Kandala is currently Professor of Biostatistics & Direction of Business and Enterprise at Northumbria University, UK. He is affiliated with the University of Witwatersrand, School of Public Health, Division of Epidemiology & Biostatistics, South Africa as a Distinguished Professor of Biostatistics and a Visiting Professor at the University of Agder, Norway and University of Warwick, UK. Prior to this, he worked as Head of Health Economics and Evidence Synthesis Research Unit at the Luxembourg Institute of Health, Luxembourg and was Associate Professor in Health Technology Assessment, a joint appointment with the University of Oxford and University of Warwick. For the past 15 years, his main research interests are in Bayesian statistical methods and their application to epidemiology and health ( maternal and child health and a variety of health-related health inequalities both in the developing countries and command economies, using large scale household data). The United Nations, Department of International Development (DFID, UK) and Population Council (Kenya) fund his current research projects on the modelling of Female Genital Mutilation. He also involved in capacity building in Biostatistics in Sub-Saharan Africa countries. He is the co-Director of the Welcome Trust funded DELTAS Africa Sub-Saharan African Consortium for Advanced Biostatistics (SSACAB), a consortium of twenty African and northern institutions, which has the mission to train the next generation of biostatisticians in Africa. Kandala has published widely in high impact peer review journals in both the field of Statistics and health in diverse populations. His recent book with Springer Science titled ‘Advance Techniques in modelling Maternal and child health in Africa’ (2014) and his forthcoming book with Springer Science is titled ‘Female Genital Mutilation around the World: Analysis of Law, Health and Practice (2018).
Kandala current research interests include, research design, statistical methods applied to epidemiology, survival analysis, longitudinal data analysis, meta-analysis, Bayesian Spatial Analysis, Health Economics and Health Technology Assessment.