Dr. Na Zou
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Assistant Professor Email: nzou2@uh.edu |
Biography
Dr. Na Zou is a tenure-track assistant professor in the Department of Industrial Engineering. Her research interests focus on developing effective, efficient and trustworthy machine learning algorithms for tackling data challenges arising from large-scale, dynamic and networked data from various real-world applications, such as health informatics and bioinformatics. Specifically, Dr. Zou’s research focuses on shortcut 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, IEEE Transactions, ICLR, ICML, NeurIPS and KDD, including Best Paper Finalists, Best Student Paper Finalists, and Best Paper Awards at INFORMS, ICQSR, AMIA. Her work has been featured twice in ISE Magazine and received one student innovation award at AMIA. She is the recipient of IEEE Irv Kaufman Award, Texas A&M Institute of Data Science Career Initiation Fellow and NSF CAREER Award.
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News
2024/10: Dr. Zou received an NIH AIM AHEAD award, as MPI, on Improving Heart Transplant through Trustworthy AI/ML Approaches.
2024/08: Dr. Zou received an NSF CISE award, as PI, on Robust and Human-aligned Deep Learning for Medical-Sensor Time Series.
2024/07: Dr. Zou's paper won best paper award at ICQSR24, Como, Italy.
2023/10: Dr. Zou received an NSF III Medium award, as PI, on Effective Detection and Mitigation for Shortcut Learning.
2023/08: Dr. Zou talked to the Eagle newspaper about how artificial intelligence systems may impact operations in local city government.
2023/08: Dr. Zou was interviewed by KAGS News (NBC) on the potential impact of trustworthy machine learnig.
2023/05: Dr. Zou received the NSF CAREER award.
2023/04: 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
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Best Paper Award, 2024
The 2nd INFORMS Conference on Quality, Statistics and Reliability
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Best Student Paper Finalist, 2023
The AMIA 2023 Annual Symposium
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Faculty Early Career Development Program (CAREER), 2023
National Science Foundation
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Knowledge Discovery and Data Mining (KDDM) Student Innovation Award, 2022
The AMIA 2022 Annual Symposium
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Best Student Paper Award Finalist, 2022
The AMIA 2022 Annual Symposium
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Texas A&M Institute of Data Science Career Initiation Fellow, 2021
Texas A&M University
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Best Student Paper Award Finalist, 2019
INFORMS QSR
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Best Paper Award Finalist, 2019
INFORMS QSR
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Featured in ISE Magazine, 2018
Institute of Industrial and Systems Engineers (IISE)
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TEES Travel Grant for NSF Workshop，2017
Texas A&M University
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Selected to New Faculty Colloquium，2017
Institute of Industrial and Systems Engineers (IISE)
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Irv Kaufman Award, 2015
IEEE Foundation
Research Interests
Machine Learning: Shortcut 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