MSc Applied Data Analytics
Queen Mary University of London
About Queen Mary University of London
Queen Mary University of London (QMUL) is one of the UK's leading research-focused higher education institutions.
QMUL, which dates back to the foundation of London Hospital Medical College in 1785, counts nine Nobel Laureates amongst its alumni and staff. As a Russell Group university, QMUL is considered to be amongst the most prestigious institutions in the UK, and currently ranks in the top 20 universities in the UK (QS World University Rankings 2021).
Queen Mary is also a leading research-intensive university, ranked 7th in the UK in the most recent Research Excellence Framework exercise.
About the School of Mathematical Sciences
Studying with the School of Mathematical Sciences at Queen Mary University of London means you’ll be joining a diverse, international community of like-minded, intellectually curious students, who use both logic and creativity to solve the problems of the 21st century.
It’s a supportive community too, working together to achieve goals, with one of the largest maths departments in the UK and a very active Mathematics Society.
Our flexible and wide range of abstract and real world programmes, means you can shape your own career path and join our esteemed alumni, who have gone on to work in research, and for prestigious organisations such as Dyson, JP Morgan, PwC, KPMG, Goldman Sachs and the Financial Conduct Authority.
Docentes em destaque
Dr Primoz SkrabaReader in Applied and Computational Topology
Primoz received a PhD in Electrical Engineering from Stanford University in 2009 and held positions at INRIA in France and the Jozef Stefan Institute, the University of Primorska, and the University of Nova Gorica in Slovenia, before joining Queen Mary in 2018. His research is broadly related to data analysis with an emphasis on topological data analysis. Primoz was also a Turning Fellow and has been working with data in government and industry.
Dr Martin BenningSenior Lecturer in Inverse Problems and Machine Learning
Martin received a PhD in Applied Mathematics from the University of Münster in 2011 and held positions at the University of Cambridge and the University of Lübeck prior to joining Queen Mary University of London in 2018. Martin is currently Academic Member of the Digital Environment Research Institute and Turing Fellow at the Alan Turing Institute. Before becoming a lecturer, he was a Leverhulme Trust Early Career Research Fellow and a Fellow of the Isaac Newton Trust. His expertise is the theoretical and computational handling of inverse & ill-posed problems, with particular focus on the fusion of model-based and data-driven regularisation approaches.
Prof Boris KhoruzhenkoProfessor of Mathematics
Boris obtained a Diploma in Mathematics from V.N. Karazin Kharkiv National University and his PhD in Mathematical and Theoretical Physics from the Institute for Low Temperature Physics of the National Academy of Sciences of Ukraine. He worked for 12 years as a Research Fellow in the Mathematical Division at the Institute for Low Temperature Physics before joining Queen Mary University of London in 1996. His current research interests are in the Random Matrix Theory and its applications. This involves investigating patterns in distribution of eigenvalues and eigenvectors of random matrices and operators.
Dr Arthur GuillauminLecturer in Mathematical Data Science
Arthur pursued a PhD under the supervision of Pr Sofia C. Olhede and Dr Adam M. Sykulski, at the Department of Statistical Science of University College London. He then held a postdoctoral position for two years with the same supervisors, following which he moved to a postdoctoral position at New York University under the supervision of Pr Laure Zanna. His research interests are in modelling spatio-temporal data with a focus on applications to environmental sciences.
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