Professor Ioannis Kosmidis

ioannis kosmidis


Turing Fellow, Turing University Lead - Warwick and Theory and Methods Challenge Fortnights Lead

Partner Institution


Ioannis Kosmidis is a Professor of Statistics at the Department of Statistics, University of Warwick, Turing University Lead - Warwick, Theory and Methods Challenge Fortnights Lead, and Turing Fellow at The Alan Turing Institute, the UK's national institute for data science and artificial intelligence.

He obtained his BSc in Statistics from the Athens University of Economics and Business in 2004. He was awarded a PhD in Statistics in 2007 at the Department of Statistics, University of Warwick with a thesis titled "Bias reduction in exponential family nonlinear models". He then held an appointment as a CRiSM Research Fellow until 2010. In September 2010, he joined the Department of Statistical Science at University College London as a Lecturer (equivalent to Assistant Professor), and he got promoted to Senior Lecturer (equivalent to Associate Professor) in 2015. He moved back to University of Warwick as a Reader in Data Science in January 2018, and got promoted to Professor of Statistics  in August 2021.

Research interests

Ioannis' theoretical and methodological research focuses on optimal estimation and inference from complex statistical models, penalized and pseudo-likelihood methods and clustering. A particular focus of his work is the development of efficient, in terms of computational complexity and implementation, algorithms for applying the methods he develops to prominent data-analytic scenarios. He is doing extensive work in producing corresponding, well-documented, open-source software that delivers the methodological advances to the data science community and beyond (see his software page for information). Ioannis also actively engages in a range of cross-disciplinary applications (e.g. applications in earthquake engineering, finance, sport and health analytics, and neuroscience), particularly in settings where statistical modelling and the associated algorithms can impact policy-making. 

He is a founding member of the Data science for sports, activity, and well-being Turing Interest Group, before which he led and run the Statistics in Sports and Health research group at UCL between 2014 and 2017.

He is an associate editor for Biometrika and the Journal of Statistical Software, and a member of the Research Section of the Royal Statistical Society. Detailed, up-to-date information on his research, teaching, enabling and engaging activities can be found on his website and his CV.