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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Stability of self-organizing net fragments as inductive bias for next-generation deep learning
We recently released "A Theory of Natural Intelligence", proposing a possible key to the emergence of intelligence in biological learners. Goal of this fellowship is to develop a technical implementation of the concept of self-organizing netfragments within contemporary deep artificial neural nets. ...
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Towards a Voice-Based Chatbot for Language Learners (ChaLL)
We take first steps towards developing ChaLL, a voice-based chatbot that provides language learners with opportunities to practice speaking in both focused and unfocused task-based conversations and receive feedback, free from the time constraints and pressures of the traditional classroom setting. ...
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INODE4StatBot.swiss – Application of new algorithms for automatic natural language translation into database query language SQL (NL-to-SQL)
The goal of this project is to apply the major algorithms developed in the EU-Project INODE (Intelligent Open Data Exploration, https://www.inode-project.eu/) to Swiss Open Data. The focus is on developing multi-lingual extensions for so-called Natural Language to SQL systems (NL-to-SQL) where a natural language ...
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Master3D – 3D-Master for a Digitized Manufacturing Platform
We enhance Bossard's Real Time Manufacturing Services by automatically creating quotes for special parts. The core is an AI-created 3D Master that unifies all available part information, enabling pricing and feasibility evaluation for many manufacturing technologies incl. additive manufacturing. ...
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certAInty – A Certification Scheme for AI systems
Certification of AI Systems by an accredited body increases trust, accelerates adoption and enables their use for safety-critical applications. We develop a Certification Scheme comprising specific requirements, criteria, measures, and technical methods for assessing Machine Learning enabled Systems. ...
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DISTRAL: Industrial Process Monitoring for Injection Molding with Distributed Transfer Learning
We develop a distributed machine learning system to sort out defect plastic parts during production. Main challenge is the transferability of learnt process know-how from case to case; the solution builds on domain adaptation, continual data-centric deep learning and federated edge computing. ...
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OSR4H – Open Set Recognition for Hematology
Development of a Proof of Concept for visual Open Set Recognition (OSR) algorithms applied to a Hematology task, the classification of white blood cells.
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An experimental framework to allow evidence-based sustainability policymaking
This research project evaluates the feasibility of using a mathematical decision framework (based on the 2019 Nobel laureates in Economy who developed an experimental approach for improving policy in poverty through field experiments) in sustainability policy, and achieving a software-supported and data-driven ...
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AC3T – AI powered CBCT for improved Combination Cancer Therapy
The project enables a novel, combined, adaptive cancer therapy combining tumor treating field and radiation therapy due to significantly improved static (3D) and time-resolved (4D) low dose Cone Beam Computer Tomography images based on artificial intelligence image reconstruction algorithms. ...
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DISCAP – Digital Infrastructure for Sustainable Consumption and Production (UNEP)
The goal of this project is to lay the technological foundations for empowering various stakeholders to make fact-based decisions to achieve sustainable consumption and production. In particular, we will evaluate how various data science, machine learning and artificial intelligence methods can be used to extract ...
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.
