Bio

I am a final-year MSc student in Industrial Mathematics at the Norwegian University of Science and Technology (NTNU). My master’s thesis lies at the intersection of stochastic modeling, finite element methods, and high-performance computing, under the supervision of Prof. Geir-Arne Fuglstad at NTNU and Prof. Alan Edelman at MIT.

During the 2025–2026 academic year, I studied at MIT as a Fulbright Scholar, taking courses in applied mathematics and machine learning while conducting research at the Julia Lab. This year, I am spending most of my time in Boston continuing my research at the Julia Lab under the supervision of Prof. Alan Edelman and Dr. Chris Rackauckas.

Publications

SNAP-FM: Sparse Nonlinear Accelerated Projection for Physics-Constrained Generative Modeling

arXiv:2607.00095

First accepted to the AI4Physics workshop at ICML 2026, and subsequently accepted to the IEEE High Performance Extreme Computing (HPEC) conference, where it won an Outstanding Paper Award.

Experience

Mila – Quebec AI Institute

Visiting Master’s Student · June 2026 – September 2026 · Montreal, Canada

Conducted research on accelerating cutting-plane algorithms for large-scale optimization problems arising in electricity markets. In particular, I worked on copositive reformulations of the unit commitment problem and methods for improving the efficiency of the resulting cutting-plane procedure. I worked in the LORER research group under the supervision of Prof. Antoine Lesage-Landry.

Neuroblox

Research Intern · January 2026 – April 2026 · Cambridge, MA

Worked on computational modeling of traveling-wave dynamics in neural systems, with a focus on understanding how wave-like activity emerges and propagates through network models.

Julia Lab, MIT CSAIL

Researcher · September 2025 – Present · Cambridge, MA

Worked on several scientific machine learning projects, including methods for overcoming stiffness barriers in Neural ODE training, SNAP-FM for physics-constrained flow matching, and HiFlight, a surrogate-modeling project for high-speed aerodynamic flows. My work has focused on combining machine learning with numerical methods and physical structure.

Deloitte

Technology Consulting Intern · June 2025 – August 2025 · Oslo, Norway

Worked in Deloitte’s AI & Data practice, supporting a client project focused on the use of AI tools in industry. Contributed to evaluating and applying AI-based solutions in a practical business setting.

Awards and Honors

Fulbright Scholarship

2025–2026

Awarded to support graduate-level studies and research in the United States.

Jansons Legat