EXPERT ANALYTICS AS - Key Persons
Ada is a senior researcher with 20 years of academic experience in the field of Astrophysics during which she taught, mentored students, organized several international conferences and led her own research projects. She is engaged in scientific communication and outreach, having published two books, delivered public lectures, appeared in the media explaining solar physics to a general audience and been nominated as TED speaker. She decided to take on a new challenge and apply her skills in the industry. Ada enjoys analyzing complex problems as well as extracting valuable information out of data.
Alessandro has a PhD in Physics and 10+ years of corporate and academic experience in software development, machine learning, scientific research, and technical troubleshooting. Alessandro is eager to work with new technologies and is experienced in solving problems analytically and with creativity. At the same time he is proficient in handling technical issues and in communicating with end users.
Alexander is a seasoned programmer specializing in Python; a result of more than three years of professional experience as a Python systems developer and over a decade programming in Python. He has worked in both the public transport sector and the energy sector on several projects combining back-end and front-end development. Alexander holds a master's thesis in computational quantum physics from the University of Oslo.
The subject of Alexander's thesis was Monte Carlo simulations of quantum dots using C++ and Python.
His education has trained him in solving complex physical and mathematical problems using various numerical methods and libraries as well as visualization. He is also a fast learner and can adapt to new frameworks and programming languages quickly.
Alocias has a master's degree in physics from the University of Oslo, submitted in spring 2018. The subject of the thesis was Quantum Monte Carlo Simulations of Quantum dots constrained in single- and double well potentials. He solved the numerical problem for both systems with new analytic expressions which had not been explicitly done before and a newer method with roots in machine learning to further improve upon the results.
Ana holds a PhD in applied mathematics from University of Bergen and has worked as a postdoctoral researcher at Simula Research Lab in Norway. Her expertise lies in computational modeling, and algorithm design and implementation to solve large-scale problems in biomechanics and geophysics. Ana is an eager and challenge-driven person with strong interest in software development, scientific computing and machine learning.
Ana's academic pursuits have primarily centered around numerical solvers for partial differential equations and the software implementation of computational techniques. Furthermore, she has delved into the analysis and utilization of neural networks, exploring their capacity to simulate physical laws and their performance in comparison to established methods.
Ana has also acquired hands-on experience in machine learning, statistics, and data visualization, particularly with social network analysis of sports data and image/video processing for motion detection.
Andreas submitted his master's thesis in applied mathematics from the University of Oslo and Simula Research Laboratory. In his thesis he investigated numerical schemes, for solving equations describing Fluid-Structure Interaction, using Python and FEniCS. His academic background has given him several tools and approaches for solving complex problems in a computational/software domain.
Ata holds a PhD in physics with specialisation in astrophysics which he obtained from Brown University in 2014. Before joining the Expert Analytics team, he has worked as a postdoctoral researcher at the University of Oslo and Universite Paris VII. His expertise includes statistical analysis of large data sets, numerical modelling, signal processing, imaging, and programming.
Bastian holds a Ph.D. in computational mathematics from the University of Oslo. In his thesis he used mathematical modeling to investigate how molecules are transported in the human brain. His expertise lies in numerical simulations, nonlinear optimization and deep learning. Bastian is a systematic person with interest in computational modeling and working with imaging data.
From his academic work, Bastian has gained substantial experience in combining large amounts of clinical imaging data with computational models. He is used to performing resource-demanding computations on supercomputers, including numerical simulations and training deep neural networks. Being a pragmatic programmer eager to learn new techniques, he used shape optimization methods in a data-driven approach to simplify the intricate workflow of his simulations.
Christian holds a PhD in fluid mechanics from the University of Oslo, where he also worked as a postdoctoral researcher. His expertise includes mathematical modeling, numerical methods and programming. Christian enjoys working in interdisciplinary environments and applying this knowledge to contribute to real-world solutions.
During his PhD studies, he was involved in several research projects collaborating with multiple international research institutes. His main responsibility was the assessment of experimental data, including creating software for data analysis and visualization, the development of theoretical models, and the software implementation of numerical solvers. In his time in academia, he worked on problems related to elastohydrodynamics, lubrication, multiphase flow, charging of supercapacitors, and biomechanics. In addition, he has also worked with machine learning by combining neural networks with a
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.
Eivind has a masters degree in Computational Science from the University of Oslo, completed in 2016. His project investigated a particle system modeling linear elasticity, and accelerating linear algebra computations using GPUs. From the studies leading to his degree he has gained broad knowledge about algorithms, numerical mathematics, and programming in several languages.
Eleonora obtained her PhD degree in applied mathematics from the University of Oslo and Simula Research Laboratory (Oslo, Norway) in 2023, and her Master's degree in Aeronautical engineering from Politecnico di Milano in 2015. During her doctoral studies, she developed efficient solvers and robust formulations for poroelasticity equations applied to model brain displacements and fluid flow. From 2019 to 2023, Eleonora worked as a research and development engineer at FLIR Unmanned Aerial Systems AS (Hvalstad, Norway). In that role, she focused on improving the aerodynamical performances of drones using both numerical models and practical experiments.
Eleonora has experience in numerical simulations, mathematical modelling, testing, scientific writing, data acquisition, data analysis, and data visualization. In addition, Eleonora has supervised master students and summer interns providing guidance and feedback to help them produce high-quality work. Eleonora enjoys working in a collaborative and multidisciplinary enviroments. She is eager to continue learning new things while making valuable contributions in dynamic and demanding settings.
Eric holds a Ph.D. in Nuclear Physics from Berkeley. His thesis was written on the nuclear data of fission yields. His main interests include nuclear medicine, data science and analysis, and statistics. Eric is currently working with Expert Analytics to develop its oncology research portfolio after the company joined the Oslo Cancer Cluster in November 2022. Eric retains an appointment on the research faculty at the Department of Nuclear Engineering at Berkeley.
Eric completed his Ph.D. in August 2021 and thereafter joined the Department of Nuclear Engineering at Berkeley as a member of the research faculty. In October 2022, Eric joined Expert Analytics. He seeks projects that can utilize his skills in data science and nuclear science.
Eric's main programming languages are Python and C++, however, he has extensive knowledge of FORTRAN and can also program in Java, MATLAB, and C. Eric has experience in open-source software development and open-access datasets. He is well-versed in using common scientific coding packages such as NumPy, SciPy, and ROOT.
Eric particularly enjoys developing thorough uncertainty quantifications for his analyses. These skills were developed in the course of his education and research in nuclear data. Eric frequently employs Monte Carlo methods for these quantifications.
As a result of his time as a National Nuclear Security Administration Fellow, Eric has developed an interest and considerable background in nuclear security policy. He led a student group at the Goldman School of Public Policy to publish their final course report in the Bulletin of Atomic Scientists.
Finally, Eric greatly enjoys teaching. During his time at Berkeley, Eric was a teaching assistant or graduate student instructor on seven occasions. In 2018, he was awarded one of Berkeley's "Outstanding Graduate Student Instructor" awards, a university-wide recognition.
Felix is a research scientist with experience in data analysis and scientific programming. He holds a PhD in physics and worked in various interdisciplinary projects both as a Postdoc and Researcher in an academic setting as well as a senior researcher in industry. Felix has a background in both experimental studies as well as mathematical and numerical modelling. His creativity, analytical mindset and scientific experience provide him with a solid foundation for finding solutions to complex problems.
His areas of expertise include image processing, time series analysis, numerical simulations of complex physical systems, statistical data analysis, machine learning applications as well as visualisation and handling of large datasets. Felix worked in the fields of environmental physics, biophysics, optics, microscopy, physics of complex systems, crystal growth, geophysics, neuroscience, sport science and medical instrument technology. During his career he collaborated with people from various backgrounds including meteorology, medicine, biology, engineering, geology, psychology and biochemistry. Felix is driven by curiosity and is always looking for new challenges.
Gry is a curious, efficient and pragmatic problem solver. She completed her PhD in experimental nuclear physics at the University of Oslo in 2013 and most of her PhD work was carried out at CERN. She has 6 years of post doc experience. Her recent work focused on understanding how the elements are created in stellar processes. This research required developing detection systems, analyzing data, visualization and carrying out complex simulations. She has also teaching experience, including course development at university level and has led her own projects since she completed her PhD.
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.
In his work he performed numerical simulations of micro-particles inhaled into the human respiratory system. This involved writing Python scripts as well as modifying and working with open-source libraries, in addition to data analysis and supercomputer simulations.
While working at Expert Analytics, he has continued developing his programming skills in Python and Go, and has been diving into topics such as machine learning and web programming.
Jakob holds a Ph.D. in computational mathematics from the University of Oslo, where he studied mathematical models of electrical activity in the brain. He also developed computer models running on high-performance computers produces large amounts of data. Jakob is a pragmatic programmer who takes pride in building robust, clean and easy-to-maintain software solutions. Since being awarded his Ph.D, Jakob has built and maintained energy-market models in the renewable power sector.
Jakob's experience working in an interdisciplinary field, and enthusiasm for learning have been key to his success in collaberating with experts from diverse fields. By working closely with colleagues, Jakob has been able to deliver practical and technically sound solutions that meet real-world needs. He values the importance of learning from others and sharing his own expertise to support others, and believes that the best solutions are achieved in collaboration with peers with a range skills and experiences.
John is a computational scientist who has experience across disciplines in using machine learning, statistics, software development to reach solutions. John has worked on a variety of problems and enjoys learning new topics and new technology that connect across disciplines. At Expert Analytics John works on problems related to global scale spatio-temporal modeling and CO2 sequestration. John also is affiliated as Researcher at the University of Oslo in the Njord Centre for Studies of the Physics of the Earth.
Kate holds a PhD in Marine Geology from Durham University, United Kingdom, and completed a post-doc at the University of Victoria, Canada. She is a problem solver, analytical thinker and loves a challenge. With her Earth Sciences background, she is an expert in big data analysis and visualisation, fieldwork planning and preparation, as well as instrument deployment. She has worked with a variety of geophysical data, and is always eager to dive into new data acquisition types. She has strong collaboration skills, extensive teaching experience and great communication skills.
Prior to her PhD where she analysed Acoustic Doppler Current Profiler data, she completed her masters at Uppsala University, Sweden, with a specialisation in geomorphology and glaciology. Here, she processed and analysed Ground Penetrating Radar data from Svalbard, and did sediment analysis at an external laboratory in Denmark. She is an expert in the pipeline of field work design, data acquisition, data analysis through to data presentation.
Job Titles:
- Professor of Applied Mathematics at the University of Oslo
Kent-Andre is a Professor of Applied Mathematics at the University of Oslo. He has extensive experience with computational modeling, multi-physics simulations, high-performance computing, and scientific software development (Python and C++).
Kent-Andre is experienced in multidisciplinary collaborations where advanced computational techniques are developed to solve real-life problems, in particular in the medicine. In XAL, he brings a broad experience in inter-disciplinary work as well as technical experience in scientific computing involving big data.
Kine is an organized scientific programmer that likes to solve problems from a big picture approach. She submitted her PhD thesis in Climate Science in December of 2021, and during her doctorate she analyzed radiation and air pollution data from a multitude of climate model simulations and compared them with observations. This work gave insight in big data analytics and visualisation, especially regarding time series and how to avoid common pitfalls like comparing apples and oranges. She enjoys working with large datasets, learning new things, and communicating/teaching science.
Kristine has a Master's degree and three years experience as a PhD-student in Nuclear Physics. She has accumulated extensive practice with statistical analysis of sensor data and problem solving using programming tools such as Python and C++. Kristine has performed analyses consisting of handling raw data, performing calibrations, doing time series analysis, statistical fitting of peak distributions and doing model simulations in order to compare to experimental data.
With a background in statistics, machine learning and Bayesian statistics she is able to extract meaningful information and interpret characteristics from data. She always approaches challenges with eagerness and can efficiently learn new skills in order to solve unique problems.
Marco holds a Ph.D in computational Condensed Matter Physics, with a strong focus on quantum and classical atomistic simulation methods. Throughout his decade-long career he has worked on both software development - mainly in C++ and Python - and research intensive projects across several research fields ranging from low-temperature physics to computational chemistry and biophysics. This experience, along with his robust mathematical and coding background, allows him to be a broad and thorough problem solver, well capable of working both independently and as a team member.
Mats has a PhD (2019) in applied and computational mathematics (University of Bergen, Bergen, Norway), in addition to a postdoctoral experience in biomathematics at the University of Oslo, Oslo, Norway (2020-2021). He has experience and interest in biomathematics, fluid mechanics, flow in porous media, heat transfer, solid mechanics, coupled systems, among others. Moreover, he has programming experience in Python, Java, Matlab and Haskell. Mats is an analytical and creative problem solver, whose expertise relies on diverse experience with mathematical modeling and numerical programming, with applications ranging from geothermal energy storage to evolutionary biology, in addition to several teaching experiences.
Max has a PhD (2014) in Aerospace Engineering (INPE, Brazil) and two postdoctoral experiences: one in Applied Mathematics, at IMPA (Brazil, 2014-2016) and another in Chemistry, at the University of Bergen (2016-2019). He has experience and interest in multiphase flow, reactive flows, flows in porous media, heat transfer, CFD, to name a few. Additionally, he has programming experience in Fortran, Matlab, Python and Octave.
Naeeme is an enthusiastic software developer with many years of experience as a project engineer. Before joining our team, she worked in the field of 3D modelling and CFD simulation of reactive and non-reactive flows, employing high-performance computing and immersive virtual reality environments to optimize the performance of industrial units. This allowed her to gain experience in solving complex problems using her expertise in software development combined with her knowledge in fluid dynamics, chemical thermodynamics, mass and heat transfer.
Ola Skavhaug - Chairman, CSO, Founder
Job Titles:
- Chairman of the Board
- CSO
- Founder
- Founder and CSO of Expert Analytics. Loves Mixing High and Low Level Languages to Join Flexibility and High Perfomance Computing
Ola has a PhD in scientific computing, and is an expert software developer with years of experience in industry and academia. He is particularly interested in mathematical and numerical software development, algorithm development, high performance computing and scientific visualization.
Through his work, Ola has obtained an extensive set of skills that allows him to understand and solve challenges in collaboration with different subject matter experts. In addition to his role as Chief Strategy Officer in XAL, Ola is available as an advisor in the renewable energy market, where he has made significant technological and scientific contributions since 2014.
Founder and CSO of Expert Analytics. Loves mixing high and low level languages to join flexibility and high perfomance computing.
Ricardo holds a PhD in applied mathematics from the University of Bergen and NORCE Norwegian Research Institute. With a strong foundation in theoretical and applied sciences, he has been a consultant since 2020, working in both public and private sectors. Ricardo's skill set includes roles as a data analyst, data scientist, and developer. One of Ricardo's key strengths is his expertise in Python and cloud computing, particularly in the Azure ecosystem.
In his academic pursuits, Ricardo delved into data assimilation algorithms, specializing in ensemble-based methods and data compression techniques mainly for oil and gas industry. Ricardo is passionate about applying this knowledge to contribute to real-world solutions.
Roar has a master's degree in High Energy Physics from the University of Oslo, completed in 2018. In his thesis he studied two different models of particle production at high energies, one statistical using the thermodynamical equations and one using the properties of a theoretical particle called Pomeron.
Robert has a PhD in astrophysics, with a specialisation in cosmological simulations. He is experienced with numerical modelling of physical systems, statistical analysis of large data sets, high-performance computing, and cloud based applications.
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.
Sebastian is a curious person always looking to learn about new topics and combining them into novel solutions to complex problems. He received his PhD in biocomputional sciences in March 2021 from the Italian Institute of Technology/University of Bologna, where he studied how nanomaterials interact with physiological environments. He is experienced in molecular simulations, data visualization, and scientific writing. In more recent years, Sebastian has been applying bioinformatic methods to genomics, proteomics, and transcriptomics data.
Sebastian holds a master's degree in applied mathematics from the University of Oslo and Simula Research Laboratory, finished in 2017. In his thesis he built a Fluid-Structure Interaction solver with Python using the FEniCS platform. This also included working with supercomputers parallelizing the computational efforts. During his studies he gained knowledge in algorithms, numerical computing and programming in different languages.
After graduating he worked for Shortcut AS, an app-development company, developing iOS apps and working with Splunk for monitoring and analyzing machine-generated big data. He has also taken courses and attended conferences on AI/Machine Learning, learning neural networks using Tensorflow, Keras, scikit-learn.
Apart from that he is highly adaptable to any situation and can quickly learn new languages and frameworks.
Sigmund submitted his masters's degree in Geophysics and Seismology at the University of Oslo in 2019. The subject of the thesis was Attenuation of Seismic Interference Noise using Convolutional Neural Networks and was written in collaboration with CGG Services AS. This work gave insight in the fields of machine learning and seismic signal processing.
Simen is a computational scientist who finished his Ph.D. in computational neuroscience in 2019. He has a background from computational astrophysics where he wrote software for finding clusters of galaxies in cosmological N-body simulations. His Ph.D. focused on quantifying uncertainties in computational models of neurons and neural networks and he created a Python toolbox for performing these calculations.
Additionally, the work included creating a new specification for data storage, data analysis, and developing an educational neural network simulator. Simen also has teaching experience and has co-authored a textbook that teaches first-semester bachelor students in biology programming, data analysis, and computational modeling.
Simen has experience at learning new disciplines and enjoys using the computer to solve complex problems, create models and numerical simulations and perform data analysis.
Therese holds a Ph.D. in Experimental Nuclear Physics from the University of Oslo. Her thesis was awarded the YARA Birkeland Prize for outstanding contributions to innovation and industry. Her main fields of expertise are developing real-time analytics tools and implementing machine learning and statistical models. The past years, she has developed prototypes and set into production software tools for the petroleum-, processing- and medical industry.
Thomas is interested in bringing to life the potential of data for automation and insight purposes. He will happily engage in the various steps of the process, from analysis and machine learning to data collection and software development.
Thomas holds a PhD in astrophysics for developing and studying models of the solar atmosphere. After finishing the PhD he worked as an analyst in the public sector. Here he took part in the business intelligence process as well as data analyses, data modeling and system architecting. Thomas also completed the two year leadership development program Teach First Norway.
The varied experience makes Thomas a diverse problem solver with a critical and systematic approach. He has the ability of quickly adopting to new projects and suggest novel solutions.
Thomas has a background in Earth Sciences and likes solving challenging problems. During his education at NGI Oslo, UiO, and ETH Zurich, he gained valuable scripting skills to automate processes, analyse and visualise data, and perform numerical simulations.
Vegard obtained his PhD degree in applied mathematics from the University of Oslo and Simula Research Laboratory in 2019 and worked as a researcher at Simula between 2019 and 2023. In his research he worked with health data, mathematical models and computer simulations to understand fluid flow in the human brain. Both physical based (differential equations) and data driven (statistical, machine learning) models were used in his research.
In addition to his scientific contributions, Vegard served as the leader of the Scientific Computing section at Simula between 2021 and 2023 and obtained valuable skills in mentoring, leadership and communication. Furthermore, he has lectured courses on data science both at BI Norwegian Business School and at the University of Oslo, giving him a broad understanding of applications within data science as well as efficient communication on the subject.
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.
Åsmund is a senior software developer, project leader, and researcher, with more than 20 years of professional experience. After spending 13 years at Simula Research Laboratory, Norway's top-ranked ICT research institution, he founded Expert Analytics in 2013, together with Ola Skavhaug.
Through various positions in his career, he has obtained a broad set of technical and management skills, which he now put to good use as both CEO of Expert Analytics and Advisor to various clients. His main areas of technical expertise spans from advanced mathematical software development through web programming to scripting, and from administration of advanced ICT solutions and configuration management to operational work. Through education and practical hands-on experience he has developed strong analytical skills within his fields of expertise. Åsmund holds a PhD in Scientific Computing and a MSc in applied mathematics.
Founder and CEO of Expert Analytics. Enjoys developing small and large systems in a number of languages and environments. Makes sure that everyting is working well, both with clients and internally.