• Assistant Professor, Engineering Technology & Industrial Distribution,
  • Industrial Distribution
  • Corrie & Jim Furber '64 Faculty Fellow
Na Zou

Educational Background

  • Ph.D., Industrial Engineering, Arizona State University – 2015
  • M.S.E., Civil, Environmental and Sustainable Engineering, Arizona State University – 2012

Research Interests

  • Interpretable Machine Learning
    Fairness in Machine Learning
    Network Modeling
    Transfer Learning
    Anomaly Detection

Awards & Honors

  • Best Student Paper Award Finalist, INFORMS QSR 2019
  • Best Paper Award Finalist, INFORMS QSR 2019
  • Featured in ISE Magazine, Institute of Industrial and Systems Engineers (IISE) 2018
  • TEES Travel Grant for NSF Workshop, College of Engineering, TAMU 2017
  • Selected to New Faculty Colloquium, IISE 2017
  • Irv Kaufman Award, IEEE Foundation 2015

Selected Publications

  • Mengnan Du, Fan Yang, Na Zou, Xia Hu. “Fairness in Deep Learning: A Computational Perspective.” 2020. IEEE Intelligent Systems.
  • Yuening Li, Xiao Huang, Jundong Li, Mengnan Du and Na Zou. “SpecAE: Spectral Autoencoder for Anomaly Detection in Attributed Networks.” 2019. The 28th ACM International Conference on Information and Knowledge Management (CIKM). (acceptance rate as 21% and INFORMS QSR Best Referred Paper Award Finalist).
  • Na Zou, Xiao Huang. “Empirical Bayes Transfer Learning for Uncertainty Characterization in Predicting Parkinson’s Disease Severity.” 2018. IISE Transactions on Healthcare Systems Engineering. 8(3):209-219. (featured in ISE Magazine).
  • Na Zou, Jing Li. “Modeling and Change Detection of Dynamic Networks by a Network State Space Model.” 2017. IISE Transactions. 49(1):45-57 (featured in ISE Magazine).
  • Na Zou, Mustafa Baydogan, Yun Zhu, Wei Wang, Ji Zhu, Jing Li. “A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems.” 2015. Technometrics. 55(3):362-373.