Data Science and Machine Learning student and research intern at Aalborg University, working on probabilistic models for graphs and genomes.
Department of Computer Science, Aalborg University. Curriculum and group projects ›
[line of study]
Department of Computer Science, Aalborg University.
With Thomas Dyhre Nielsen, Mads Albertsen and Abdulkadir Çelikkanat. Benchmarked mmlong2 binning on 20 MicroBench samples on BioCloud (cost and genome quality); re-implemented SemiBin2’s long-read self-supervised mode; audited 12 binners against one interface.
With Abdulkadir Çelikkanat. Research paper in preparation on inferring the number of communities in a graph.
Go-to-market strategy and startup support, plus occasional digital and AI direction.
[Clients, what you delivered, one result.]
[What you led or changed.]
Python, PyTorch, JAX, NumPy / SciPy, SQL, LaTeX.
Proficient in Stan and NumPyro: probabilistic models, MCMC and variational inference.
PyTorch Geometric for graph neural networks; stochastic block models and graph sampling.
Building and running complex research pipelines with AI coding agents, as in MegoBin and my other research projects.
Snakemake pipelines on HPC (Slurm, AAU BioCloud); reproducible experiments with versioned code and figures.