Dr. Na Zou
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
2024/7: Dr. Zou's paper won best paper award at ICQSR24, Como, Italy.
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
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
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