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.
NLP Community Building - ComBi
SwissNLP would like to take concerted action to better network Swiss players from industry, science and administration in the field of Natural Language Processing (NLP). For this reason various activities are to be carried out until the end of 2025 such as expert group meetings, applied conferences, data ...
Brain Research International Data Governance & Exchange
The goal of this project is to develop an International Data Governance Framework (IDGF) that can advance responsible international brain research and innovation. This will start with the identification of the technical, legal, ethical and organizational challenges to IDGF and the development of pathways to address ...
Deep Dive ML on Simulated Enzyme-Electrolysis Performance
The goal of this pilot study is to research requirements needed to develop a computational model that simulates the fluidic and electro-biochemical dynamics in the power-to-liquid process in order to optimise the performance, efficiency and longevity of enzymes.
AI4REALNET: AI for REAL-world NETwork operation
The scope of AI4REALNET covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic management) modelled by networks that can be simulated, and are traditionally operated by humans, and where AI systems complement and augment human abilities. It has two main ...
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. ...
Intelligent planning for robot-based manufacturing
The proposed research seeks to merge data-driven methods, symbolic knowledge, and domain expertise to enhance the planning, optimization, and control of industrial robots and processes in robot-based manufacturing. By incorporating sensor data, we can leverage additional information to monitor and control industrial ...
Enabling Scientific Diplomacy: Preparation of the GESDA Neurotechnology Compass
The Geneva Science and Diplomacy Anticipator (GESDA) is developing the “Neurotechnology Compass” (the NeuroTech Compass – NTC). The NTC aims A tool aimed at equipping decision-makers with the necessary navigation tools to best support research in neuroscience and neurotechnology and their applications in society. By ...
ML-BCA: Machine Learning for Body Composition Analysis
The Centre for Artificial Intelligence (CAI) of the ZHAW, together with the Cantonal Hospital Aarau, has laid the foundations for machine learning-supported body composition analysis on image files of the KSA within the framework of preliminary studies and has achieved promising results. The aim of this project is ...
Digital Health Zurich – A practice lab for patient-centred clinical innovation
Digital Health Zurich researches digital health solutions in the hospital context and implements them efficiently and with practical relevance. Core topics are Patient Reported Outcome Measure (PROMs), remote monitoring, integrated care and related technologies as well as empowerment of patients and staff. Our ...
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. ...
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.