Javier E. Flores joined Pacific Northwest National Laboratory’s (PNNL’s) Applied Statistics and Computational Modeling group in June 2021 after completing his PhD in biostatistics at the University of Iowa. Javier has since transitioned to the Computational Biology group within PNNL’s Earth and Biological Sciences Directorate. In this capacity, Flores has worked on developing false discovery rate estimation methods for gas chromatography/mass spectrometry-based metabolomics, applied machine learning toward multi-omics data analysis and integration, and developed software for improving the efficiency of nuclear magnetic resonance based metabolomic data processing.

Before joining PNNL, Flores completed his doctoral thesis at the University of Iowa. Through his thesis work, he developed a new class of information criteria—metrics that may be used to rank-order statistical models. The criteria developed by Flores generalize a popularly used information criterion (i.e., the Akaike Information Criterion) and are designed for predictive modeling applications because they demonstrate a tendency to select models with minimal prediction error for large samples. While at the University of Iowa, Flores also collaborated with interdisciplinary teams on applied projects within injury epidemiology.

Aside from his research activity, Flores has a passion for teaching and mentoring. He served as an adjunct faculty at Grinnell College, teaching an introductory course in applied statistics. He also served for multiple years as a project mentor for the Iowa Summer Institute in Biostatistics, a program that aims to expose students from underrepresented backgrounds to the field of biostatistics.

Research Interests

  • Multi-omics
  • R Shiny
  • Predictive modeling
  • Model selection
  • Biostatistics
  • Computational biology
  • Machine learning
  • Statistics
  • Data analysis
  • R


PhD in biostatistics, University of Iowa

MS in biostatistics, University of Iowa

BS in chemistry, The University of Texas at Brownsville



Javier E. Flores, Daniel M. Claborne, Zachary D. Weller, Bobbie-Jo M. Webb-Robertson, Katrina M. Waters, and Lisa M. Bramer. "Missing data in multi-omics integration: Recent advances through artificial intelligence." Front. Artif. Intell. Feb. 2023.


Javier E. Flores, Joseph E. Cavanaugh. "Partial Likelihood." Wiley StatsRef: Statistics Reference Online. doi: 10.1002/9781118445112.stat05932.pub2

Andrew A. Neath, Javier E. Flores, Joseph E. Cavanaugh. "Bayesian multiple comparisons and model selection." Wiley Interdisciplinary Reviews: Computational Statistics. March 2018. doi: 10.1002/wics.1420


Mark L Hatzenbuehler, Javier E FloresJoseph E CavanaughAngela Onwuachi-WilligMarizen R Ramirez"Anti-bullying Policies and Disparities in Bullying: A State-Level Analysis." American Journal of Preventive Medicine. Aug. 2017  doi: 10.1016/j.amepre.2017.02.004