Computation, life
& engineering.
Connecting computational models, biological knowledge and physical systems.
Meet the laboratory
Understanding biological and engineered systems
through data, models and experiments.
Research areas
Three disciplines.
A common interest in complex systems.
01Computer science
Learning from data.
Interpreting predictions.
How can a model explain the variables behind its predictions?
We are interested in machine learning methods that make complex data useful for scientific analysis. Predictive modelling and interpretability connect model outputs to the variables that can be studied in an experiment.
- Machine learning
- Interpretable models
- Experimental design
02Biology
Reading sequences.
Studying living systems.
How can sequence and experimental data guide biological design?
Our interests connect biological sequence information with experimental observations. Computational analysis provides a way to investigate design choices and compare candidate sequences in their biological context.
- Bioinformatics
- Sequence design
- Biological data
03Mechanical
engineering
Modelling behaviour.
Connecting to the physical world.
engineering
How can sensing and control connect a model to a physical system?
We explore the relationship between computational descriptions and physical behaviour. Sensing, control and biologically inspired design offer ways to study how engineered systems interact with their environment.
- Physical modelling
- Sensing & control
- Biologically inspired design
The laboratory
Aietheia brings computer science, biology and mechanical engineering into the same research conversation.
Our interests span computational methods, biological processes and engineered systems. We look for questions that benefit from these perspectives together: how a sequence can be designed, how a prediction can be understood, and how a model can inform a physical experiment.
Clear assumptions, reproducible analysis and experimental evidence guide this work.
Our research interests
Acknowledgements
We thank the authors, maintainers and contributors who share their research software with the scientific community.