Aaron Scheffler, PhD, MS
Assistant Professor
Epidemiology & Biostatistics
School of Medicine

My research centers on the statistical challenges posed by highly structured data collected in an increasing number of applications ranging from imaging to wearable technologies. Frequently, the observed data are discrete samples of an underlying functional process which exhibits complex dependencies that are difficult to capture using traditional statistical models.

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A central theme in my research is to provide computationally efficient methods for these rich data structures that maintain information along each dimension while simultaneously providing interpretable components and inferences. In addition, I apply techniques from statistics and machine learning including mixed effects models, gradient boosting, and tree based methods, to assist collaborators in psychiatry, neurology, oncology, and HIV/AIDS research.

Education & Training

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  • PhD Biostatistics University of California, Los Angeles 2019
  • MS Biostatistics University of California, Los Angeles 2015
  • BA Biochemistry Columbia University 2011

Websites

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Publications (42)

Top publication keywords:
Child DevelopmentHouse CallsHypothermia, InducedPrincipal Component AnalysisFunctional NeuroimagingAlpha RhythmInfant, Newborn, DiseasesMothersChild HealthAutism Spectrum DisorderLung Diseases, ObstructiveModels, StatisticalHypoxia-Ischemia, BrainCommunity Health WorkersElectroencephalography

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