Hi, I'm
MSc student in Applied & Computational Mathematics at KTH, specializing in data science, machine learning, and statistical modeling.
I'm a mathematician and aspiring data scientist based in Stockholm, with a passion for turning complex problems into clean, interpretable models. Currently finishing my MSc at KTH Royal Institute of Technology with a focus on machine learning, probability theory, and statistical inference.
I spent a semester at TU Delft studying financial mathematics and stochastic processes, and hold a BSc in Engineering Mathematics from KTH. I enjoy working at the intersection of rigorous mathematics and practical engineering.
Researched the Most Diversified Portfolio (MDP) as an alternative to market-cap weighted indices. Simulated MDPs in Python and benchmarked against market indices. Explored factor estimation and dimensionality reduction techniques.
Built a frequency-severity GLM on 137k policies with Poisson frequency and Gamma severity models. Implemented a full pricing pipeline including risk grouping, tariff cell aggregation, and model validation.
Applied deep learning-based super-resolution to enhance simulated radio maps, reducing reliance on costly ray-tracing. Achieved 21% better reconstruction metrics than interpolation baseline and 12x faster generation.
Built a Bayesian hierarchical change-point model with a hybrid Gibbs + Metropolis-Hastings sampler. Implemented and tuned Hamiltonian Monte Carlo, achieving 99.9% acceptance rate with fast-decaying autocorrelation.
Compared shallow vs deep FCNNs and CNNs using TensorFlow, holding compute capacity constant to isolate the impact of depth. Evaluated using accuracy, runtime, and parameter count with dropout ablations.
Collaborated with a PhD team to create an idealized model of the left atrium for simulating blood flow dynamics using finite element analysis in C++. Highlighted applications in biomedical engineering.
Led teams and coordinated on-site operations and documentation, serving as main company representative.
Led operations for Armada Run, coordinating team schedules, logistics, and event-day execution.
Explored fintech operations and expanded knowledge on MECE, Agile/Scrum, and MVP-driven product development.
Provided 1:1 tutoring in probability theory and statistics, adapting content to student needs.
I'm always open to discussing new opportunities, interesting projects, or collaborations. Feel free to reach out.