Djura studied Artificial Intelligence at the University of Amsterdam (UvA) and received her Msc in 2015. After graduation she as worked as a Data Science consultant at Xomnia, Java developer at Eagle Eye networks, before becoming a Data Engineering consultant at Eonics. As a consultant she has seen big data being applied at various companies such as Nuon, Nationale Nederlanden, NDW, and Sanoma. She also worked on a R&D project for developing drones that can count warehouse inventory. Her focus was mainly on how to recognize shelf inventory from camera images.
Djura joined the Escience center in 2020 to work on the Big Data & Health projects.
Jesus studied Computer Science and Engineering at the Carlos III University of Madrid and has an MSc in Artificial Intelligence. Over the past 10 years, he has been developing multi-platform web applications with a focus on combining strong design aesthetics with technical know-how. During his career he has partnered with researchers and designers to develop and deliver new features, to translate concepts into living, breathing prototypes, interactions, animations and details to deliver the best user experience.
Breixo Soliño Fernández obtained his Computer Engineering degree at the University of Santiago de Compostela in 2013. After graduation, he worked for two years as an R&D engineer at Imatia Innovation, a small technological company.
In 2017 he came to the Netherlands to study a MSc in Artificial Intelligence at Utrecht University, and he is currently pursuing an internship at the eScience Center.
His main interests lie in autonomous robots, cognitive science, and the overlap between both disciplines. Other interests cover topics such as teaching and computer vision.
Ou Ku studied Geodesy in Central South University (China) where he obtained his BSc and discovered his interest in Earth Observation (EO). He continued his study in Delft University of Technology (TUDelft) and obtained a MSc degree in Geosciences and Remote Sensing. For his Master thesis, he focused on a specific EO technology: Interferometric Synthetic Aperture Radar (InSAR), which is applied for large-scale ground deformation monitoring. After his graduation in 2017, he continued his interest in InSAR and worked in an InSAR company named SkyGeo for two and half years.
Ou Ku has research interest in scientific computation and visualisation for Earth Observation applications. He also has interest in Deep Learning and GPU acceleration techniques.
Robin has a background in Physics and High Performance Computing, with a particular focus on the biophysical and materials simulation domains.
As a postdoctoral researcher at University College London he worked on the optimization of HemeLB, a high performance lattice-Boltzmann code for simulations of blood flow, integrating it into a clinical pipeline (CERREBRAL project, Qatar), and overseeing a complex coupling of two instances representing the human arterial and venous trees, with an external heart model (under the EU CompBioMed project). As part of the EU COMPAT project he co-designed the SCEMa material properties prediction model, cyclically coupling Molecular Dynamics simulations to a Finite Element macroscale model, for which he designed a graph based clustering algorithm to drastically reduce the number of MD simulations required. Under the EU VECMA project he led development on the EasyVVUQ python framework for Validation, Verification and Uncertainty Quantification of multiscale applications.
During his PhD at the University of Leeds, he wrote the Fluctuating Finite Element Analysis (FFEA) code, modelling molecular motors involved in the beating of flagella such as sperm tails. He obtained a master’s in Physics from the University of Edinburgh in 2010.
Robin joined the Netherlands eScience Center in February 2020 as senior eScience research engineer.
Arnold graduated in Molecular Biology (2004, Comenius University in Bratislava, Slovakia). As an exchange student at Wageningen University and Research (WUR) in the Netherlands, he followed courses in bioinformatics and worked on his masters thesis in bioinformatics (Comparative genome analysis of White spot syndrome virus isolates).
He started his PhD research on comparative genomics of fungi and later focused on (phylogenetic) sequence-based clustering methods and data integration at the Laboratory of Bioinformatics, WUR (2009). In close collaboration with SURFsara, he used the Dutch Life Science Grid to compute a comprehensive matrix of corresponding genes (called orthologs) for all species with sequenced genomes. For this, he developed an efficient graph heuristics and an integrated protein resource.
As a postdoctoral researcher at the Department of Ecology and Evolution, University of Lausanne, Swiss Institute of Bioinformatics, he focused on genome-wide detection of positive selection in animal genomes using the Swiss Multi-science Computing Grid. Arnold returned to the Netherlands where he joined the Department of Genetics, Erasmus University Medical Center to study cellular effects of (non-)ionizing radiation using mass spectrometry-based proteomics.
In 2015 Arnold joined the team at the eScience Center. His interests include optimized (linked) data handing, analytics and/or efficient scientific workflows.
Alessio studied Computer Science at the University of L’Aquila (Italy), where he obtained a BSc and MSc (cum laude). He also obtained a MSc in Computer Science from the Vrije Universiteit (VU) in Amsterdam.
In Amsterdam he developed an interest in high-performance and parallel computing and began working with Graphics Processing Units (GPUs) for his master’s project, under the supervision of Prof. Dr. Rob van Nieuwpoort and Prof. Dr. Ana Lucia Varbanescu.
After his graduation he worked for over a year as a researcher at the VU, where he worked on the acceleration, with GPUs and other accelerators, of radio astronomy algorithms. He later started a PhD at the VU, on the topic of accelerating radio astronomy algorithms using many-core accelerators and auto-tuning, under the supervision of Prof. Dr. Henri Bal and Prof. Dr. Rob van Nieuwpoort.
During his PhD he also spent a year working as a scientific programmer at ASTRON, the Netherlands institute for radio astronomy, where he worked on the real-time pipeline for ARTS, the Apertif Radio Transients System. He is expected to defend his PhD at the VU in the first half of 2017. His research interests include high-performance and parallel computing, algorithms, and auto-tuning; his reference programming languages are C++ and OpenCL.
Alessio joined the Netherlands eScience Center in February 2017.
Christiaan has studied Psychology, Physics and Artificial Intelligence, all at the University of Amsterdam (UvA). Christiaan received his MSc in both Psychology and Artificial Intelligence, track Intelligent Systems. In his thesis he applied reinforcement learning to the problem of learning new behavior in the field of robotics. His specialties include machine learning, pattern recognition, computer vision and reinforcement learning.
During and after his study, he worked at Conclusion Learning Centers developing a Learning Management System (LMS). For this system he developed various new functionalities. These include a recommender system that recommends users products based on their previous behavior and setting up new catalog search functionality using Elastic Search.
In 2013 Christiaan joined the Netherlands eScience Center as an eScience Engineer to work on the eEcology project.
Maarten studied Computer Science at the VU University in Amsterdam, where he specialized in Multimedia Applications. His Master’s thesis focused on visualization of the inner workings of the Ibis Complex HPC framework. During his studies, Maarten worked in IT support at the Faculty of Science at the VU University for 6 years, helping researchers to use the faculty’s computing services to their full extent. During this time, he also engaged in some early eScience by parallelizing his code to verify a Math algorithm on a large scale.
After graduation, Maarten was employed by the VU University as a Scientific Programmer to continue his work in visualization. His work was used to promote the Ibis eScience framework and a sample application in Astrophysics at the Supercomputing conference in Seattle in 2011. He also played a major role in the overhaul of the Computer Graphics course at the VU University, by introducing a framework for OpenGL 3+ and GLSL shader programming.
Today, Maarten is employed by the Netherlands eScience Center as a core team eScience Engineer, where he also focuses on visualization.
Vincent graduated in Human kinetic technology (BEng) at The Hague University of Applied Sciences and in Human movement sciences (MSc with cum laude) at the VU University in Amsterdam. In 2008 Vincent moved to England to complete a PhD in Epidemiology at the MRC Epidemiology Unit within the University of Cambridge. Vincent did a post-doc at the Institute of Cellular Medicine within Newcastle University.
Central theme of Vincent’s work has been the development of scientific software and algorithms to process data from wearable movement sensors (accelerometers). Vincent pioneered the analysis of data collected with human wrist-mounted high-resolution accelerometers that have been implemented since 2007 in population research on daily physical activity and sleep: His algorithms for movement sensor calibration, sensor wear detection, and signal aggregation are now used in almost every study that uses these sensors in the world. He released his code as open source software in R package GGIR. At the eScience Center Vincent has been working on machine learning (incl. deep learning) models for Epilepsy detection from EEG signals, emotion recognition from audio-visual data, and text. Vincent worked full time at the Netherlands eScience Center between June 2015 and April 2019, and nowadays works mainly as independent consultant, please visit www.movementdata.nl for more information.