Aaron Scheffler

Aaron Scheffler is an Assistant Professor in the Department of Epidemiology & Biostatistics at the University of California, San Francisco (UCSF) School of Medicine. His research program addresses statistical challenges arising from highly structured biomedical data, particularly in neuroimaging and wearable technologies. As a core statistician for the UCSF Memory and Aging Center, including the Alzheimer's Disease Research Center and ALBA Language Neurobiology laboratory, he collaborates extensively with clinical researchers across multiple disciplines.

Dr. Scheffler received his PhD and MS in Biostatistics from the University of California, Los Angeles and his BA in Biochemistry from Columbia University. His methodological expertise spans functional data analysis, disease progression modeling, and multi-modal brain imaging data integration.

His research focuses on developing computationally efficient statistical methods for complex biomedical data that maintain information across multiple dimensions while providing interpretable components. His work addresses challenges in disease progression modeling for neurodegenerative disorders, joint analysis of multi-modal brain imaging data, and functional data analysis of electroencephalography (EEG) data. Current projects include Bayesian generalized nonlinear mixed effects models for disease progression, joint modeling of structural and network brain imaging data, and advanced methods for EEG analysis in developmental disorders.

Analysis of his recent publications reveals a strong interdisciplinary focus spanning neurology, orthopedics, and neonatology. His work demonstrates expertise in analyzing complex data structures including longitudinal imaging, EEG, and biomechanical measurements. Key methodological themes include Bayesian modeling, functional data analysis, and machine learning applications to biomedical problems. His research consistently bridges advanced statistical methodology with clinically relevant questions.

Dr. Scheffler's research is supported by extramural grants from the National Institutes of Health Institute of Neurological Disorders and Stroke and the National Science Foundation (Division of Mathematical Sciences). His recent NIH/NINDS R01 grant titled 'Bayesian Object-Oriented Modeling of Multi-Modal Imaging Data' and NSF DMS grant 'Use of Random Compression Matrices For Scalable Inference in High Dimensional Structured Regressions' demonstrate his leadership in methodological innovation for complex biomedical data.

He maintains active collaborations with researchers at UCSF in neurology, orthopedics, and HIV/AIDS research, contributing statistical expertise to diverse clinical investigations. His work with the Memory and Aging Center and ALBA Language Neurobiology laboratory positions him at the forefront of statistical methods development for neurodegenerative disease research.