معرفی
Xiaoqian Wang is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, with a courtesy appointment in Biomedical Engineering. She leads research in trustworthy machine learning, focusing on explainability, fairness, robustness, and healthcare applications. Her work has earned her the 2022 NSF CAREER Award and IEEE Senior Membership.
Education: PhD in Electrical Engineering from the University of Pittsburgh (2019), advised by Prof. Heng Huang; Bachelor's from Zhejiang University (2013).
Research interests include developing interpretable AI systems, mitigating algorithmic bias, and applying machine learning to healthcare challenges such as Alzheimer's disease progression modeling. Recent efforts explore spurious correlation mitigation in multi-task and vision-language models.
Awards and recognitions: Recipient of the NSF CAREER Award (2022), IEEE Senior Member status (2023+).
Teaching: Courses include ECE 264 (Advanced C Programming), ECE 570 (Artificial Intelligence), and ECE 695 (Machine Learning in Bioinformatics/Healthcare).
Lab affiliations: Regenstrief Center for Healthcare Engineering at Purdue University.
