Meet Vasiliki Koutra

Dr Koutra said: “My research focuses on the blind spots of traditional experimental design, which often misses how treatments can ripple beyond the intended subjects to also affect neighbouring subjects, whether in social networks, healthcare, or agriculture systems. For example, in a social network marketing experiment, advertisements must be assigned carefully to evaluate differences in click-through rates or revenue, considering not only their direct effects on users but also the indirect or viral effects they generate through connections. I am drawn to the challenge of developing rigorous, scalable methods that reflect this complexity.

“I develop statistical methodologies tailored for large, noisy, interconnected systems that estimate both direct and indirect effects using graph theory, optimal design theory, and algorithmic techniques. My work aims to support sound decision-making by contributing methods that yield trustworthy, timely, and cost-effective evidence, even when the subjects of an experiment are connected. The goal is to help experimenters and researchers draw valid and reliable conclusions from their experimental data.

“Poorly designed experiments can lead to misleading conclusions and poor decisions. Robust experimental designs yield reliable data that enhance decision-making across diverse fields, from finance and environmental science to engineering and healthcare.

“For example, in healthcare, recognising how patient interactions influence outcomes enables more effective comparisons of interventions such as hand hygiene information leaflets, ultimately helping to reduce infections such as MRSA. By embracing the complexity of real-life systems instead of oversimplifying, experimental design transforms messy realities into powerful insights.

“My work naturally intersects with many fields. I have collaborated with researchers in medicine, agriculture, and beyond, translating complex questions into rigorous, well-designed experiments. This interdisciplinary science is both practical and drives new theoretical challenges, which I find deeply motivating.

“I am particularly interested in building new collaborations in healthcare and pharmaceutical science. My aim is to contribute to challenges such as treatment selection, trial sample sizing, and appropriate allocation across experimental units, while integrating experimental design with modelling to help ensure that research findings are trustworthy, meaningful, and reproducible.

“The environment at King’s fosters thorough methodological research while promoting practical impact and interdisciplinary collaboration. It has been an inspiring and supportive setting for my growth as a researcher.”