Neil Walkinshaw

Research

I am especially interested in developing techniques to support the testing of that are traditionally hard to test (e.g. complex input spaces, cyber-physical systems, systems with long execution times, etc.). My research tends to focus on the application of concepts and techniques rooted in Machine Learning and probability theory. In recent years much of my research has focussed on the application of Causal Inference to test causal relationships between inputs and outputs in scientific software models (funded by the EPSRC CITCOM project).

• 📚 My publications can be found here: Google Scholar | DBLP
• 💡 If you're interested in collaboration, or in studying for a Ph.D. with me, feel free to contact me!