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Benjamin Haaland, Ph.D.

Languages spoken: English

Academic Information

Departments: Population Health Sciences - Associate Professor, Family & Preventive Medicine - Adjunct Associate Professor

Divisions: Biostatistics, DFPM Administration

Academic Office Information

Research Interests

  • Meta-Analytic Approaches to Comparative Effectiveness
  • Experimental Design and Modeling Techniques for Non-Parametric Regression Problems and Machine Learning

Ben Haaland is an Associate Professor in the Department of Population Health Sciences and Co-Director of the Cancer Biostatistics (CB) Shared Resource. From 2010-2014, he was an assistant professor in the Centre for Quantitative Medicine at Duke-NUS Graduate Medical School, Singapore and from 2014-2017, was an assistant professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology. Ben joined the University of Utah in 2017, and was appointed CB Shared Resource Co-Director in 2018.

Research Statement

Ben Haaland's overall research agenda is focused on two areas, evidence-based medicine and design and analysis for large-scale and high-dimensional non-linear regression problems. Ben’s evidence-based medicine research is directed towards using objective, quantitative evidence to inform decision making in health care, from tailoring therapies to individual patients, to estimating burden of disease, to using predictive analytics to improve diagnostic accuracy, to assessing effectiveness of interventions. Ben’s large-scale and high-dimensional non-linear regression research is largely directed towards methodology enabling the usage of computer simulations to study real systems of interest for which actual experimentation is difficult or impossible.

Education History

Internship Eli Lilly and Company
Internship IBM Thomas J. Watson Research Center
Doctoral Training University of Wisconsin–Madison
Graduate Training Montana State University
Undergraduate Montana State University
Applied Mathematics