My research revolves around interdisciplary applications using structured deep learning. The main focus of my PhD is attempting to speed up space weather simulation that follows the hybrid-Vlasov formalism.

Experience

  • Visiting researcher at CMCC building an ML based alternative to the operational numerical Mediterranean forecasting system.
  • Visiting researcher at SARAO developing computer vision techniques to deconvolve radio interferometric images.
  • Technical student at CERN working with Kubeflow, a cloud native service supporting scalable end-to-end machine learning pipelines.
  • Further information in my CV.

Publications

article Accurate Mediterranean Sea forecasting via graph-based deep learning
Daniel Holmberg, Emanuela Clementi, Italo Epicoco, Teemu Roos
preprint, 2025
arxiv | slides
article Global fields of daily accumulation-mode particle number concentrations using in situ observations, reanalysis data and machine learning
Aino Ovaska, Elio Rauth, Daniel Holmberg, et al.
preprint, 2025
paper
article Learning Developmental Age from 3D Infant Kinetics Using Adaptive Graph Neural Networks
Daniel Holmberg, Manu Airaksinen, Viviana Marchi, Andrea Guzzetta, Anna Tuiskula, Leena Haataja, Sampsa Vanhatalo, Teemu Roos
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2025
paper | arxiv
article Regional Ocean Forecasting with Hierarchical Graph Neural Networks
Daniel Holmberg, Emanuela Clementi, Teemu Roos
In NeurIPS 2024 Workshop on Tackling Climate Change with Machine Learning, 2024
paper | arxiv | slides | poster
article Jet Energy Calibration with Deep Learning as a Kubeflow Pipeline
Daniel Holmberg, Dejan Golubovic, Henning Kirschenmann
Computing and Software for Big Science, Vol 7, 2023
paper | arxiv | kubecon video | meetup video
article Jet Energy Corrections with Graph Neural Network Regression
Daniel Holmberg
Master’s Thesis, University of Helsinki, 2022
thesis | slides | poster
article Interatomic Fe–Cr potential for modeling kinetics on Fe surfaces
Pekko Kuopanportti, Matti Ropo, Daniel Holmberg, et al.
Computational Materials Science, Vol 203, 2022
paper | arxiv
article Potentialmodeller vid simulering av Fe-Cr
Daniel Holmberg
Bachelor’s Thesis, University of Helsinki, May 2019
thesis | slides

Talks

Accurate Mediterranean Sea Forecasting via Graph-based Deep Learning The Way Forward Workshop: AI/ML in Earth System Science :it:
Regional Ocean Forecasting with Hierarchical Graph Neural Networks CMCC Seminar :it:
CERN ML Platform CMG Group Meeting :switzerland:
Jet Energy Corrections with GNN Regression using Kubeflow at CERN KubeCon Valencia :es:
Jet Energy Corrections with Graph Neural Network Regression Learning to Discover :fr:
Centralized Management of Your Machine Learning Lifecycle CERN IT Technical Forum :switzerland:
Jet Energy Corrections with DNN Regression CMS Machine Learning Forum :switzerland:
Emerging Computing Architectures Distributed ML Seminar :finland:
Top Quark Mass Measurement LPC CMS Data Analysis School