Sonja Mathias, Adrien Coulier and Andreas Hellander (2021), CBMOS: a GPU-enabled Python framework for the numerical study of center-based models (bioRxiv preprint)

Fredrik Wrede, Robin Eriksson, Richard Jiang, Linda Petzold, Stefan Engblom, Andreas Hellander (2021), Robust and integrative Bayesian neural networks for likelihood-free parameter inference (ArXiv preprint)

Ola Spjuth, Andreas Hellander and Jens Frid (2021), The Machine Learning Life Cycle and the Cloud: Implications for Drug Discovery (submitted)

Harrison PJ, Wieslander H, Sabirsh A,  Karlsson J, Malmsjö V, Hellander A, Wählby C,  Spjuth O. (2021) Deep learning models for lipid-nanoparticle-based drug delivery, Nanomedicine.

Richard Jiang, Bruno Jacob, Matthew Geiger, Sean Matthew, Bryan Rumsey, Prashant Singh, Fredrik Wrede, Tau-Mu Yi, Brian Drawert, Andreas Hellander, Linda Petzold (2021) Epidemiological modeling in StochSS Live!, 2021, Bioinformatics btab061

Morgan Ekmefjord, Addi Ait-Mlouk, Sadi Alawadi, Mattias Åkesson, Desislava Stoyanova, Ola Spjuth, Salman Toor, Andreas Hellander (2021) Scalable federated learning with FEDn. (ArXiv preprint)

Ben Blamey, Ida-Maria Sintorn, Andres Hellander and Salman Toor (2021) Resource- and Message Size-Aware Scheduling of Stream Processing at the Edge with application to Realtime Microscopy. (ArXiv preprint).

Adrien Coulier, Stefan Hellander and Andreas Hellander (2021), A multiscale compartment-based model of stochastic gene regulatory networks using hitting-time analysis, J. Chem. Phys. 154, 184105.


Richard Jiang, Fredrik Wrede, Prashant Singh, Andreas Hellander and Linda R Petzold, Accelerated Regression-Based Summary Statistic for Discrete Stochastic Systems via Approximate Simulations, 2020 (submitted)

Mattias Åkesson, Prashant Singh, Fredrik Wrede, Andreas Hellander, Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation, ArXiv preprint.

Oliver Stein, Ben Blamey, Johan Karlsson, Alan Sabirsh, Ola Spjuth, Andreas Hellander, Salman Toor (2020) Smart Resource Management for Data Streaming using an Online Bin-packing Strategy, 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 2020, pp. 2207-2216 ArXiv preprint.

Ben Blamey, Salman Toor, Martin Dahlö, Håkan Wieslander, Philip J Harrison, Ida-Maria Sintorn, Alan Sabirsh, Carolina Wählby, Ola Spjuth, Andreas Hellander, Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit, Gigascience 10(3) BioRxiv preprint.

S. Mathias, A. Coulier, A. Bouchnita, A. Hellander (2020), Impact of force functions on the numerical simulation of centre-based models, Bulletin of Mathematical Biology 82, 132. BioRxiv preprint.

A. Bouchnita, V. Volpert, M.J. Koury, A. Hellander (2020) A multiscale model to design therapeutic strategies that overcome drug resistance in multiple myeloma, Mathematical Biosciences, 319, pp. 108293.


B. Blamey, I-M. Sintorn, A. Hellander, S. Toor (2019) Resource- and Message Size-Aware Scheduling of Stream Processing at the Edge with application to Real-time Microscopy ArXiv preprint: https://arxiv.org/abs/1912.09088  Dataset

B. Blamey, A. Hellander, and S. Toor, Apache Spark Streaming, Kafka and HarmonicIO: A Performance Benchmark and Architecture Comparison for Enterprise and Scientific Computing, in Bench’19, Denver, Colorado, USA, 2019. ArXiv preprint

S. Hellander and A. Hellander (2019) Hierarchical Reaction-Diffusion Master Equation, J. Chem. Phys, 152(3) pp. 034104.  ArXiv preprint

A. Bouchnita, S. Hellander, A. Hellander (2019),   A 3D Multiscale Model to Explore the Role of EGFR Overexpression in Tumourigenesis, Bull. Math. Biol. 81(7):2323-2344

B. Blamey, F. Wrede, J. Karlsson, A. Hellander, S. Toor (2019), Adapting The Secretary Hiring Problem for Optimal Hot-Cold Tier Placement under Top-Workloads, in 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). ArXiv preprint.

F. Wrede and  A. Hellander (2019), Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning, Bioinformatics btz420.  


P. Singh and  A. Hellander (2018), Multi-objective optimization driven construction of uniform priors for likelihood-free parameter inference, EUROSIS , 2018. p. 22-27.

A. Coulier and A. Hellander (2018), Orchestral: a lightweight framework for parallel simulations of cell-cell communication, in IEEE 14th International Conference on e-Science.

P. Singh and A. Hellander (2018), Multi-Statistic Approximate Bayesian Computation with Multi-Armed Bandits (submitted).

P. Singh and A. Hellander (2018), Hyperparameter Optimization for Approximate Bayesian Computation, Proceedings of the Winter Simulation Conference 2018,  pp. 1718-1729.

P. Singh, E. Vats and A. Hast (2018), Learning surrogate models of document image quality metrics for automated document image processing, I Proc. 13th International Workshop on Document Analysis Systems.

P. Torruangwatthana, H. Wieslander, B. Blamey, A. Hellander and S. Toor (2018), HarmonicIO: Scalable data stream processing for scientific datasets, In. proc. 2018 IEEE 11th International Conference on Cloud Computing (CLOUD)

K. Ausmees, A. John, S. Toor, A. Hellander  and C. Nettelblad (2017), BAMSI: A multi-cloud service for scalable distributed filtering of massive genome data,  BMC Bioinformatics 19, Article number: 240.