Research

applied probability, real options analysis, applications in energy

Interests

John Moriarty is Professor of Mathematics in the School of Mathematical Sciences, where he is also the School impact lead. Prior to joining Queen Mary, John was a Senior Lecturer in Probability and Statistics at the University of Manchester.

He holds a BA in Mathematical Sciences, MSc in Applied Statistics and DPhil in Mathematics from the University of Oxford. After the completion of his studies he held a post-doctoral research fellowship at University College Cork. He currently holds an EPSRC Early Career Research Fellowship, and serves as Principal Organiser for the 2019 Isaac Newton Institute programme on the Mathematics of Energy Systems.

His current research interests are in applied probability, real options analysis, and applications in energy. He is an EPSRC Early Career Research Fellow and other funding details can be found on the RCUK gateway to research.

Publications

Publications of specific relevance to Applied Data Science

2018

Martyr R, Moriarty J and Beck C (2018). Optimal control of a commercial building's thermostatic load for off-peak demand response. Journal of Building Performance Simulation  vol. 12, (5) 1-15. 10.1080/19401493.2018.1535624

De Angelis T, Ferrari G and Moriarty J (2018). A Solvable Two-Dimensional Degenerate Singular Stochastic Control Problem with Non Convex Costs. Informs  Mathematics of Operations Research  10.1287/moor.2018.0934

De Angelis T, Ferrari G and MORIARTY JM (2018). Nash equilibria of threshold type for two-player nonzero-sum games of stopping. Institute of Mathematical Statistics  Annals of Applied Probability  10.1214/17-AAP1301

2017

Johnson P, MORIARTY JM and Peskir G (2017). Detecting Changes in Real-Time Data: A User's Guide to Optimal Detection. Royal Society, The  Philosophical Transactions of The Royal Society a: Mathematical, Physical and Engineering Sciences  10.1098/rsta.2016.0298

Mijatovic A, MORIARTY JM and Vogrinc J (2017). Procuring load curtailment from local customers under uncertainty. Royal Society, The  Philosophical Transactions a: Mathematical, Physical and Engineering Sciences  10.1098/rsta.2016.0311

Gonzalez J, MORIARTY JM and Palczewski J (2017). Bayesian calibration and number of jump components in electricity spot price models. Elsevier  Energy Economics  vol. 65, 375-388. 10.1016/j.eneco.2017.04.022

De Angelis T, Ferrari G, Martyr R and MORIARTY JM (2017). Optimal entry to an irreversible investment plan with non convex costs. Springer Verlag  Mathematics and Financial Economics  10.1007/s11579-017-0187-y

2016

Schachter JA, Mancarella P, Moriarty J and Shaw R (2016). Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation. Energy Policy  vol. 97, 439-449. 10.1016/j.enpol.2016.07.038

MORIARTY JM and Palczewski J (2016). Real option valuation for reserve capacity. European Journal of Operational Research  10.1016/j.ejor.2016.07.003

2015

De Angelis T, Ferrari G and Moriarty J (2015). A Nonconvex Singular Stochastic Control Problem and its Related Optimal Stopping Boundaries. Siam Journal On Control and Optimization  vol. 53, (3) 1199-1223. 10.1137/14096801x

Grants

Grants of specific relevance to Applied Data Science

Research Fellowship for Data-Centric Engineering Programme
Moriarty J and Kosmala T
£276,297 The Alan Turing Institute (25-04-2020 - 24-04-2022)

Markov chain optimisation for energy systems (Ext.)
Moriarty J
£576,855 Engineering and Physical Sciences Research Council (24-04-2017 - 29-06-2020)

Summary

Optimal Prediction in Local Electricity Markets
Moriarty J
£214,717 Engineering and Physical Sciences Research Council (31-08-2015 - 24-04-2017)

Summary