Anis holds a PhD in Fluid Mechanics from the University of Oslo. Before joining us, he completed a three-year postdoctoral fellowship, which included research stays at PUC-Rio, Brazil and Princeton University, USA.
Advanced Data Visualization
Concise and informative visualisation is the key for comprehension and communication of data and analysis results. Especially these days where the amount of data is often huge and traditional visualisation forms may not be suitable. Treatments like data reduction or aggregation are then needed to visualise the data efficiently.
Visualisation of data plays an important role in data science, machine learning and analysis platforms. Raw data needs to be inspected, results of computational simulations and algorithms need to verified, and the end-users need insight into the data too. Given the large amounts of data available in today's analyses, implementing efficient and responsive visualization software is far from trivial.
Our consultants have expertise in standard and advanced data visualisation techniques. This includes pretreatments such as reduction, aggregation and contextualising of data. For more complex visualization of larger data sets, a combination of different techniques is often required. For instance, deriving some statistical measures across spatial, temporal and parametric dimensions can be combined with blending techniques to provide novel visual insight.
Diako holds a Ph.D. in Computational Mathematics from the University of Oslo. As a student at both Mathematics and Physics departments at the University of Oslo, he has acquired a broad knowledge in various physical and mathematical theories, and numerical methods.
Guttorm is a curious person with an interest and enthusiasm for technology and problem solving. His academic background is focused around applied mathematics, programming, and physics. He submitted his master’s thesis the summer 2017 in the field of Computational Science and Engineering at the University of Oslo / Simula.
Robert is finishing a PhD in astrophysics at the University of Oslo, with specialisation in cosmological simulations. He is experienced with numerical modelling of physical systems, statistical analysis of large data sets, and solving highly non-linear systems of differential equations with parallel computing.
Robert Solli is a specialist in scientific programming, with expertise in mathematical optimisation, statistical analysis and machine learning. He has solved a varied set of problems with this skillset, from understanding complex physical systems to increasing student volunteer participation.
Vinzenz is a curious, pragmatic, creative problem solver. He holds a PhD in biomechanical engineering, focusing on stochastic simulations of the blood flow in the human arterial system. This interdisciplinary work included working within engineering, medicine, biology, software development and statistics.