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
Salman Toor. Toor obtained his Masters and PhD in Scientific Computing from Uppsala University, Sweden. After postdoctoral research as part of the CMS program, Helsinki Institute of Physics, Finland, he is currently employed as a researcher in Applied Cloud Computing at the Department of Information Technology, Uppsala University and as Cloud Application Expert at the UPPMAX HPC Centre. His research interests include management, scalability and performance of distributed infrastructures for scientific applications. He also serves as Senior Cloud Architect in the SNIC Science Cloud project.
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 the field of engineering design optimization.
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.