AICS / Research / Fields
Connected fields.
Shared discoveries.
Our research brings together artificial intelligence, complex systems, biotechnology and 3D technologies. We connect computational methods with questions from physics, biology and medicine.
01 / Learning from data and structure
Artificial Intelligence
Artificial intelligence develops computational methods to learn from data, recognize patterns and represent relationships. Our research map connects AI theory with language models, graphs and computer vision.
- Large language models (LLMs)
- Investigate models that learn patterns in language and support the analysis and generation of text.
- Graphs
- Represent entities and their relationships to study structured data and connect learning methods with network science.
- Computer vision
- Extract information from images, connecting visual patterns with applications such as plant analysis and 3D research.
- AI theory
- Study the mathematical and computational foundations of learning, representation and inference.
02 / From interactions to collective behavior
Complex Systems
Complex systems research asks how interactions among many components give rise to collective patterns and behavior. This front connects chaos theory, complex networks, fractal geometry and cellular automata with the study of artificial intelligence.
- Chaos theory
- Investigate nonlinear dynamics and sensitivity to initial conditions to understand how deterministic systems can produce intricate, unpredictable behavior.
- Complex networks
- Study the organization and dynamics of interconnected systems, relating network structure to the behavior of the whole.
- Fractal geometry
- Study self-similarity and patterns across scales, connecting the description of complex shapes and textures to computer vision.
- Cellular automata (CA)
- Explore how local rules produce collective behavior, connecting discrete dynamical models with graphs and network representations.
The connection with AI runs in both directions: network and dynamical perspectives help study learning systems, while AI provides methods for exploring complex data. Graphs connect to complex networks and cellular automata, fractal geometry connects to computer vision, and AI theory connects to complex systems.
03 / Understanding living systems
Biotechnology
Biotechnology connects biological questions with computational analysis and new technologies. Virology, medicine and plant sciences form the three branches of this research front.
- Virology
- Study viruses and their interactions with biological systems through interdisciplinary analysis.
- Medicine
- Connect biological data and computational methods to questions in health and disease.
- Plant sciences
- Investigate plant structures and patterns, linking biological observation with image analysis and computational methods.
04 / From physical form to digital models
3D technologies
Capturing, representing and producing three-dimensional structures connects the physical world with computational models. This research front brings together scanning, printing and bioprinting.
- 3D scanning
- Capture the shape and geometry of objects for digital reconstruction, measurement and analysis.
- 3D printing
- Translate digital models into physical objects, supporting the study and prototyping of complex geometries.
- Bioprinting
- Explore the intersection of three-dimensional fabrication and biological research.