Ciprian Crainiceanu

Ciprian Crainiceanu is a Professor in the Department of Biostatistics at the Bloomberg School of Public Health, Johns Hopkins University. His research spans biostatistical methodology and applications in public health, with a focus on high-dimensional data from wearable devices and medical imaging.

Education:

• PhD, Cornell University, 2003
• MS, University of Bucharest, 1998

His research interests include functional data analysis, measurement error, longitudinal modeling, Bayesian inference, and nonparametric statistics, with applications in sleep, aging, multiple sclerosis, Alzheimer’s disease, and cancer. He develops statistical tools tailored to complex data from accelerometers, neuroimaging (MRI, CT, SPECT), and surgical monitoring. His recent work involves dynamic prediction models, step-counting algorithms for NHANES and ARIC data, and methods for high-dimensional functional and imaging data.

The most recent publications highlight advancements in wearable data analysis, medical imaging platforms like Neuroconductor, and novel resampling methods such as the upstrap. His work integrates statistical theory, software development, and interdisciplinary collaboration.

Scientific Awards:

• Fellow of the American Statistical Association (ASA)
• Chair, Statistics in Imaging Section of ASA (two terms)
• Chair, Biostatistics Methods and Research Design (BMRD) NIH review section

Crainiceanu is actively involved in mentoring, teaching, and collaborative research. He co-founded the SMART (Statistical Methods and Applications for Research in Technology) research group and Neuroconductor, fostering interdisciplinary innovation. His work emphasizes scalable, software-backed methods and close collaboration with domain scientists. He has led methodological developments in variance components testing, functional regression, population value decomposition, and dynamic prediction, applied to real-world health challenges.

Labs and Research Groups:

• Co-founder, SMART (Statistical Methods and Applications for Research in Technology)
• Co-founder, Neuroconductor (open-source platform for medical imaging in R)
• Wearable and Implantable Technology (WIT) group
• MAGIC (Methods and Applications Group for Imaging in the Clinic)