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Background

Zeynep Ertem’s expertise is in data analytics in healthcare systems, epidemic disease modelling, network optimization, discrete optimization, social networks and health systems optimization. Prior to joining ��������, she was an adjunct professor in the Department of Data Sciences and Operations at Marshall School of Business at University of Southern California. She also served as a post-doctoral fellow at the University of Texas at Austin in the Department of Data Science and Statistics. She completed her PhD in industrial and systems engineering at Texas A&M University after obtaining her BS degree in industrial engineering from the Middle East Technical University in Turkey, with a minor in mathematics. Her recent papers were published in high-impact journals such as PLOS Computational Biology, Social Networks, the Journal of Global Optimization, and also highlighted by several U.S. news outlets.

Lab page

Education

• PhD: Texas A&M University, College Station, TX

• BS: Middle East Technical University, Ankara, Turkey

Research Interests

• Optimization and modelling
• Decision Support Systems
• Infectious disease modelling
• Public health optimization
• Social networks
• Machine learning on public health
• Network optimization

More Info

• The impact of school opening model on SARS-CoV-2 community incidence and mortality.
  Ertem, Z., Schechter-Perkins, E.M., Oster, E. et al. 2021 (Nature Medicine)
  (Impact Factor: 53.44)
• A Decision Analytic Approach for Social Distancing Policies During COVID-19 Pandemic.
  Ertem, Z., Araz, O.M., Cruz-Aponte, M. 2021 Decision Support Systems (2021): 113630 (Impact Factor: 4.72)
• Identifying climatological interactions in global influenza across temperate and tropical regions.
  Du, Z*., Ertem, Z.*, Li, Z., Tan, X., Zhao X., Bai, Y., Tian X. 2020 International Conference on Mobile Wireless Middleware, Operating Systems, and Applications (pp. 98-103). Springer, Cham. (Impact Factor: 2.62)
• Inter-urban interactions of mobility via cellular position tracking in the southeast Songliao Basin, Northeast China. Du, Z., Yang, Y., Ertem, Z., Gao, C., Huang, L., Huang, Q., Bai, Y. 2019. Under publication Scientific Data (Impact Factor: 5.30)

• Scientific insights into Physarum-based modelling: Comment on “Does being multi-headed make you better at solving problems? A survey of Physarum-based models and computations” by C. Gao et al. Du, Z., Cai, Q., Ertem, Z., Bai, Y. Physics of Life Reviews, January 2019 (Impact Factor: 9.47)
• On the Multi-source Influenza Forecasting: A Bayesian Approach. Ertem, Z., Raymond, D., Meyers, L.A., PLOS Computational Biology, September 2018 (Impact Factor: 4.55)
• The Maximum Independent Union of Cliques Problem: Complexity and Exact Approaches. Ertem, Z., Lykhovyd, E., Wang, Y., Butenko, S. Journal of Global Optimization, July 2018 (Impact Factor: 1.74)
• Scale Reduction Techniques for Computing Maximum Induced Bi-cliques. Shahinpour, S., Shirvani, S., Ertem, Z., Butenko, S., Algorithms, October 2017 (Impact Factor: 1.44)
• Detecting Large Cohesive Subgroups with High Clustering Coefficients. Ertem, Z., Veremyev, A., Butenko, S. Social Networks, July 2016 (Impact Factor: 3.57)
• Demographic Breakdown of Twitter Users: An analysis based on names. Oktay, H., Firat, A., Ertem, Z. Proceedings of the Sixth ASE International Conference on Social Computing May 2014, Stanford,CA