Prof. Dr. - Ing. Morris Riedel

Morris Riedel Cloud Computing 0

Research

Cloud Computing

Cloud Computing Gaia-X Cloud Official English Material

Morris Riedel Teaching 0

Teaching

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...

Morris Riedel Research 0

Research

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...

Morris Riedel Publications

Publications

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...

Morris Riedel Service 0

Service

Service – Overview

Organisation of International Scientific Conferences Topic Chair Data Management, Analytics and Deep Learning 25th Euro-Par Conference, August 26-30, 2019, Goettingen, Germany [ Web Page ] Program Committee Member The 21st IEEE International Conference on High Performance Computing and Communications (HPCC-2019), August 10-12, 2019, Zhangjiajie, China [ Web Page ] Program Committee Member 8th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2018), December 11-13, 2018, Melbourne, Australia [ Web Page ] Program Committee Member 9th Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE 2018), held in conjunction with the 14th IEEE International Conference on e-Science (e-Science...

Morris Riedel Theses 0

Theses

Theses – Overview

Theses Proposals I’m always open to proposals for bachelor, master, or doctoral thesis topics that are along the lines of my research interests. Feel free to contact me for details. Doctoral Theses [In Progress] Deep Learning Application Co-Design on Innovative HPC Architectures Ernir Erlingsson, Doctoral Thesis University of Iceland, School of Engineering and Natural Sciences (SENS), Iceland Phd student @ernire Ernir Erlingsson of @Haskoli_Islands alongside other data-driven & HPC application specialists explain technology experts at the @DEEPprojects F2F meeting how to take advantage of the modular supercomputing concept implemented by @fzj_jsc pic.twitter.com/aby8UE95l9 — Morris Riedel (@MorrisRiedel) May 8, 2018 Today...

Morris Riedel Media 0

Media

Media – Overview

2017 Invited Tutorial – Introduction to Machine Learning Algorithms Morris Riedel Ghent University, six lectures including exercises 2017-11-23 – 2017-11-24 [ Event ] Lecture 1 – Machine Learning Fundamentals Lecture 2 – Unsupervised Clustering and Applications Lecture 3 – Supervised Classification and Applications Lecture 4 – Classification Challenges and Solutions Lecture 5 – Regularization and Support Vector Machines Lecture 6 – Validation and Parallelization Benefits

Morris Riedel Biography 0

Biography

Biography

Biography Executive Summary Prof. Dr. – Ing. Morris Riedel is an Adjunct Associate Professor at the School of Engineering and Natural Sciences of the University of Iceland. He received his PhD from the Karlsruhe Institute of Technology (KIT) and works in parallel and distributed systems since 15 years. He previously held various positions at the Juelich Supercomputing Centre of Forschungszentrum Juelich in Germany. At this institute, he is also the head of a specific scientific research group focused on ‘High Productivity Data Processing’ and a cross-sectional team ‘Deep Learning’. Professional Networks and Associations Institute of Electrical and Electronics Engineers (IEEE)...

Nature Journals Morris Riedel 0

Publications

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 Morris Riedel 0

Teaching

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...

UNICORE 6 Recent and Future Advancements 0

Publications

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 0

Publications

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...

2019-12-13 Introduction To HPC and Quantum Computing for AI Morris Riedel 0

Teaching

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...

2019-12-02 Collaboration in the Context of Helmholtz Artificial Intelligence Morris Riedel 0

Talks

Collaboration in the Context of Helmholtz Artificial Intelligence

Collaboration in the Context of Helmholtz Artificial Intelligence Workshop for Joint Artificial Intelligence Strategy of Heinrich Heine University Duesseldorf & Forschungszentrum Juelich House of Heinrich Heine University Duesseldorf, Germany 2019-12-02 [ Slides ~11.2 MB (pdf) ] Presenting initial success stories of @helmholtz_ai @helmholtz_de #AI & cooperation at @HHU_de in #AI & #neuroscience with T.Dickscheid @dickscheid & S.Eickhoff @INM7_ISN @fz_juelich @fzj_jsc @DEEPprojects @Haskoli_Islands @uni_iceland @uisens .slides: https://t.co/H8Kh8rx327. pic.twitter.com/cqnrgo21cG — Morris Riedel (@MorrisRiedel) December 10, 2019 Sieh dir diesen Beitrag auf Instagram an Presenting initial success stories of @helmholtz_de #AI & cooperation at @hhubeichten in #AI & #neuroscience with T.Dickscheid & S.Eickhoff...