Cybercriminals and malicious actors are increasingly using AI to spread disinformation at scale – for example, by generating fake news articles and emails, or manipulating social media posts that deceive both people and systems.

AI:SECURITY combines advanced AI technologies (such as Natural Language Processing) with cutting-edge cybersecurity research to develop intelligent systems that can detect and prevent such threats. For instance, imagine an AI model that identifies a phishing email by analyzing both its content and context.

The project both aims to defend against attacks and ensure that AI systems themselves remain secure – e.g. by protecting LLMs from being hijacked or misused by malicious actors in societal applications, such as chat bots. This is a vital step toward building a safe and secure digital society. 

Professor Johannes Bjerva

Tenure track adjunkt Qiongxiu (‘Jane’) Li

Jens Myrup Pedersen

Psychopathology is on the rise among young people, and identity disturbance is one of the key early markers of its development.

AI:MIND aims to develop conversational AI that supports young people in expressing, structuring, and reflecting on their thoughts, feelings, and experiences—ultimately helping them gain a clearer sense of who they are. The system will also be designed to recognize early signs of identity-related distress, such as uncertainty about one’s values.

The goal is to provide early, preventive, and easily accessible support for young people, while also assisting professionals in identifying and engaging effectively with those in need.

Lektor Majse Lind

Professor Niels van Berkel

Thomas Dyhre Nielsen

Animals and plants interact in complex networks performing key ecological functions—such as seed dispersal or pollination of plants. Climate change and habitat loss threaten these interactions.

AI:EcoNet uses artificial intelligence to analyze and predict how such ecological networks evolve over time. For instance, AI can model what might happen to an ecosystem if key species disappears.

By combining big data and advanced models, this project supports better decisions in nature conservation and biodiversity protection.

Lektor Michael Ørsted

Adjunkt Abdulkadir Celikkanat

Mads Albertsen

AI is increasingly being used in expert fields like medicine and architecture, but real-world integration is often difficult.

AI:Xpertise investigates how to develop AI solutions that truly support expert workflows. For example, one AI model helps architects generate design ideas, while another assists doctors during pre-surgery assessments. At the same time, the project studies how workplaces adapt to using AI.

The aim is to find what technical and organizational conditions are needed for AI to be useful and trusted in expert settings.

Lektor Andreas Møgelmose,

Lektor Kasper Trolle Elmholt

Thomas B. Moeslund

Robots are increasingly used in industry and healthcare but making them work naturally with humans is still a challenge.

AI:Cybernetics develops a new kind of control system, where AI combines human signals (like muscle activity) with awareness of the environment (such as camera input). Imagine a robotic, prosthetic hand that automatically adjusts to the object you want to grab—without you needing to consciously control every movement. The same principle applies to robot arms helping with assembly tasks.

The goal is intuitive and efficient teamwork between people and robots.

Lektor Jakob Lund Dideriksen

Lektor Dimitris Chrysostomou

Strahinja Dosen

Modern energy systems, such as electric vehicle chargers and power grids, are increasingly exposed to cyber attacks that can cause physical damage.
AI:HARDWARE uses AI to protect this infrastructure and to design hardware that is secure by design. The lab also develops AI that runs efficiently on small, low-power devices. The goal is energy systems that are smart, secure, and able to protect themselves.

Edlira Dushku 

Hongbo Zhao 

Zheng-Hua Tan

This project uses AI to understand how many genes work together to affect a person’s risk of common diseases. Today’s tools often look at genes one by one and miss the bigger picture. By learning from large health databases, the project aims to give more accurate and personal risk predictions. This can help doctors find diseases earlier and choose better treatments in the future.

Palle Duun Rohde

Mikkel Meyer Andersen

Rasmus Waagepetersen

AI:INFRA works on using artificial intelligence to build and run important systems like energy, water, and communication in remote communities. These places often have very limited power, internet access, and technical resources. The lab explores how AI can help communities run better with fewer resources, while still being reliable and fair. The goal is to develop smart technology that uses very little energy but gives real benefits to people.

Chen Li

Mette Simonsen Abildgaard

Zheng-Hua Tan

AI:EMBODY studies how people communicate without words during therapy sessions, such as through facial expressions, posture, and movement. These signals are very important but hard to measure. The lab develops AI that can analyse video recordings to detect these subtle signals. This helps therapists better understand their clients and improve mental health treatment.

Rikke Gade

Ole Karkov Østergård

Thomas Moeslund

AI:GENE-XPLAIN develops AI tools that predict genetic cancer risk and help explain these risks to people in a clear and safe way. One part of the project builds AI models that can predict the risk of several cancers at once and explain how genes influence that risk. Another part studies how people understand and react to these predictions, so the information supports good decisions without causing unnecessary worry.

Anne Krogh Nøhr

Chalotte Glintborg 

Martin Bøgsted

Many wind turbines in Denmark are reaching the end of their planned lifetime. AI:Wind-Lab uses AI to help decide when turbines can safely keep running. By combining AI learning methods with engineering and safe statistics, turbines can monitor their own health and predict problems. This helps produce clean energy for longer without increasing risk.

Szymon Gres

Christophe Biscio 

Rafal Wisniewski

Rain and humidity weaken wireless signals used for satellite internet and navigation. AI:GeoComm turns this problem into a solution by using signal changes to learn about the weather and take appropriate action. By combining AI with physics and real-time data, the project improves weather forecasts and makes communication systems more reliable, which is especially important for Denmark and Greenland.

Lotte Ansgaard Thomsen

Israel Leyva-Mayorga 

Ehsan Forootan

Historical texts are often used to train AI, but they are hard to search and analyse. PAGE Lab builds AI tools that turn old texts into structured knowledge that computers can understand. This makes it possible to search across sources, find hidden connections, and explore history in new ways. The goal is to make cultural heritage data easier to study and use.

Russa Biswas

Johan Heinsen 

Bo Poulsen

Health records contain a wealth of clinically valuable information, but a large proportion of these data, notably patient journal notes, are not structured, hindering their usability, potentially leading to suboptimal care. AI:HealthData investigates AI methods that extract clinically relevant entities, relations and events from health records and organise them into knowledge graphs, supported by data management techniques for efficient retrieval and analytics. As a first application, AI:HealthData focuses on generating contextual and trustworthy patient summaries for general practitioners, saving time and improving care.

Charles Vesteghem

Daniele Dell’Aglio 

Martin Bøgsted

Through dedicated strategic funding, AI:X Labs provides a structured environment where innovative projects can thrive. Lab directors from different departments bring varied expertise to the table, ensuring that AI is both developed at its core and used creatively to address specific domain problems. The four PhD students in each lab form the backbone of daily research activity, building their careers while contributing fresh insights to the field.

Whether you are passionate about shaping AI theory or applying cutting-edge AI tools to societal challenges, AI:X Labs offers a platform to make a difference. A virtual structure means anyone across the university can participate, uniting fields and empowering breakthrough discoveries.

If you want to push boundaries, spark collaboration, and help shape Aalborg University’s path as a global AI leader, AI:X Labs is where you need to be.

Artificial intelligence (AI) is shaping the society of the future with new opportunities and dilemmas, and it is natural that we as a university take a leadership role in this area. At AAU, we are a leader in AI research, supported by interdisciplinary initiatives such as "AI for the People".

AI is one of the most groundbreaking technologies of our time. By investing heavily in AI research, AAU helps drive innovation and technological development, which can lead to new discoveries and solutions to complex problems. AI can help tackle some of the biggest societal challenges we face today, for example in health and climate.

In October 2024, The Executive Management decided, as part of the AAU strategy Knowledge for the World, to prioritized AI as a research goal in 2025 and beyond. AAU will establish 13 AI:X Labs: five AI:X Labs started in 2025, and nine AI:X Labs will start in 2026.