Staff profile

About me:

I am an Associate Professor of Statistics at Durham University. Previously, I had academic positions at Imperial College, Manchester and KU Leuven. My research mainly focuses on high dimensional statistics, longitudinal data analysis, change point analysis for high dimensional data, mixed-effects models, survival analysis, nonparametric and semiparametric models, joint modelling and model diagnostics. A major focus of my research has been on developing novel statistical methods and models for the analysis of complex data such as high dimensional data and longitudinal/multilevel data, especially from medical and health studies.

I have achieved Fellowship of the Higher Education Academy. Last academic year I taught the MSc course "Models and Methods for Health Data Science". This year I teach the course "High Dimensional Statistics IV" for final year mathematics and statistics students.

If you are interested to do a PhD in Statistics or Data Science, please get in touch.

• High dimensional statistics
• Longitudinal data analysis
• Change point analysis for high dimensional data
• Statistical modelling and inference
• Biostatistics
• Survival analysis

• Statistics

Conference Paper

• Drikvandi, Reza (2021), Diagnostic tools for random effects in general mixed models, The 14th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2021). London, UK.
• Drikvandi, Reza (2020), Invited session "Recent advances in biostatistics", The 13th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2020). London, UK.
• Drikvandi, Reza (2019), Joint modelling of longitudinal data involving time-varying covariates, The 12th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2019). London, UK.
• Drikvandi, Reza (2019), A novel method for analysis of high dimensional data, The Royal Statistical Society International Conference 2019. Belfast, UK.
• Drikvandi, Reza (2017), A joint mixed model for longitudinal data involving time-varying covariates, The 17th Conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society. London, UK.
• Drikvandi, Reza (2016), A joint semiparametric mixed model for longitudinal data involving time-varying covariates, The Royal Statistical Society International Conference 2016. Manchester, UK.
• Drikvandi, Reza (2015), Assessing the random effects part of mixed models, The 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015). London, UK.
• Drikvandi, Reza (2014), Diagnosing misspecication of the random-effects distribution in mixed models, The 22nd Conference of the Belgian Statistical Society. Louvain-la-Neuve, Belgium.

Journal Article

• Drikvandi, Reza & Lawal, Olamide (2023). Sparse principal component analysis for natural language processing. Annals of Data Science 10(1): 25-41.
• Rubio, Javier & Drikvandi, Reza (2022). MEGH: A parametric class of general hazard models for clustered survival data. Statistical Methods in Medical Research 31(8): 1603-1616.
• Al-Zubaidy, Noor, Crespo, Roberto, Jones, Sarah, Drikvandi, Reza, Gould, Lisa, Leis, Melanie, Maheswaran, Hendramoorty, Neves, Ana Luisa & Darzi, Ara (2021). Using big data analytics to explore the relationship between government stringency and preventative social behaviour during the COVID-19 pandemic in the United Kingdom. Health Informatics Journal
• Drikvandi, Reza (2020). Nonlinear mixed-effects models with misspecified random-effects distribution. Pharmaceutical Statistics 19(3): 187-201.
• Rao, Kaidi, Drikvandi, Reza & Saville, Ben (2019). Permutation and Bayesian tests for testing random effects in linear mixed-effects models. Statistics in Medicine 38(25): 5034-5047.
• Sirimongkolkasem, Tanin & Drikvandi, Reza (2019). On regularisation methods for analysis of high dimensional data. Annals of Data Science 6(4): 737-763.
• Drikvandi, Reza & Noorian, Sajad (2019). Testing random effects in linear mixed-effects models with serially correlated errors. Biometrical Journal 61(4): 802-812.
• Efendi, Achmad, Drikvandi, Reza, Verbeke, Geert & Molenberghs, Geert (2017). A goodness-of-fit test for the random-effects distribution in mixed models. Statistical Methods in Medical Research 26(2): 970-983.
• Drikvandi, Reza (2017). Nonlinear mixed-effects models for pharmacokinetic data analysis: assessment of the random-effects distribution. Journal of Pharmacokinetics and Pharmacodynamics 44(3): 223-232.
• Drikvandi, Reza, Verbeke, Geert & Molenberghs, Geert (2017). Diagnosing misspecification of the random-effects distribution in mixed models. Biometrics 73(1): 63-71, 63-71.
• Drikvandi, Reza, Verbeke, Geert & Molenberghs, Geert (2017). Supplementary materials for: Diagnosing misspecification of the random-effects distribution in mixed models. Biometrics
• Drikvandi, Reza, Verbeke, Geert, Khodadadi, Ahmad & Partovi Nia, Vahid (2013). Testing multiple variance components in linear mixed-effects models. Biostatistics 14(1): 144-159.
• Drikvandi, Reza, Khodadadi, Ahmad & Verbeke, Geert (2012). Testing variance components in balanced linear growth curve models. Journal of Applied Statistics 39(3): 563-572.
• Drikvandi, Reza, Modarres, Reza & Jalilian, Abdullah H (2011). A bootstrap test for symmetry based on ranked set samples. Computational Statistics & Data Analysis 55(4): 1807-1814.

Report

• Drikvandi, Reza, Williams, Angus, Boustati, Ayman, Ezer, Daphne, Arenas, Diego, de Wiljes, Jan-Hendrik, Chang, Marina, Varga, Marton, Groves, Matthew & Ceritli, Taha (2018). CodeCheck: How do our food choices affect climate change?