Research
Research Agenda
Our research agenda covers the following areas and is conducted within the confines of projects executed with industry partners:
- Database and Big Data technology
- Data Mining, Statistics and Predictive Modeling
- Machine Learning and Graph Analytics
- Information Retrieval and Natural Language Processing
- Business Intelligence and Visual Analytics
- Data Warehousing and Decision Support
- Communication and Visualization of Results
- Privacy, Security and Ethics
- Entrepreneurship and Data Product Design
R&D Projects
This list gets directly filled from ZHAW's project database. Not all projects may show up due to interlinkage aspects.
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Simulation of pedestrian and traffic flows
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Fighting bites with bytes: Promoting public health with crowdsourced tick prevention
Ticks are on the rise and transmit several infectious diseases, leading to serious illness or even death. The smartphone App “Zecke–Tick Prevention helps people, to remember the tick bite location and to check it for potential Lyme disease symptoms. In an interdisciplinary approach, ZHAW-scientists want to find out ...
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NQuest – Natural Language Query Exploration System
There is a huge amount of valuable information hidden in a company's database which is not easily accessible to business people. To query these databases, end users need to know the technical query language SQL as well as the database structure. However, typical end users do not have enough SQL skills to formulate ...
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User-Centric Privacy Policy: A GDPR-Compliant Policy Which Users Understand
The purpose of this project is to create a user-centric privacy policy (UCPP), applicable in a variety of settings (e.g., websites, hospitals, or banks), which is compliant with the General Data Protection Regulation (GDPR). Most importantly, the majority of users should be able to understand it and act accordingly. ...
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REFRACT – Repeat protein Function, Refinement, Annotation and Classification of Topologies
REFRACT is an international consortium aiming to extend our knowledge on the mechanism of tandem repeat protein (TRP) function and evolution, establishing a common classification and best practices. Starting from available state of the art computational tools and databases, it aims to drive a new level of TRP ...
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Smartstones - AI for plant breeding
Goal of the project is a feasibility study to evaluate the potential of diverse AI techniques for opimising plant breeding on the basis of morphological characteristics.
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Simulation & Optimization needs HPC
The simulation and optimization is predestined for high performance computing (HPC). Many computing operations are necessary and huge amounts of data are being generated. The requirements have also increased in recent years as the models become more complex. In addition, simulation-based optimization needs a large ...
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Development of Algorithms for the Analysis of Football Players and Game Situations based on Motion Data
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Prediction of Turnover in Gastronomy
How many guests will visit a restaurant and at what time of the day? Which menus will be ordered? Planning is absolutely crucial in gastronomy but not at all easy. It must be ensured that the correct amount of food is purchased and enough staff is present to run the shop. The planning which has been done intuitively ...
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Decision Support System for Predictive Maintenance of Laser Cutting Machines
A new decision support system for predictive maintenance of laser cutting machines is developed. The system provides a platform for condition monitoring, fault detection and prediction of the remaining useful life of systems and components as well as data-driven decision support and prescriptive recommendations for ...
SNF/NRP project: Bio-SODA
One of the major promises of Big Data lies in the simultaneous mining of multiple sources of data. This is particularly important in life sciences, where different and complementary data are scattered across multiple resources. To overcome this issue, the use of RDF/semantic web technology is emerging, but querying these systems often proves to be too complex for most users—thereby hampering wide development and adoption of these technologies.