Lauren Burns
Statistics, Operations, and Data Science
Assistant Professor
Non-tenure Track
  • Office Location1810 Liacouras Walk, Room 334
  • Curriculum Vitae View
  • Titles & RolesDeputy Chair


Lauren Burns is an Assistant Professor of Instruction in the Department of Statistical Science. She teaches traditional and online BBA, honors, and general education courses, as well as courses in the Fox MBA and Executive MBA programs. Outside of teaching, Dr. Burns has also worked on various consulting projects for the Center for Statistical Analysis at Temple.

Dr. Burns’ research interests are in the areas of survival analysis, specifically the presence of non-proportional hazards, high-dimensional data, and dimension reduction. She focuses mostly on applications in Biostatistics dealing with micro-array gene expression data.

Before beginning her career here, Dr. Burns received her M.S. degree and PhD in Statistics from Temple’s Fox School of Business. She also studied at Muhlenberg College, where she earned a Bachelor of Science degree in Mathematics and Economics.


  • Ph.D., Statistics Temple University, Philadelphia
  • M.S., Statistics Temple University, Philadelphia
  • B.S., Mathematics and Economics Muhlenberg College, Allentown, Pennsylvania


  • August 2011 – Present, Temple University, Philadelphia, PA
  • August 2013 – December 2015, Lasalle University, Philadelphia, PA
  • May 2013 – July 2015, Delaware County Community College, Media, PA

Sample Publications

  • Das, K., Afriyie, P., Spirko, L. ”A Semiparametric Bayesian Approach for Analyzing Longitudinal Data from Multiple Related Groups”. International Journal of Biostatistics, 2015.
  • Spirko-Burns L., Devarajan K. “Unified methods for feature selection in large-scale genomic studies with censored survival outcomes.” Bioinformatics. 2020; 36(11): 3409-3417.
  • Spirko-Burns L., Devarajan K. (In Press)” Supervised dimension reduction for large-scale `omics’ data with censored survival outcomes under possible non-proportional hazards” [published online ahead of print, 2020 Jan 10]. IEEE/ACM Trans Comput Biol Bioinform. 2020; doi:10.1109/TCBB.2020.2965934.