Daniel Sharpe

My research is concerned with the development of algorithms for the efficient simulation and analysis of Markov chain dynamics. Finite Markov chains are discrete-state stochastic models that are used to represent the dynamics of many processes. Examples of tangible applications include modeling financial markets and the distribution of species populations in an ecosystem. Markov chains are also commonly used as representations of the dynamics of condensed matter, biophysical, and biochemical systems. The analysis and simulation of Markov chains representing realistic processes, which typically feature a "rare event" that is of particular interest, is plagued by numerical and efficiency issues. To obtain the rare event trajectories and analyse characteristic features of the transition of interest, special enhanced sampling methodologies and numerically stable algorithms must be used.

I am the developer of the DISCOTRESS (DIscrete Time COntinuous State Rare Event Simulation Suite) for simulation and analysis of the dynamics for arbitrary Markov chains. Visit github.com/danieljsharpe

I previously studied at Van Mildert College, Durham University, obtaining a 1^st class (Hons.) MChem degree and being awarded the Vice Chancellor’s Scholarship and Prize for Mastership of chemistry. I am a recipient of a Vice Chancellor’s Scholarship Award to study for a PhD at the University of Cambridge.