The main research focus of the group is using numerical analysis to develop and analyze efficient and robust numerical methods for problems involving stochastic models and differential equations in engineering and sciences.
The research is driven by applications from areas such as computational mechanics, quantitative finance, biological and chemical modeling, and wireless communications.
More specifically, research contributions include a posteriori error approximation and related adaptive algorithms for numerical solutions of various differential equations, including ordinary differential equations, partial differential equations, and stochastic differential equations. Further research topics include Bayesian model calibration and validation, data assimilation, hierarchical and sparse approximation, optimal control, optimal experimental design, scientific machine learning, stochastic optimization, and uncertainty quantification.
Throughout his tenure at KAUST, Prof. Tempone successfully supervised ten PhDs until completion, directed the KAUST Strategic Research Initiative in Uncertainty Quantification (2012-2016), and served as the Program Director of the SIAM Uncertainty Quantification Activity Group (2013-2014). In 2016, Thomson Reuters recognized him as a highly cited researcher, and in 2018, Prof. Tempone was awarded the Alexander von Humboldt professorship hosted by RWTH Aachen. His research group placed a dozen faculty members in Germany (Uni. Karlsruhe), Norway (Uni. of Oslo), Saudi Arabia (KFUPM), the United Kingdom (Dundee, Heriot-Watt, Leeds, Nottingham), and the USA (University of New Mexico). Some of his research team members have also obtained positions in the industry, including, among others, Bain & Company in Finland, Baker Hughes, Enel Group in Italy, G-Research hedge fund in the UK, Honeywell, InConcert Spain, McKinsey & Company, Saudi Aramco, UK Meteorological Office and United Technologies (Raytheon). He has also collaborated with Saudi Aramco through multiple projects.