I am a physicist with a background in theoretical physics and professional experience in software engineering. I hold a Master’s degree in Physics from the University of Copenhagen, where my research focused on the CMB on large angular scales.
My research experience includes theoretical modelling, numerical methods, and scientific computing. I have worked with first-principles simulations using Quantum ESPRESSO and Yambo, and have developed practical experience with machine learning through independent projects in natural language processing and computer vision.
After my studies, I worked as a software engineer, developing and maintaining large-scale software systems. This experience strengthened my programming, problem-solving, and computational skills, and gave me experience working with complex systems and large-scale structured data.
I am now interested in returning to research and applying this combination of physics, computational methods, and software engineering to scientific problems in astrophysics.
Thesis Tile: The CMB on large angular scales
Thesis Title: Perfect Transmission in Non-Hermitian Scattering Media
Investigated the dipolar power asymmetry of the Cosmic Microwave Background (CMB) using Planck observations. Combined existing theoretical models, derived the corresponding dipole amplitude, and constrained the model using observational data.
View thesisInvestigated wave propagation and perfect transmission in non-Hermitian scattering media using analytical and numerical methods in MATLAB.
View thesisPerformed first-principles Density Functional Theory (DFT) calculations using Quantum ESPRESSO and Yambo to investigate the optical, electronic, and thermodynamic properties of materials under ultrafast laser excitation.
Conducted convergence testing, band-structure, and density-of-states calculations for materials including silicon and nickel. Used Python for computational post-processing, analysis, and visualization.
Project: eu-LISA Interoperability Platform — an EU agency responsible for large-scale IT systems supporting border control, visa management, and asylum processes.
Developed and maintained software for a large-scale e-commerce platform processing millions of orders annually.
Developed and evaluated deep learning models for classifying scientific text using the PubMed 200k RCT dataset. Explored different text representations and model architectures, including pretrained embeddings, character-level representations, and hybrid approaches.
View on GitHub
Developed and fine-tuned deep learning models for image classification using the Food101 dataset. Worked with data preprocessing, model training, transfer learning, evaluation, and visualization using TensorFlow.
View on GitHub- Likelihood - Distribution function - Prior and Posterior Probabilities - Maximum Likelihood Estimation - Bayesian Parameter Estimation - Hypercube and Gaussian functions - kth-Nearest Neighbor (KNN) classifier - Parzen Windows classifier - Steepest Descent algorithm
- Neural Network Regression & Classification - Computer Vision - NLP - Time Series - Transfer Learning - Supervised Learning
- A∗ search algorithm - Sampling-Based Planning - Robot Kinematics and Dynamics Project - Form Closure - Stability of an Assembly - Capstone Project, Mobile Manipulation
All assignments and projects were completed using Visual Studio. - Objects, Types and Values. - Errors. - Functions. - Classes - IO Streams - Customizing IO - Graphic Classes - Class Design - GUI - Vector and Free Store - Pointer and Arrays