Principal Investigator & Group Leader
Division of Scientific Computing (TDB)
Department of Information Technology
Box 337, SE-751 05 Uppsala
telephone: +46-18-471 2609
email: andreas.hellander at it.uu.se
Stefan Hellander. Stefan obtained his Ph.D. in scientific computing from Uppsala University in 2013. He then went on to work as a postdoc in the lab of Prof. Linda Petzold at UCSB, until returning to Uppsala in August of 2017. His research interests include microscopic and mesoscopic modeling and simulation of reaction-diffusion systems, as well as multiscale modeling with the aim of accurately integrating the different scales.
Prashant Singh. Prashant received his B.Sc. (H) and M.Sc. degrees in Computer Science from the University of Delhi, India in 2009 and 2011 respectively. He obtained the degree of Ph.D. in Computer Science Engineering from Ghent University, Belgium in May 2016. Prashant’s research interests span machine learning, optimization and scientific computing. His interested include Gaussian processes for large scale and distributed modeling, Bayesian optimization, active learning and surrogate modeling and optimization problems in engineering.
Ben Blamey. Ben undertook his PhD at Cardiff Metropolitan University, in partnership with a tech startup, studying data mining (especially natural language processing) in the context of social media. Subsequently, he lectured at Cardiff University, helping to establish the National Software Academy and create the Applied Software Engineering Bsc., in collaboration with industry. Before joining the Hellander Lab, he worked on connected cars at Springworks. He is broadly interested in the architecture of scientific computing systems and the representation of metadata therein.
Anass Bouchnita received his Engineer’s and PhD degree in Modelling and Scientific Computing from the Mohammadia School of Engineering. He also obtained a PhD degree from Claude Bernard Lyon 1 University. He works on the development of novel mathematical models that simulate complex physiological systems. His research interests include reaction-diffusion systems, multiscale cell-based models, PK-PD modelling, and their various applications in biomedicine.
Adrien Coulier. Adrien graduated with an Engineer’s degree in Mathematical Engineering from the National Institute of Applied Sciences of Rouen and a Master’s degree in Theoretical Computer Science from the University of Rouen (France). Adrien’s research interests include Parallel Computing, Probability Theory and Mathematical Modeling of Natural Phenomena.
Sonja Mathias. Following an interdisciplinary Bachelor of Science in Computational Life Science from the University of Lübeck, Sonja received a Master of Science in Mathematics with specialization in Numerical Mathematics and Scientific Computing from the University of Bonn (both Germany). In her MSc thesis in the Virtual Materials Design group at the Fraunhofer SCAI (St. Augustin, Germany) she developed a kernel-based learning method for the potential energy of atomic systems using Gaussian processes. Aside from Machine Learning, her research interests include the mathematical modeling of biological systems and the simulation thereof, especially at the multicellular scale.
Fredrik Wrede. Fredrik graduated with a BSc degree in biology/molecular biology followed by a MSc degree in Bioinformatics at Uppsala University. Fredrik’s research interests include Applied Cloud Computing, Data Mining and Machine Learning, and Modeling of Biological Phenomena. Fredrik is is part of the Center for Interdisciplinary Mathematics (CIM) graduate school.