William Consagra

William Consagra is an Assistant Professor in the Department of Statistics at the University of South Carolina's McCausland College of Arts and Sciences. He holds a BS and MS in Applied Mathematics from the Rochester Institute of Technology and a PhD in Statistics from the University of Rochester, followed by a postdoctoral fellowship at Harvard Medical School. His research focuses on functional data analysis, computational statistics, and deep learning applied to neuroimaging and connectomics. Consagra specializes in neuroimaging inverse problems, diffusion MRI analysis, and statistical methods for medical data.

• Education:
  • Bachelor of Science in Applied Mathematics, Rochester Institute of Technology
  • Master of Science in Applied Mathematics, Rochester Institute of Technology
  • Doctor of Philosophy in Statistics, University of Rochester

Research Interests: Dr. Consagra develops advanced statistical and machine learning techniques for neuroimaging applications, including diffusion MRI parameter estimation, structural connectomics analysis, and uncertainty quantification. His work bridges computational methods with clinical challenges in oncology and geriatric medicine, addressing issues like chemotherapy symptom management and patient well-being trajectories. His methodologies often involve functional data analysis, neural field modeling, and high-dimensional data harmonization.

His recent publications highlight innovations in multi-scale neural representation models, automated connectome analysis, and overcoming technical barriers in medical imaging. He has contributed to interdisciplinary studies on aging populations, cancer outcomes, and healthcare equity in telemedicine contexts.

Labs & Teams: While specific lab affiliations are not detailed, his work aligns with medical imaging research groups and biostatistics collaborations at Harvard Medical School and University of South Carolina.