Peter Johnson

Peter Johnson is a Lecturer in Financial Mathematics and Probability at The University of Manchester. His research focuses on stochastic processes, statistical detection methods, and biophysical systems. He contributes to the UN Sustainable Development Goals through work on probabilistic modeling and biomedical applications.

Research interests include Bayesian analysis, Brownian motion dynamics, Bessel processes, and ion transport mechanisms in cellular environments. His work bridges financial mathematics with biophysical studies, applying stochastic models to both quantitative finance and cellular biology.

Recent contributions include methodologies for detecting random drifts in Brownian motion and analyzing V-ATPase regulation in mammalian brains. His 2017 work on optimal detection algorithms has been influential in real-time data analysis frameworks.

Dr. Johnson holds a PhD in Mathematics from The University of Manchester (2015), supervised by Professors Peskir and Evatt. His research outputs span peer-reviewed journals and interdisciplinary collaborations in biophysics and mathematical finance.