Cloud Computing
Cloud Computing Gaia-X Cloud Official English Material
Nature Journals
Nature Journals Nature Biotechnology Bray, N., Pimentel, H., Melsted, P., Pachter, L.: Near-optimal probabilistic RNA-seq quantification, Nature Biotechnology Vol. 34, pages 525–527, 2016 Abstract: We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in
Master of Data Science
Master of Data Science Existing Programs Online Portal, Master’s in Data Science Portal [ Master’s in Data Science Portal ] Lists many different Master of Data Science Programs and many of those as sponsored and require more Information to receive more Information. Online Master’s Degree in Data Science, Online Master’s Degree in Data Science [ Online Master’s Degree in Data Science ] Adressed to companies: ‘you’ll focus on helping your company solve problems by creating machine learning algorithms to examine and manipulate data’ Drexel’s online data science master’s is a compilation of computer science and information systems. Allows to choose...
Teaching – Overview
Teaching Experience Adjunct Lecturer, Lecturer, Senior Lecturer or Professor University Course: High Performance Computing – Advanced Scientific Computing, REI105M, School of Engineering and Natural Sciences, University of Iceland, Iceland, Fall 2019 [ MORE ] University Course: Cloud Computing and Big Data – Parallel and Scalable Machine Learning and Deep Learning, REI504M, School of Engineering and Natural Sciences, University of Iceland, Iceland, Fall 2018 [ MORE ] University Course: High Performance Computing – Advanced Scientific Computing, REI105M, School of Engineering and Natural Sciences, University of Iceland, Iceland, Fall 2017 [ MORE ] University Course: Cloud Computing and Big Data – Internet-based...
Research – Overview
Research Areas Research of the high productivity data processing research group at Forschungszentrum Juelich – Juelich Supercomputing Centre and University of Iceland focuses on application-driven parallel and scalable machine learning methods including related areas such as feature engineering, statistical data mining, and innovative deep learning techniques. In our projects we are cooperating with academic research groups worldside as well as with selected industry companies including the support of start-ups. Additional funding sources are the European Union or the German Federal Ministry of Education and Research. If you are interested in one of these research topics please contact me by email...
Publications – Overview
Theses Candidate’s or Master’s thesis Riedel, M.: Design and Evaluation of a Collaborative Online Visualization and Steering Framework for e-Science Application in Grids, Master Thesis (2007), University of Hagen, Berichte des Forschungszentrum Juelichs, 2007 [ JUSER ] Riedel, M.: Prospects and Realization of Flexible Service Offers in a Grid Environment, Diploma Thesis (2004), University of Applied Sciences Cologne, Berichte des Forschungszentrum Juelichs, 2004 (Note: 6-month diploma theses are the German pre-Bologna equivalent of master’s theses) [ JUSER ] Doctoral thesis Riedel, M.: Design and Applications of an Interoperability Reference Model for Production e-Science Infrastructures, PhD Thesis (2012), Karlsruhe Institute of...
UNICORE 6 Recent and Future Advancements
UNICORE 6 Recent and Future Advancements Streit, A., Bala, P., Beck-Ratzka, A., Benedyczak, K., Bergmann, S., Breu, R., Daivandy, J., Demuth, B., Eifer, A., Giesler, A., Hagemeier, B., Holl, S., Huber, V., Lamla, N., Mallmann, D., Memon, A.S., Memon, M.S., Rambadt, M., Riedel, M., Romberg, M., Schuller, B., Schlauch, T., Schreiber, A., Soddemann, T., Ziegler, W.: UNICORE 6 Recent and Future Advancements, Springer Journal of Annals of Telecommunications, Vol 65 (11-12), 2010 [ JOURNAL ] [ DOI ] [ JUSER ] [ GOOGLE SCHOLAR ] [ RESEARCHGATE ] Abstract: UNICORE is a European Grid Technology with more than 10 years...
Smart Data Analytics Methods for Remote Sensing Applications
Smart Data Analytics Methods for Remote Sensing Applications Cavallaro, G., Riedel, M., Benediktsson, J.A., Goetz, M., Runarsson, T., Jonasson, K., Lippert, T.: Smart Data Analytics Methods for Remote Sensing Applications, in conference proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2014), July 13-18, 2014, Quebec City, Canada [ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] Abstract: The big data analytics approach emerged that can be interpreted as extracting information from large quantities of scientific data in a systematic way. In order to have a more concrete understanding of this term we refer to...
Introduction to HPC and Quantum Computing for AI Applications
Introduction to HPC and Quantum Computing for AI Applications Invited Training Course organized by Obuda University and Parallel and Distributed Systems Lab MTA Sztaki, Budapest, Hungary 2019-12-13 Materials [ Overall Lecture: Introduction to HPC and Quantum Computing for AI Applications – Slides ~38.7 MB (pdf) ] Slides available of #HPC #QuantumComputing #QuantumAnnealing @dwavesys for AI Applications training @SZTAKI_LPDS using Modular Supercomputing @fz_juelich @fzj_jsc @helmholtz_ai @helmholtz_de @Haskoli_Islands @uni_iceland @uisens @DEEPprojects.slides: https://t.co/bZsgQ2qqaz.. pic.twitter.com/ze95rTzhwh — Morris Riedel (@MorrisRiedel) December 20, 2019 Sieh dir diesen Beitrag auf Instagram an Slides available of #HPC #QuantumComputing #QuantumAnnealing D-Wave Systems for AI Applications training at MTA Sztaki...