Morris Riedel Teaching 0

Teaching – Overview

Teaching Experience Adjunct Lecturer, Lecturer, Senior Lecturer or Professor University Course: Cloud Computing and Big Data – Parallel and Scalable Machine Learning and Deep Learning, School of Engineering and Natural Sciences, University of Iceland, Iceland, Fall 2018 [ MORE ] University Course: High Performance Computing – Advanced Scientific Computing, School of Engineering and Natural Sciences, University of Iceland, Iceland, Fall 2017 [ MORE ] University Course: Cloud Computing and Big Data – Internet-based Shared Computing & Data Processing, School of Engineering and Natural Sciences, University of Iceland, Iceland, Spring 2017 University Course: High Performance Computing B – High Productivity Processing...

Morris Riedel Publications

Publications – Overview

Book Chapters Peer-reviewed Publications by the World’s most respected Academic Publishers Riedel, M.: e-Science Infrastructure Interoperability Guide: The Seven Steps Toward Interoperability for e-Science, Springer Book Series Computer Communications and Networks, Guide to e-Science – Next Generation Scientific Research and Discovery, 2011, pp. 233-264, ISBN 978-0-85729-439-5 [ BOOK SERIES ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] Streit, A., Erwin, D., Lippert, T., Mallmann, D., Menday, R., Rambadt, M., Riedel, M., Romberg, M., Schuller, B., Wieder, P.: UNICORE – From Project Results to Production Grids, Elsevier Book Series Advances in Parallel Computing, Vol 14, 2005, pp. 357-376, ISBN...

Morris Riedel Service 0

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 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 2018), October 29 – November 1st, 2018, Amsterdam, the Netherlands [ Web Page ] Program Committee Member 14th International Workshop on Scheduling and Resource...

Morris Riedel Research 0

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 Theses 0

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 – 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

2019-02-15 ON4OFF Projekt Juelich Supercomputing Centre Rolle und Ziele Morris Riedel 0

ON4OFF Projekt – Juelich Supercomputing Centre – Rolle und Ziele

ON4OFF Projekt – Juelich Supercomputing Centre – Rolle und Ziele ON4OFF Vision Workshop Adesso, Essen Germany 2019-02-15 [ Slides ~1.69 MB (pdf) ] ON4OFF Project Team @adessoAG @INtelegenceGmbH @paluno_se @PieperBeauty @fz_juelich explores with @ProfHeinemann how to improve retail using also #MachineLearning & modular supercomputing by @DEEPprojects @fzj_jsc @uisens @Haskoli_Islands @uni_iceland – https://t.co/xCDitaxS71 pic.twitter.com/urAlzECiAx — Morris Riedel (@MorrisRiedel) February 16, 2019

2019-01-21 DEEP EST Tutorial Machine Learning and Modular Supercomputing Content 0

DEEP-EST Tutorial – Machine Learning and Modular Supercomputing

DEEP-EST Tutorial – Machine Learning and Modular Supercomputing HIPEAC Conference 2019 Conference Centre, Valencia, Spain 2019-01-21 [ Event ] Abstract The fast training of traditional machine learning models and more innovative deep learning networks from increasingly growing large quantities of scientific and engineering datasets (aka ‘Big Data‘) requires high performance computing (HPC) on modern supercomputers today. HPC technologies such as those developed within the European DEEP-EST project provide innovative approaches w.r.t. processing, memory, and modular supercomputing usage during training, testing, and validation processes. Materials [ Lecture 1: Modular Supercomputing and Machine Learning – Welcome to HiPEAC Tutorial – Slides ~1.12...

2019-01-16 Overview German HPC Resources and Facilities Helmholtz Morris Riedel 0

Overview of German HPC Resources and Facilities – Helmholtz

Overview of German HPC Resources and Facilities – Helmholtz CIFAR – Helmholtz Association Workshop – Artificial Intelligence for Neuroscience Mars Discovery District, Toronto, Canada 2019-01-16 [ Slides ~15.61 MB (pdf) ] [ Event ] Thanks to @CIFAR_News organizers for a great AI for Neuroscience event last week & crafting ideas with A. Evans to connect to CBRAIN & talking about German High Performance Computing resources in @helmholtz_en @helmholtz_de @fzj_jsc @fz_juelich – slides: https://t.co/xCDitaxS71 pic.twitter.com/5NDH1Yq0ex — Morris Riedel (@MorrisRiedel) January 20, 2019

2019-01-15 On Parallel and Scalable ML and DL Research Morris Riedel 0

On Parallel and Scalable Machine and Deep Learning Research

On Parallel and Scalable Machine and Deep Learning Research CIFAR – Helmholtz Association Workshop – Artificial Intelligence for Neuroscience Mars Discovery District, Toronto, Canada 2019-01-15 [ Slides ~9.31 MB (pdf) ] [ Event ] Talk at @CIFAR_NEWS @helmholtz_de @helmholtz_en event AI for Neuroscience about my @uni_iceland @fzj_jsc @fz_juelich @DEEPprojects machine/deep learning research group results & neuroscience options; T. Dickscheid presents @HumanBrainProj research; slides: https://t.co/xCDitaxS71 pic.twitter.com/wvbEHBYQHq — Morris Riedel (@MorrisRiedel) January 18, 2019

Morris Riedel Journals 0

Journals

Academic Journals ISI Journals with a High Impact Factor ISI journals are those international scientific journals documented in the Institute for Scientific Information (ISI) databases under the auspices of Thomson Reuters. IEEE Transactions on Parallel and Distributed Systems (TPDS), Impact Factor: 3.971 (2018-12-30) [ JOURNAL ] Springer Journal of Grid Computing, Impact Factor: 2.800 (2018-12-30) [ JOURNAL ] IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), Impact Factor: 2.777 (2018-12-30) [ JOURNAL ] Other ISI Journals & SCOPUS Journals Scopus is the largest abstract and citation database of peer-reviewed literature: scientific journals, books and conference...

Fog Detection Using Deep Learning 0

Fog Detection using Deep Learning

Fog Detection using Deep Learning See also Research activities driven by Ernir Erlingsson: http://www.ernire.org 2018-12-03 Workshop @ Jülich Supercomputing Centre, Germany Welcome Address – Juelich Supercomputing Centre (Morris Riedel) Slides PDF (10,2 MB) KNMI Data Lab (Jan Willem Noteboom) Slides PDF (7,3 MB) Fog Detection from Camera Images Experiences at KNMI (Andrea Pagani) Slides PDF (5,8 MB) DEEP-EST EU Project & JSC (Ernir Erlingsson) Slides PDF (9,5 MB) Research Results: To be published shortly Research Results to be published shortly #DeepLearning Practice & Experience: Deep Learning & Fog Detection – Research of PhD student E. Erlingsson @ernire, J. W. Noteboom...

2018-11-14 Parallel and Scalable Machine and Deep Learning at JSC Morris Riedel 0

Parallel and Scalable Machine and Deep Learning at JSC

Parallel and Scalable Machine and Deep Learning at JSC NCSA Affiliates Meeting International Supercomputing Conference 2018, Dallas, Texas, USA 2018-11-14 [ Slides ~4.76 MB (pdf) ] Thanks for discussions at the #SC18 NCSA @NCSAatIllinois affiliates meeting & invitation to talk about @DEEPprojects & ML/DL at JSC @fzj_jsc @fz_juelich & our international lab idea with University of Iceland @uni_iceland @uisens @Haskoli_Islands – slides: https://t.co/xCDitaxS71 pic.twitter.com/hAykWjDT1P — Morris Riedel (@MorrisRiedel) November 17, 2018