial Intelligence 2025–2027
Norwegian University of Science and Technology (NTNU)
Exchange semester at the University of California, Berkeley, fall 2026
Prospective thesis: bio-inspired artificial intelligence for portfolio optimization under uncertainty
B.Sc. in Computer Science 2022–2025
Norwegian University of Science and Technology (NTNU)
Thesis: real-time motion capture and calibration for adaptive Parkinson’s disease gameplay
Software Engineer Summer Intern, June 2026 – August 2026
Aize, Oslo
Sole machine learning developer on a data-quality application built over large-scale oil and gas asset data. I built a semi-supervised datatype classifier using teacher-student self-training, and an unsupervised model that infers which attributes an asset should have from its metadata. Both were integrated into existing Databricks pipelines. The datasets contained very few usable labels, which shaped the architectural choices throughout.
Master’s: Introduction to Machine Learning, Bio-Inspired Artificial Intelligence, Artificial Intelligence Methods, Introduction to Artificial Intelligence
Bachelor’s: Statistics, Mathematical Methods 1–3, Applied Machine Learning, Algorithms and Data Structures
Programming: Python, Rust, Java, C#, SQL
Machine Learning: supervised regression and classification, semi-supervised learning, teacher-student self-training, clustering and mixture models, neural networks, feature engineering, walk-forward and cross-validation
Mathematics and Optimization: probability and statistical inference, linear algebra, numerical methods, constrained, combinatorial, and multi-objective optimization, evolutionary, memetic, and swarm algorithms
Infrastructure: Git, Linux, AWS, Databricks, Alpaca API, self-hosted deployment
Norwegian Native
English Native
Spanish A2
German A2
You can view the full CV here.
