Data Science & Software Science

Partner for industry and research

Research at Software Competence Center Hagenberg (SCCH) concentrates on equal footing in Data Science and Software Science. The synergy of Data Science and Software Science at SCCH is an important success factor. 

As a COMET competence center, SCCH conducts cutting-edge research on an international level. Together with our scientific partners, especially Johannes Kepler University Linz, SCCH strives toward leadership in the future-oriented fields of digitalization and artificial intelligence.

 

Instandhaltungstage 2018

SCCH introduces Predictive Analytics Tool

From 10th to 12th April 2018, experts and practitioners will meet at the Instandhaltungstage in Salzburg. The motto of the event is "Excellent maintenance as THE engine for manufacturing companies".

IOT Flagship Project

Started successfully

The public kick-off of the Austrian flagship project IoT4CPS took place at TU Vienna on February 1, 2018.

New publication

In IEEE Software

In the January/February 2018 Issue of IEEE Software is a contribution of Atif Mashkoor and Miklos Biro available. It covers the topic Software Safety and Security Risk Mitigation in Cyber-physical Systems.

Long Night of Research

Experience research up close

On April 13th it's time again! Visitors can gain a unique insight into research.  At the Long Night of Research, the SCCH will show two different areas of application for software use. One example is how to predict the condition of a machine and optimize maintenance, and in the second example we show how to use data glasses optimally in production operations.

IoT4CPS Kick -Off Event

Austria's flagship project

The IoT4CPS project aims to develop guidelines, methods and tools for secure IoT-based applications in the areas of Connected & Autonomous Vehicles and Industry 4.0. IoT4CPS focuses on the development, production and operation of safe components and applications for connected and autonomous vehicles.The workshop will be held in Vienna, at 1st of February 2018.

(Junior) Research Engineer Computer Vision (m/f)

Job offer

We are looking for a (Junior) Research Engineer (f/m) to join our computer vision team at Software Competence Center Hagenberg with expertise in software development, machine (and deep) learning as well as in mathematical modelling or embedded vision.

Big / Stream Data Processing

  • Secure and Efficient Distributed Algorithms for Big Data
  • Heterogeneous Online Transfer Learning
  • Data Quality and Data and Model Management

Smart Data Discovery

  • Structure Learning
  • Causal Discovery
  • Trustworthy, Interpretable Models
  • Integration of Event / Log Data

 

Fault Detection and Identification

  • Fast (Online) Algorithms that Learn Partial System Models
  • Fault Detection and Prediction
  • Optimal Maintenance

Predictive Analytics and Optimization

  • Transfer Learning
  • Online Transfer Learning
  • Optimization and Control of Complex Tasks

Artificial Intelligence and Digitization

Deep learning in industry

In the course of the digital transformation, artificial intelligence (AI) and machine learning (ML) are suddenly on everyone's lips. Systems that learn independently from large amounts of data are reality. On November 16th, the Future Network Event will show you how these technologies can be used in a way that will benefit your bottom line. Speakers from SCCH will inform about the latest developments.

CfP: VST 2018

2nd Workshop on Validation, Analysis and Evolution of Software Tests

VST 2018 is an unique event bringing together academics, industrial researchers, and practitioners for exchanging experiences, solutions and new ideas in applying methods, techniques and tools from software analysis, evolution and reengineering to advance the state of the art in test development and maintenance.

International Conference on Learning Representations

Joint paper presented

The Data Analysis Systems (DAS) group and the FLLL of the Johannes Kepler University Linz cooperate in the field of  dissertations. The paper on Machine Learing/Deep Learning, which was presented at the ICLR 2017, originates from this cooperation.