Dr. Na Zou

Dr.Zou Profile Picture 

Assistant Professor
Department of Industrial Engineering
University of Houston
W220 Engineering Bldg 2
Houston, TX 77204

Email: nzou2@uh.edu
Office: (+1) 979-862-7825

Biography

Dr. Na Zou is a tenure-track assistant professor in the Department of Industrial Engineering. Her
research is in the area of data-driven modeling and knowledge discovery for tackling data challenges raised by large-scale, dynamic
and networked data from various real-world information systems. Specifically, Dr. Zou’s research focuses on fairness in machine learning,
interpretable machine learning, transfer learning, and network modeling and inference. The research projects have resulted in publications at
prestigious venues such as Technometrics, IISE Transactions and ACM Transactions, including one Best Paper Finalist and one Best Student Paper
Finalist at INFORMS QSR section, two featured articles at ISE Magazine and one student innovation award at AMIA annual symposium. She was the
recipient of IEEE Irv Kaufman Award, Texas A&M Institute of Data Science Career Initiation Fellow and NSF CAREER Award.

News

  • 2023/8: Dr. Zou talked to the Eagle newspaper about how artificial intelligence systems may impact operations in local city government.

  • 2023/8: Dr. Zou was interviewed by KAGS News (NBC) on bias in machine learnig and its potential impact.

  • 2023/5: Dr. Zou received the prestigious NSF CAREER award.

  • 2023/4: Dr. Zou was elected as the Data Analytics and Information Systems (DAIS) Division president of
    the Institute of Industrial and Systems Engineering (IISE).

Honors and Awards

  • Faculty Early Career Development Program (CAREER), 2023
    National Science Foundation

  • Knowledge Discovery and Data Mining (KDDM) Student Innovation Award, 2022
    The AMIA 2022 Annual Symposium

  • Best Student Paper Award Finalist, 2022
    The AMIA 2022 Annual Symposium

  • Texas A&M Institute of Data Science Career Initiation Fellow, 2021
    Texas A&M University

  • Best Student Paper Award Finalist, 2019
    INFORMS QSR

  • Best Paper Award Finalist, 2019
    INFORMS QSR

  • Featured in ISE Magazine, 2018
    Institute of Industrial and Systems Engineers (IISE)

  • TEES Travel Grant for NSF Workshop,2017
    Texas A&M University

  • Selected to New Faculty Colloquium,2017
    Institute of Industrial and Systems Engineers (IISE)

  • Irv Kaufman Award, 2015
    IEEE Foundation

Research Interests

  • Machine Learning: Fairness in Machine Learning, Interpretable Machine Learning, Transfer Learning, Sparse Learning,
    Uncertainty Quantification

  • Network Modeling and Inference: Dynamic Networks, Network Embedding with Heterogeneous Information, Anomaly Detection

  • Brain Informatics: Connectivity Modeling from Neuroimaging, Cognitive Performance Assessment, Biomarker Identification,
    Disease Diagnosis and monitoring