Andreas Hellander
Universitetslektor vid Institutionen för informationsteknologi; Beräkningsvetenskap
- Telefon:
- 018-471 29 72
- Mobiltelefon:
- 070-395 04 47, 073-469 70 10
- E-post:
- andreas.hellander@it.uu.se
- Besöksadress:
- Hus 10, Lägerhyddsvägen 1
- Postadress:
- Box 337
751 05 UPPSALA
- Akademiska meriter:
- Docent
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Kort presentation
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Hellander lab on Computational Science and Engineering: http://hellanderlab.research.it.uu.se
Nyckelord
- applied cloud computing
- computational science and engineering
- computational systems biology
- escience
Biografi
Denna text finns inte på svenska, därför visas den engelska versionen.
Andreas Hellander is Associate Professor of Scientific Computing at Uppsala University where he leads a research group on computational science and engineering at the Division of Scientific Computing, Department of Information Technology.
His research centers around efficient and flexible computational methods and scientific software for computational experimentation in particular in the life sciences. Focus areas are computational systems biology, distributed (cloud) and data-intensive computing and multiscale modelling of stochastic reaction diffusion kinetics.
Forskning
With a core in scientific computing and systems biology, the work in the lab aims to develop next-generation tools for smart and efficient computational experimentation. A prominent application area is systems biology, where we use simulations to study spatial and temporal aspects of cellular regulatory systems. To that effect, we pursue a broad range of topics ranging from development of multiscale methods for spatial stochastic simulations to modelling of multicellular systems to cloud computing and development of smart and interactive computational science and engineering software.
Publikationer
Senaste publikationer
- Data management of scientific applications in a reinforcement learning-based hierarchical storage system (2024)
- Contributions of cell behavior to geometric order in embryonic cartilage (2023)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning (2023)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract (2023)
- FedQAS (2022)
Alla publikationer
Artiklar
- Data management of scientific applications in a reinforcement learning-based hierarchical storage system (2024)
- Contributions of cell behavior to geometric order in embryonic cartilage (2023)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning (2023)
- FedQAS (2022)
- Surface flow for colonial integration in reef-building corals (2022)
- Systematic comparison of modeling fidelity levels and parameter inference settings applied to negative feedback gene regulation (2022)
- Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods (2022)
- Altered developmental programs and oriented cell divisions lead to bulky bones during salamander limb regeneration (2022)
- CBMOS (2022)
- Living in darkness (2022)
- Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation (2022)
- Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit (2021)
- A multiscale compartment-based model of stochastic gene regulatory networks using hitting-time analysis (2021)
- Deep-learning models for lipid nanoparticle-based drug delivery (2021)
- Epidemiological modeling in StochSS Live! (2021)
- Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators (2021)
- Scalable machine learning-assisted model exploration and inference using Sciope (2021)
- Approaches for containerized scientific workflows in cloud environments with applications in life science (2021)
- The machine learning life cycle and the cloud (2021)
- A multiscale model to design therapeutic strategies that overcome drug resistance to tyrosine kinase inhibitors in multiple myeloma (2020)
- Hierarchical algorithm for the reaction–diffusion master equation (2020)
- Impact of Force Function Formulations on the Numerical Simulation of Centre-Based Models. (2020)
- A 3D multiscale model to explore the role of EGFR overexpression in tumourigenesis (2019)
- Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning (2019)
- BAMSI (2018)
- Robustness analysis of spatiotemporal models in the presence of extrinsic fluctuations (2017)
- Mesoscopic-microscopic spatial stochastic simulation with automatic system partitioning (2017)
- Oriented clonal cell dynamics enables accurate growth and shaping of vertebrate cartilage (2017)
- GillesPy (2016)
- Mesoscopic modeling of stochastic reaction–diffusion kinetics in the subdiffusive regime (2016)
- Stochastic Simulation Service (2016)
- MOLNs (2016)
- Analysis of neural crest-derived clones reveals novel aspects of facial development (2016)
- Analysis and design of jump coefficients in discrete stochastic diffusion models (2016)
- Reaction rates for mesoscopic reaction-diffusion kinetics (2015)
- Accuracy of the Michaelis–Menten approximation when analysing effects of molecular noise (2015)
- Local error estimates for adaptive simulation of the reaction–diffusion master equation via operator splitting (2014)
- URDME (2012)
- Coupled mesoscopic and microscopic simulation of stochastic reaction-diffusion processes in mixed dimensions (2012)
- Reaction-diffusion master equation in the microscopic limit (2012)
- CellMC (2010)
- An adaptive algorithm for simulation of stochastic reaction-diffusion processes (2010)
- Incorporating active transport of cellular cargo in stochastic mesoscopic models of living cells (2010)
- Simulation of stochastic reaction-diffusion processes on unstructured meshes (2009)
- A hierarchy of approximations of the master equation scaled by a size parameter (2008)
- Sparse grids and hybrid methods for the chemical master equation (2008)
- Efficient computation of transient solutions of the chemical master equation based on uniformization and quasi-Monte Carlo (2008)
- Hybrid method for the chemical master equation (2007)
- A pipeline for systematic comparison of model levels and parameter inference settings applied to negative feedback gene regulation
Böcker
- Multiscale Stochastic Simulation of Reaction-Transport Processes (2011)
- Numerical simulation of well stirred biochemical reaction networks governed by the master equation (2008)
Kapitel
Konferenser
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract (2023)
- Scalable federated machine learning with FEDn (2022)
- Robust and integrative Bayesian neural networks for likelihood-free parameter inference (2022)
- Apache Spark Streaming, Kafka and HarmonicIO (2020)
- Smart Resource Management for Data Streaming using an Online Bin-packing Strategy (2020)
- Adapting the secretary hiring problem for optimal hot–cold tier placement under top-K workloads (2019)
- Orchestral (2018)
- Multi-objective optimization driven construction of uniform priors for likelihood-free parameter inference (2018)
- Hyperparameter optimization for approximate Bayesian computation (2018)
- HarmonicIO (2018)
- Cost-aware application development and management using CLOUD-METRIC (2017)
- Surrogate assisted model reduction for stochastic biochemical reaction networks (2017)
- SNIC Science Cloud (SSC) (2017)
- Automatic and portable cloud deployment for scientific simulations (2014)
- Scientific analysis by queries in extended SPARQL over a scalable e-Science data store (2013)
- Abstractions for scaling eScience applications to distributed computing environments (2012)
- Reducing complexity in management of eScience computations (2012)
- Adaptive stochastic hybrid simulation of biochemical reaction-diffusion models (2009)
Rapporter
- Coupled mesoscopic and microscopic simulation of stochastic reaction-diffusion processes in mixed dimensions (2011)
- Incorporating active transport of cellular cargo in stochastic mesoscopic models of living cells (2010)
- An adaptive algorithm for simulation of stochastic reaction-diffusion processes (2009)
- Simulation of stochastic reaction-diffusion processes on unstructured meshes (2008)
- A hierarchy of approximations of the master equation scaled by a size parameter (2007)
- Efficient computation of transient solutions of the chemical master equation based on uniformization and Quasi-Monte Carlo (2007)
- Hybrid method for the chemical master equation (2006)
