About Owen Douglas Owen Douglas Research Consultant, Stochastic Numerics Research Group Owen Douglas was a consultant for the Stochastic Numerics Research Group (STOCHNUM) at King Abdullah University of Science and Technology (KAUST). He is also a former Visiting Student at the STOCHNUM group from the University of Oxford. Research Interests Neural networks and Applied Mathematics Education Profile Masters of Engineering Science, University of Oxford Specialised in Applied Mathematics, Neural Networks, Information Engineering, Signal Processing and Statistics Articles Related News October 2023 StochNum warmly welcomed visiting students Owen Douglas from University of Oxford and Arved Bartuska from RWTH 1 min read · Sun, Oct 1 2023 News In a melting pot of intellectual pursuits, we warmly welcomed two visiting students Arved and Owen, as they embarked on an exciting academic journey. Owen Douglas from University of Oxford is conducting a project in neural networks applied to stochastic equations. Arved Bartuska from RWTH Aachen University is working on his thesis "Hierarchical Methods for Bayesian Optimal Experimental Design" under the supervision of prof. Raul Tempone. He is also collaborating on two underlying research papers with Dr. Andre Carlon. The goal of the project is to develop efficient estimators for nested
StochNum warmly welcomed visiting students Owen Douglas from University of Oxford and Arved Bartuska from RWTH 1 min read · Sun, Oct 1 2023 News In a melting pot of intellectual pursuits, we warmly welcomed two visiting students Arved and Owen, as they embarked on an exciting academic journey. Owen Douglas from University of Oxford is conducting a project in neural networks applied to stochastic equations. Arved Bartuska from RWTH Aachen University is working on his thesis "Hierarchical Methods for Bayesian Optimal Experimental Design" under the supervision of prof. Raul Tempone. He is also collaborating on two underlying research papers with Dr. Andre Carlon. The goal of the project is to develop efficient estimators for nested
