Research of Information Technology
At the Information Technology group, our mission is to advance the field of smart systems engineering and informatics through education, research, and collaboration.
Mission
We strive to provide our students with the knowledge and skills they need to become leaders in the fast-changing world of data science, big data, and artificial intelligence. We conduct cutting-edge research that pushes the boundaries of knowledge and addresses real-world challenges in food and health, business, and society. We work closely with industry, government, and other academic institutions to create a vibrant ecosystem of innovation, where our ideas can have a tangible impact on people's lives. We are committed to excellence, diversity, and inclusion, and we believe in the power of technology to create a better future for all.
Vision
As the technological landscape rapidly evolves, the rise of smart and interconnected systems presents exciting opportunities for innovation and growth across industries. Incorporating cutting-edge technologies such as communication and network tech, cloud computing, the internet of things, and robotics, these systems demand advances in systems engineering, software engineering, information technology, and artificial intelligence. Our chair group is committed to leading the way in the development of smart systems and system-of-systems engineering, building on the substantial progress we've already made. We envision a future where our research drives progress in these areas, enabling the creation of highly advanced systems with greater functionality and performance than the sum of their parts. Through collaboration and innovation, we will work to harness the power of these smart systems to improve people's lives, enhance their well-being, and foster sustainable development.
Our objectives
In keeping with our vision and mission, we have set out the following objectives:
- To identify, analyse, and understand the latest developments and challenges in smart systems and system-of-systems engineering.
- To develop cutting-edge concepts, methods, and tools for smart systems and system-of-systems engineering in the life sciences application domains.
- To apply and evaluate the approaches we develop to ensure they are effective in addressing the unique challenges of the life sciences application domains.
Research Approach
Our main research strategy is centered on the industry-as-laboratory approach, where we collaborate directly with relevant groups at Wageningen University and research centers, as well as corresponding industrial partners.
This approach involves active analysis of existing life sciences application domains, which can be done reactively or proactively. Through this analysis, important research problems will be identified that are relevant both from a state-of-the-art perspective and to the stakeholders in the problem domain. Once the relevant research problems have been agreed upon, research is carried out interactively with constant feedback from the application domain stakeholders. Early research results can be quickly validated within a real industrial context, and this ongoing interaction ensures that research stays relevant and useful to the problem domain stakeholders. This approach enables us to focus our research efforts on problems that have a real-world impact and to develop practical solutions that can be readily implemented in industry.
Values
The group embraces several core values that guide our actions and decisions, including a commitment to excellence, performance-driven outcomes, collaboration, diversity, integrity, and accountability. We strive to achieve excellence in our research, education, and project acquisition, recognizing the importance of delivering high-quality results that have real-world impact.
In addition, we value integrity, collaboration and teamwork, recognizing that our collective expertise and perspectives are key to solving complex problems and driving innovation. We promote a culture of inclusivity and diversity, recognizing that a range of perspectives and experiences can foster creativity, critical thinking, and better outcomes. We are committed to providing a welcoming and respectful environment for all members of our community.
We also embrace accountability, taking responsibility for our actions and decisions, and being transparent in our communications and operations. We value integrity, ethical behavior, and respect for intellectual property rights. Finally, we encourage professional development, recognizing that continuous learning and growth are essential to achieving our goals and staying at the forefront of our field.
Facilities
The INF group at Wageningen University & Research has established three distinct labs: the Creative Technology Lab, the Social Drones Lab, and the Research Software Engineering Lab.
Creative Technology Lab
This lab provides a space for students and researchers to experiment with new forms of interactive media, such as virtual and augmented reality, generative art, and interactive installations. The lab is equipped with cutting-edge technology such as 3D printers, sensors, and microcontrollers to facilitate the creation of new and innovative projects. The lab also collaborates with external partners and organizes events to showcase the creative output of its members.
Digital Twin Lab
The Digital Twin (DT) Lab advances DT technology as a core methodology for designing, optimizing, and operating systems across scales and domains, from cities to agriculture and robotics to biology. It focuses on standardizing DT concepts with reference architectures, AI-driven modelling, and quality frameworks while developing an open-source DT framework. The lab applies DTs in fields like greenhouse management and energy grids, aiming for high maturity and seamless integration. Additionally, it showcases real-world applications, such as greenhouse demonstrators. With a team of experts in AI, modelling, and software engineering, the lab collaborates with researchers and industry to push DT innovation forward, aiming to ultimately make DTs accessible and transformative across all sectors.
AI for Research Software Engineering Lab
This lab is focused on developing high-quality research software for the scientific community. The lab provides services such as code development, testing, and maintenance to support researchers in their work. The lab is staffed by experienced software engineers who work closely with researchers to ensure that their software is efficient, reliable, and well-documented. The lab also provides training and education in best practices for research software engineering. Visit us.
Research themes
Our research is centered around five general themes, and seven applied themes.
General themes:
- Systems Engineering
- Socio-Technical Systems
- Data Science
- Artificial Intelligence
- Software Engineering
Applied themes:
- Energy Informatics
- Health Informatics
- Immersive Technology
- Computational Social Science
- Supply Chain Informatics
- Precision Agriculture
- Research Software Engineering
General themes
Systems engineering
A holistic systems thinking approach is adopted to cope with the complex problems. The group focuses on understanding the underlying principles but also on creating smart systems and artifacts. To design, develop, and operate smart systems, a systems engineering approach that integrates multiple disciplines is adopted. This involves the application of engineering and management principles to the planning, design, implementation, testing, and maintenance of smart systems.
Socio-technical systems
Smart systems usually include and are operated by humans (within (virtual) organizations) following implicit or explicit processes. In this context, we focus on aspects of socio-technical systems for addressing the interaction between society/individuals and technology. Social simulation, using simulation gaming and agent-based modelling, is a prominent research method we use for investigating the emergent dynamics of socio-technical systems. This allows connecting agent behavior with emergent system pattern. Further, we aim to focus on human-centered, responsible AI.
Data science
Smart systems usually have to deal with large data sets that are captured, pre-processed, and used to extract relevant information and knowledge to support the overall smart decision-making process. Here, we focus on various data science approaches such as data mining, statistical analysis, and machine learning.
Artificial intelligence
Artificial intelligence is a key enabler for smart systems and system of systems engineering. In this context, we focus on various artificial intelligence approaches such as machine learning, deep learning, reinforcement learning, and natural language processing.
Software engineering
For engineering smart systems and systems of systems, it is essential to design, implement, test, and maintain the software that controls the system. Particular topics in this context include software architecting, software ecosystems, model-driven development, parallel computing, product line engineering, and middleware.
Applied themes
Energy informatics
This research domain focuses on the use of information and communication technologies to optimize the production, distribution, and consumption of energy. The goal is to make energy systems more efficient, reliable, and sustainable.
Health informatics
This domain deals with the use of information and communication technologies to improve the quality, safety, and efficiency of healthcare. It covers a wide range of topics, including electronic health records, clinical decision support systems, telemedicine, and medical imaging.
Supply chain informatics
This research area focuses on the use of information and communication technologies to optimize the management of supply chains. It covers topics such as inventory management, logistics, and transportation.
Immersive technology
This research area explores the use of virtual and augmented reality, haptics, and other immersive technologies to create more engaging and effective learning, training, and entertainment experiences.
Research software engineering
This area of research focuses on the development and optimization of software for scientific research. It covers topics such as software design, development, testing, and maintenance.
