π’ We have 2 fully-funded Ph.D. positions starting in Winter 2026 or Fall 2026. If you're interested in joining the Efficient AI lab and working on efficient CV, VLM, or LLM, please fill out the recruiting form.
Efficient AI, Deep Learning Model Compression (Knowledge Distillation, Pruning, Quantization), Speech Recognition, Distributed/Cloud/Edge Computing
Kaiqi Zhao (θ΅΅ε―ηͺ) is a tenure-track assistant professor in the Computer Science and Engineering Department at Oakland University, Michigan, since August 2024.
She is the director of Efficient AI Lab.
She earned her Ph.D. degree in the School of Computing and Augmented Intelligence at Arizona State University under the supervision of
Prof. Ming Zhao.
Central to her research is innovating in model compression techniques to automatically and efficiently generate small, high-performance, and hardware-efficient machine learning/deep learning models,
catalyzing the advancement of AI on edge devices.
Her research efforts are aimed to generate both fundamental scientific values and practical societal impacts.
As the first author, she has published peer-reviewed papers at top-tier AI conferences, e.g., AISTATS, ICASSP (Oral), and InterSpeech (Oral), and top-tier edge computing conferences, e.g., ACM/IEEE SEC (Best Poster Award).
As a co-author, she has also published papers at prestigious system and edge computing conferences, e.g., IEEE ICDCS, USENIX HotEdge and USENIX OpML.
Her work on "Knowledge Distillation via Module Replacing for Automatic Speech Recognition" has been integrated into the Amazon Alex library for production usage.
She has been actively contributing to the research community by serving as a U.S. National Science Foundation (NSF) Reviewer (2025),
Program Committee (PC) member for AAAI (2026) and the Conference Ph.D. Forum chair for ACM/IEEE SEC (2021).
She has also served as an invited reviewer for top-tier AI conferences, including NeurIPS (2022β2025), ICML (2022β2025), ICLR (2024β2025), AAAI (2023β2025),
AISTATS (2024β2025), ICASSP (2024β2025), Interspeech (2023β2025), and AAMAS (2026),
as well as for leading journals such as the IEEE Internet of Things Journal (Impact Factor: 11.1), IEEE Transactions on Knowledge and Data Engineering (Impact Factor: 10.4),
IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 10.2), IEEE Transactions on Mobile Computing (Impact Factor: 9.2),
IEEE Transactions on Circuits and Systems for Video Technology (Impact Factor: 8.3), and IEEE Transactions on Intelligent Vehicles (Impact Factor: 8.2).
Email: kaiqizhao@oakland.edu
Phone: 248-370-2211
Office: Room 514, Engineering Center, 115 Library Dr., Rochester, MI 48309