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
This list gets directly filled from ZHAW's project database. Not all projects may show up due to interlinkage aspects.
Designing Business Models for the IoT
This project aims at developing a business model simulation software for evaluating IoT business models. The holistic approach leverages advanced simulation methods and will create new revenue opportunities for Swiss manufacturing companies.
A top-down indicator of lean-green alignment in small and medium-sized enterprises
To address the challenge from global warming, the UNFCCC has given rise to several initiatives to channel financial capital into decarbonization efforts. Among investors, demand increasing for investment vehicles that offer both environmental sustainability as well as economic performance benefits. We aim to design ...
Confidential Data Analytics based on Trusted Execution Environments
Currently there is an unmet need for trust and privacy in multi-party data analytics (e.g. in cloud computing). A new solution approach using hardware-based trusted execution environments is called Confidential Computing. The Zurich-based and investor-backed startup decentriq is a provider of confidential analytics ...
Predicitve Waste Management for SBB Train Stations
We develop a system to optimize the waste collection and disposal on SBB's train stations. The new system will use a container fill level sensor network, a novel waste accumulation forecasting algorithm, and state of the art methods for simulation-based tour-planning.
Interscriber: Turning Dialogues into Actionable Insights
This project aims to fully digitize and automate the transcription of spoken dialogues. We will implement a software system, Interscriber, that takes an audio recording as input and creates text using algorithms for Speech-to-Text and Speaker Diarization. The text is further processed and corrected. Finally, ...
Prototypes for the Sustainable Digitisation of University Teaching
The COVID-19 Pandemy has forced higher education into fast forwarding their digitisation across the board. This creates valuable and relevant information for the sustainable digitization beyond the crisis mode. The project structures evidence-based digital teaching exsperiences and digital competences at the ...
Privacy-preserving confidential computing with trusted execution environments
When companies store their data in the cloud or share data with other organizations via the cloud, information security and data protection are based on trust, legal agreements and technical and organizational measures. "Confidential Computing" technology can ensure the confidentiality and protection of data in the ...
Acceptance of an app for contact-tracing of SARS-CoV-2 in the Swiss population
The survey of 1929 adults in Switzerland in the period from 17 - 26 April 2020 suggests that a large majority of the population in any case or probably intends to a) install an app for contact-tracing of SARS-CoV-2, b) report infections in the app and c) comply with the app's request for contact reduction or ...
PiaBreed: Machine Learning for automated ovulation and birth monitoring in horses
The project comprises the tasks of a comprehensive data collection (Piavita/ University of Bern) and the development of a mobile, non-invasive system (Piavita/ZHAW) for veterinarians and breeders. The goal is to collect important vital data and to develop a new algorithm scheme with which - ovulation in mares can ...
INODE - Intelligent Open Data Exploration
Data growth and availability as well as data democratization have radically changed data exploration in the last 10 years. Many different data sets, generated by users, systems and sensors, are continuously being collected. These data sets contain information about scientific experiments, health, energy, education ...
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.