Professor Mardia's main research contributions are distributed over the following seven areas of statistics: multivariate analysis, directional data analysis, spatial statistics, statistical image analysis, shape analysis, spatio-temporal modelling and statistical bioinformatics. Much of his research in these areas has been motivated by challenging and new emerging applications in a wide variety of fields including biology, medicine, image analysis, computer science and geosciences.
1. Multivariate Analysis: Mardia's measure of skewness and kurtosis, Multivariate MRF, Book
2. Directional Statistics: Research Monograph, RSS Discussion paper, Mardia model on Torus, Line finding statistical procedure.
3. Spatial Statistics. Maximum likelihood estimation in Kriging and of Kriging with derivative information.
4. Statistical Image Analysis: Fusion methods, segmentation methods, warping methods. RSS Discussion paper.
5. Shape Analysis: Mardia-Dryden model, Goodall-Mardia multivariate shape models, Bilateral symmetry and projective invariants. Research Monograph. Shape of brain and FASD.
6. Spatial Temporal Modelling: Kriged-Kalman filter. TEST discussion paper.
7. Statistical Bioinformatics: Alignment through Bayesian hierarchical model, directional hidden Markov models for local structure prediction of protein (PNAS paper).