Na Zou

Professor pushing the boundaries of machine learning and industrial technology, Na Zou is an Assistant Professor in the Engineering Technology & Industrial Distribution Department at Texas A&M University. With a keen focus on advancing the fields of interpretable machine learning and fairness in machine learning, she is dedicated to developing innovative solutions that address complex challenges in network modeling, transfer learning, and anomaly detection. Dr. Zou's research is characterized by its interdisciplinary approach, bridging the gap between theoretical advancements and practical applications. Her work in network modeling and anomaly detection has been instrumental in enhancing the reliability and efficiency of industrial systems, while her contributions to fairness and interpretability in machine learning ensure that these technologies are accessible and equitable. Throughout her career, Dr. Zou has been recognized for her outstanding contributions to the field. She was a Best Student Paper Award Finalist at the INFORMS Quality, Statistics, and Reliability (QSR) conference in 2019, highlighting her commitment to excellence in research. Additionally, her innovative work was featured in ISE Magazine by the Institute of Industrial and Systems Engineers (IISE) in 2018, underscoring her influence and impact within the engineering community. At Texas A&M University, Dr. Zou is not only a dedicated researcher but also a passionate educator, inspiring the next generation of engineers and technologists. Her commitment to fostering a collaborative and inclusive learning environment is evident in her teaching and mentorship, where she encourages students to explore the intersections of technology and society.