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 DBSCAN 0

DBSCAN

DBSCAN Parallel & Scalable DBSCAN Goetz, M., Bodenstein, C., Riedel, M.: HPDBSCAN – Highly Parallel DBSCAN, in conference proceedings of ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2015), Machine Learning in HPC Environments (MLHPC 2015) Workshop, November 15-20, 2015, Austin, Texas, USA [ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] [ MORE ] DBSCAN Applications Bodenstein, C., Goetz, M., Jansen, A., Scholz, H., Riedel, M.: Automatic Object Detection using DBSCAN for Counting Intoxicated Flies in the FLORIDA Assay, in conference proceedings of the 15th IEEE International Conference on Machine Learning and...

Morris Riedel Talks

Talks – Overview

Lectures Plenary Lecture or Keynote Address at an International Academic Conference Scientific Big Data Analytics – Practice & Experience, Invited Keynote, The International Conference on Cloud and Autonomic Computing (CAC 2014), September 8 – 12, 2014, Imperial College, London, UK Public Guest Lecture at a University outside of Iceland Selected Parallel and Scalable Methods for Scientific Big Data Analytics, Invited Talk, ZIH-Kolloquium, May 21, 2015, Technical University of Dresden, Germany Enabling Parallel and Scalable Tools for Scientific Big Data Analytics, Invited Talk, AixCAPE Spring Meeting 2015, May 6, 2015, RWTH Technical University of Aachen, Germany Bedeutung von Interoperabilität und Standards...

Deutscher Bundestag Impulsvortrag Kuenstliche Intelligenz Morris Riedel 0

Deutscher Bundestag Impulsvortrag Kuenstliche Intelligenz

Deutscher Bundestag Impulsvortrag Kuenstliche Intelligenz Deutscher Bundestag, Enquete-Kommission ‘Kuenstliche Intelligenz’ Berlin, Germany 2019-03-11 [ Slides ~4.86 MB (pdf) ] [ EVENT ] [ PRESS ] Video of my talk @ Deutscher Bundestag German federal parliament now at https://t.co/dcqT15JYPY discussing among #ArtificialIntelligence experts HAICU @helmholtz_en SMITH, ON4OFF & Modular Supercomputing by @DEEPprojects @fzj_jsc @fz_juelich @uisens @uni_iceland @Haskoli_Islands pic.twitter.com/YSzWHtpmru — Morris Riedel (@MorrisRiedel) March 21, 2019 Invited talk at Deutscher Bundestag – the German federal parliament – presenting artificial intelligence chances with examples of SMITH, ON4OFF & Modular Supercomputing by @DEEPprojects @fzj_jsc @fz_juelich @uisens @uni_iceland @Haskoli_Islands – talk at: https://t.co/xCDitaxS71 pic.twitter.com/S5VkSRacRQ —...

Morris Riedel Retail Analytics 0

Retail Analytics

Retail Analytics Kuenstliche Intelligenz Links (German Language) Strategie Künstliche Intelligenz der Bundesregierung, November 2018 [ MORE ] ON4OFF EU EFRE Project ON4OFF Team @PieperBeauty @paluno_se @adessoAG @INtelegenceGmbH @fz_juelich & ProXperts discuss with @ProfHeinemann using #ArtificialIntelligence in #Retail via #NLP & #ModularSupercomputing by @DEEPprojects @fzj_jsc @Haskoli_Islands @uisens @uni_iceland – https://t.co/xal4kRdWcy pic.twitter.com/kPIvhOQp5a — Morris Riedel (@MorrisRiedel) March 20, 2019 ON4OFF Project Team @paluno_se @adessoAG @INtelegenceGmbH @fz_juelich & ProXperts discuss with @ProfHeinemann selected #Retail use cases for @PieperBeauty using #MachineLearning & #DeepLearning with Modular Supercomputing driven by @fzj_jsc @Haskoli_Islands @uisens @uni_iceland pic.twitter.com/a5HtTTY4nb — Morris Riedel (@MorrisRiedel) March 7, 2019 ON4OFF Project Team @adessoAG...

2019-02-25 PRACE Tutorial Parallel and Scalable Machine Learning Morris Riedel 0

PRACE Tutorial – Parallel and Scalable Machine Learning

PRACE Tutorial: Parallel and Scalable Machine Learning Invited Tutorial PRACE Advanced Training Center, Juelich Supercomputing Centre, Germany 2019-02-25 – 2019-02-27 [ EVENT ] Lecture 1 – Parallel and Scalable Machine Learning driven by HPC (pdf, ~9,97 MB) Lecture 2 – Introduction to Machine Learning Fundamentals – Theory (pdf, ~12,9 MB) Lecture 3 – Introduction to Machine Learning Fundamentals – Practice (Jupyter Notebooks – request resources contacting m.riedel@morrisriedel.de) [Martin Schultz] Lecture 4 – Feed Forward Neural Networks (Jupyter Notebooks – request resources contacting m.riedel@morrisriedel.de) [Martin Schultz] Lecture 5 – Feed Forward Neural Networks (Jupyter Notebooks – request resources contacting m.riedel@morrisriedel.de) Lecture...

2019-02-18 SMITH ASIC Use Case Related Work VPH Morris Riedel 0

SMITH ASIC Use Case and Related Work Virtual Physiological Human

SMITH ASIC Use Case and Related Work Virtual Physiological Human SMITH ASIC AG2 Workshop RWTH Aachen University Clinic, Aachen, Germany 2019-02-18 [ Slides ~7.10 MB (pdf) ] SMITH Algorithmic Surveillance of Intensive Care Unit Patients (ASIC) workshop @UniklinikAachen discussing virtual patient models like @VPH_Institute using modular supercomputing of @DEEPprojects @fzj_jsc @fz_juelich @Haskoli_Islands @uisens @uni_iceland – https://t.co/xCDitaxS71 pic.twitter.com/3Cw2vKKBux — Morris Riedel (@MorrisRiedel) February 18, 2019

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

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...

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...