About the faculty

Alexander Ploner, PhD
Alexander is an experienced senior biostatistician at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet. He has extensive experience working as an applied biostatistician, including genetic analyses and cancer screening. Alexander has considerable expertise with R and survival analysis.
Eva Meglic
Eva is a PhD student at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet. She specializes in biostatistics and epidemiology, with practical experience in biostatistics from industry. Her PhD research focuses on the epidemiology of human papillomavirus (HPV) vaccination and its relation to cancer.
Fabrizio di Mari
Fabrizio is a visiting PhD student at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet. He has worked in biostatistics at the Italian National Institute of Health and has previous experience as a software developer in private companies. His PhD research focuses on extending mixture cure models with model-based clustering and machine learning techniques, as well as estimating complete cancer prevalence using cancer registry incidence and survival data. Fabrizio has considerable expertise in both R and Python.
Mark Clements, PhD
Mark is an associate professor in biostatistics at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet. He has worked as a biostatistician in Sweden, Australia, the United Kingdom and New Zealand for both universities and government. His primary research interests lie in cancer epidemiology, survival analysis methods and simulation for cancer screening. Mark has co-authored more than 140 scientific publications and also developed R software for survival analysis. He has taught survival analysis to a range of audiences.
Yunyang Deng, PhD
Yunyang is a postdoctoral researcher in epidemiology at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet. His expertise lies in epidemiology, with practical experience in cancer screening and epidemiology, Mendelian randomization, lifestyle factors, and non-communicable diseases. His current research focuses on developing machine learning prediction models for high-grade cervical lesions and exploring the associations between HPV infection and non-communicable diseases.