Fengqing Maggie Zhu
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Associate Professor Purdue University Office: MSEE 334 |
Brief Biography
Fengqing Maggie Zhu is an Associate Professor of the Elmore Family School of Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana.
Dr. Zhu received the B.S.E.E. (with highest distinction), M.S. and Ph.D. degrees in Electrical and Computer Engineering from Purdue University in 2004, 2006 and 2011, respectively. Prior to joining Purdue in 2015, she was a Staff Researcher at Futurewei Technologies, where she received a Certification of Recognition for Core Technology Contribution in 2012.
Dr. Zhu is the recipient of an NSF CISE Research Initiation Initiative (CRII) award, a Google Faculty Research Award, and an ESI and trainee poster award for the NIH Precision Nutrition workshop. Her group’s work on visual coding for machines has received the Best Algorithms Paper Award at the Winter Conference on Applications of Computer Vision (WACV) 2023 and the Best Paper Finalists at the Picture Coding Symposium (PCS) 2022. She received the Purdue Seed for Success Awards in 2018 and 2020, and was named Outstanding Engineering Teacher in 2023.
Dr. Zhu is currently serving as an Associate Editor for the IEEE Transactions on Multimedia (2025 - present). She was a former Assocaite Editor of the IEEE Transactions on Circuits and Systems for Video Technology (2021-2024). She is the Vice Chair of the IEEE Signal Processing Society Technical Committee on Multimedia Signal Processing (2025-present) and an Elected Member of the IEEE Signal Processing Society Technical Committee on Image, Video, and Multidimensional Signal Processing (2025-present). She has served on the organizing and program committees of major conferences in her field and received recognition such as the Outstanding Area Chair for ICME 2021. Dr. Zhu is a senior member of the IEEE.
Dr. Zhu's research interests include smart health with a focus on image based dietary assessment and wearable sensor data analysis, visual coding for machines, and application-driven visual data analytics. Her research is supported by the National Science Foundation (NSF), National Institutes of Health (NIH), Office of Naval Research (ONR) and many industry sponsors such as Google, Eli Lilly, and HP Labs.
Research
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Past Projects:
Teaching
ECE 63400 – Digital Video Systems (Course materials are available to students enrolled in the class on Brightspace) Previous Offering
ECE438 – Introduction to Signal and Image Processing (formerly Digital Signal Processing with Applications) (Course materials are available to students enrolled in the class on Brightspace)
ECE301 – Signals and Systems (Course materials are available to students enrolled in the class on Brightspace)