Peter Vincent
Office: 211 City and Guilds Building
Phone: 020 759 41975

Postdoctoral Scholars

Arun Pillai
Topic: Flux Reconstruction and PyFR

PhD Students

Lidia Caros Roca
Topic: Flux Reconstruction and PyFR

Semih Akkurt
Topic: Flux Reconstruction and PyFR

Masters Students

None at present ...

Past Members

Lionel Agostini (Postdoctoral Scholar 2019-2020)
Niki Loppi (PhD Student 2015-2019 and Postdoctoral Scholar 2019-2020)
Yoshiaki Abe (Postdoctoral Scholar 2016-2018)
Francesco Iori (PhD Student 2014-2018)
Alexandru Dorcioman (Masters Student 2018)
Alan Perfect (Masters Student 2018)
Lorenza Grechy (PhD Student 2013-2017 and Postdoctoral Scholar 2017-2018)
Arvind Iyer (Postdoctoral Scholar 2014-2018)
George Ntemos (PhD Student 2013-2017)
Maksym Tymchenko (UROP Stundet 2017)
Alex Haigh (Masters Student 2017)
Thomas Goode (Masters Student 2017)
Sagar Mitha (Masters Student 2017)
Andrei Hirjanu (Masters Student 2017)
Jin Seok Park (Postdoctoral Scholar 2014-2016)
Yumnah Mohamied (PhD Student 2012-2016)
Javier Igual Campos (Masters Student 2016)
Zakaira Meddings (UROP Student 2016)
Brian Vermeire (Postdoctoral Scholar 2014-2016)
Daniele De Grazia (PhD Student 2012-2016)
Liang Dong (Masters Student 2016)
Freddie Witherden (PhD Student 2012-2015 and Postdoctoral Scholar 2015-2016)
Liu Yaguang (Masters Student 2015)
Bryan Tan (Masters Student 2015)
Gabriel Gassem (Masters Student 2015)
Kevin Castel (Masters Student 2014)
Kayan Kanga (Masters Student 2014)
Chih-Hao Chen (Masters Student 2013)
Michail Georgiou (Masters Student 2013)
Celia Perez (Masters Student 2013)
Pak Lao (Masters Student 2013)
Jack Turton (Masters Student 2013)
Nicolo Demicheli (Masters Student 2013)
Bruno Villamiel (Masters Student 2012)
Arnau Perdigo (Masters Student 2012)
Ravi Khiroya (UROP Student 2012)


PhD Studentship - Development of In-situ Visualisation and Analysis Technology for High-Fidelity Computational Fluid Dynamics
Summary: A PhD Studentship is currently available. The project, will involve addition of 'in-situ' visualisation, processing, and analysis technology to PyFR, an open-source high-order massively-parallel CFD platform, as well as its application to solve a range of challenging unsteady flow problems. Candidates should hold, or expect to obtain, an undergraduate degree in a numerate discipline. Previous programming experience is important (ideally Python, C++ and CUDA).