Kaiqi Zhao

Research Interests

Efficient AI, Machine Learning/Deep Learning Model Compression (Knowledge Distillation, Pruning, Quantization), Distributed/Cloud/Edge Computing

Short Bio

Kaiqi Zhao (赵凯琪) 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 (2023–2025) 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 (2022–2025), ICML (2022–2025), ICLR (2024–2025), AAAI (2023–2025), AISTATS (2024–2025), ICASSP (2024–2025), and Interspeech (2023–2025), as well as for leading journals such as the IEEE Internet of Things Journal (Impact Factor: 11.1), IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 10.2), IEEE Transactions on Circuits and Systems for Video Technology (Impact Factor: 8.3), and IEEE Transactions on Intelligent Vehicles (Impact Factor: 8.2).

News

We have 2 Ph.D. positions starting in Fall 2025, Winter 2026, or Fall 2026. If you're interested in efficient CV, VLM, LLM, or Generative AI, please send your CV to kaiqizhao@oakland.edu.

• June 2025: Invited as a distinguished speaker at TechFusion 2025: AI, Cybersecurity, and Emerging Trends in Computer Science, taking place in Singapore on 22-23 September 2025.
• June 2025: Invited as a speaker at at the International Conference on Machine Learning, Artificial Intelligence, and Data Science (ICMLAIDS 2026), taking place on March 20-21, 2026, in Florida, USA.
• June 2025: Attended CVPR 2025 and presented two posters.
• May 2025: Attended the ACSIC Symposium on Frontiers in Computing (SOFC) 2025 and gave a brief oral introduction of our lab.
• May 2025: Invited as a speaker at TechWorld 2025: Big Data, Computer Science and Information Technologies, Bali, Indonesia, August 2025.
• Apr 2025: Awarded the Travel Grant from the ACSIC Symposium on Frontiers in Computing (SOFC) 2025.
• Apr 2025: Achieved an average student evaluation of 4.7/5.0 (12 students) for CIS 4140 and 5.0/5.0 (11 students) for CIS 5140 (Deep Learning and Applications) in Winter 2025.
• Apr 2025: One paper accepted to the Women in Computer Vision Worksop (WiCV) at CVPR 2025.
• Mar 2025: One paper accepted to the CVPR 2025 Workshop on Efficient Large Vision Models (ELVM).
• Mar 2025: Awarded the Faculty Research Fellowship from Oakland University.
• Mar 2025: One paper accepted to ICDCS 2025.
• Jan 2025: Served as a reviewer for the U.S. National Science Foundation (NSF).
• Jan 2025: Achieved an average student evaluation of 5.0/5.0 for CIS 4140 and 4.9/5.0 for CIS 5140 (Deep Learning and Applications) in Fall 2024.
• Oct 2024: Delivered an invited talk titled "Revolutionizing Edge AI: Enhanced and Automated Model Compression" at the Seminar of Lightning Research Talks in AI at the Michigan Celebration of Women in Computing conference.
• Aug 2024: Welcomed my first full-time Ph.D. student, Justin Kur.
• Aug 2024: Joined Oakland University as a tenure-track Assistant Professor in the Computer Science and Engineering Department.
• May 2024: One paper accepted and presented at AISTATS 2024.
• Apr 2024: Successfully defended my Ph.D. dissertation.
• Jan 2024: Awarded the Graduate College Completion Fellowship, one of the highest honors given to graduate students in the School of Computing and Augmented Intelligence (two recipients annually).
• Dec 2023: Received the Best Poster Award at ACM/IEEE SEC 2023.
• Jun 2023: One paper accepted and presented in the oral session at ICASSP 2023.
• Apr 2023: One paper accepted and presented at AISTATS 2023.
• Sep 2022: One paper accepted and presented in the oral session at Interspeech 2022.
• Jul 2019: One paper accepted and presented at ACM/IEEE HotEdge 2019.
• May 2019: One paper accepted and presented at USENIX OpML 2019.

Professional Experience

Oakland University, Computer Science and Engineering Department, Rochester, MI
Tenure-Track Assistant Professor, August 2024 – Present
Arizona State University, School of Computing and Augmented Intelligence (SCAI), Tempe, AZ
• Research Assistant / Graduate Student Assistant, August 2018 – May 2024
• Instructor Assistant, October 2023 – December 2023
• Instructor, August 2019 – May 2020
• Teaching Assistant, August 2018 – May 2022
Amazon Web Services, Inc.
• Applied Scientist Intern, Santa Clara, CA, May 2022 – August 2022
• Applied Scientist Intern, Santa Clara, CA, May 2021 – August 2021
• Applied Scientist Intern, East Palo Alto, CA, May 2020 – August 2020
Beihang University, School of Software, Beijing, China
• Research Assistant, September 2015 – March 2018
• Teaching Assistant, September 2016 – December 2017
Venture Commune Investment Development Co. Ltd., Beijing, China
Data Scientist Intern, June 2016 – December 2017

Selected Publications

Conference Papers:

• CVPR'25: Beyond STE: A Curriculum-Driven Backpropagation Method for Quantization-Aware Training
  K. Zhao
  Women in Computer Vision Worksop (WiCV) at IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), June 2025.
• CVPR'25: Progressive Element-wise Gradient Estimation for Neural Network Quantization
  K. Zhao
  IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) Workshop on Efficient Large Vision Models (ELVM), June 2025.
• ICDCS'25: Smart Blue Light Pole-based Real-Time Crowd Counting for Smart Campuses
  Y. Chen, K. Zhao, K. Gundu, Z. Zaidi, M. Zhao
  45th IEEE International Conference on Distributed Computing Systems (ICDCS), July 2025. (Acceptance Rate: 19.7%)
• AISTATS'24: Self-Supervised Quantization-Aware Knowledge Distillation
  K. Zhao, M. Zhao
  27th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024. (Acceptance Rate: 27.6%)
• SEC'23: Poster: Self-Supervised Quantization-Aware Knowledge Distillation
  K. Zhao, M. Zhao
  ACM / IEEE Symposium on Edge Computing (SEC), December 2023. (Best Poster Award)
• ICASSP'23 (Oral): A Contrastive Knowledge Transfer Framework for Model Compression and Transfer Learning
  K. Zhao, Y. Chen, M. Zhao
  IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2023. (Oral)
• AISTATS'23: Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions
  K. Zhao, A. Jain, M. Zhao
  26th International Conference on Artificial Intelligence and Statistics (AISTATS), April 2023. (Acceptance Rate: 29%)
• Interspeech'22 (Oral): Knowledge Distillation via Module Replacing for Automatic Speech Recognition with Recurrent Neural Network Transducer
  K. Zhao, H. D. Nguyen, A. Jain, N. Susanj, A. Mouchtaris, L. Gupta, M. Zhao
  23rd Interspeech Conference, September 2022. (Oral)
• HotEdge'19: Exploring the Use of Synthetic Gradients for Distributed Deep Learning across Cloud and Edge Resources
  Y. Chen, K. Zhao, B. Li, M. Zhao
  2nd USENIX Workshop on Hot Topics in Edge Computing (HotEdge), July 2019. (Acceptance Rate: 29%)
• OpML'19: KnowledgeNet: Disaggregated and Distributed Training and Serving of Deep Neural Networks
  S. Biookaghazadeh, Y. Chen, K. Zhao, M. Zhao
  USENIX Conference on Operational Machine Learning (OpML), May 2019

Preprints:

• Data-Augmented Quantization-Aware Knowledge Distillation
  J. Kur, K. Zhao
  Under review
• Mitigating the Environmental Impact of Generative AI for Sustainability
  K. Zhao, D. Sui, T. Sanchez, S. Shaw, Y. Fu, W. Gong, H. Liu, X. Huang, J. Jiao, X. Ye
  Under review

Awards

• ACSIC Symposium on Frontiers in Computing (SOFC) Travel Grant, 2025
• Faculty Research Fellowship, Oakland University, 2025
• Nomination of Dean’s Dissertation Award, Arizona State University, 2024
• Graduate College Completion Fellowship, Arizona State University, 2024
  The most prestigious award given to graduate students in the School of Computing and Augmented Intelligence (two recipients per year).
• ACM/IEEE Symposium on Edge Computing (SEC) NSF Best Poster Award, 2023
• ACM/IEEE Symposium on Edge Computing (SEC) NSF Student Travel Grant, 2023
• School of Computing and Augmented Intelligence (SCAI) Doctoral Fellowship, Arizona State University, 2023
• School of Computing and Augmented Intelligence (SCAI) Doctoral Fellowship, Arizona State University, 2022
• ACM/IEEE Symposium on Edge Computing (SEC) NSF Student Travel Grant, 2021
• National Graduate Fellowship, Beihang University, China, 2017
  The most prestigious award given to graduate students in the department of software engineering (five recipients per year).
• Excellence Award in the Global Competition of the Open Innovation Business Contest 5.0 of NTT DATA, Japan, 2017
  Represented the sole champion team from China, garnering media coverage from prominent mainstream outlets, e.g., PEOPLE.CN, NTT DATA, and Beihang University.
• Champion Winner in China Contest Division of the Open Innovation Business Contest 5.0 of NTT DATA, China, 2017
• Outstanding Graduate Fellowship, Beihang University, China, 2016
• Overseas Education and Practice Award, Beihang University, China, 2016
• Academic Excellence Fellowship, Beihang University, China, 2016
• Excellent Student Fellowship, Beihang University, China, 2016

Professional Services

Conference Chair

• SEC: ACM/IEEE Symposium on Edge Computing Ph.D. Forum Chair, 2021

Program Committee Member

• The 39th Annual AAAI Conference on Artificial Intelligence, 2025
• The 38th Annual AAAI Conference on Artificial Intelligence, 2024
• The 37th Annual AAAI Conference on Artificial Intelligence, 2023

Invited Reviewer

• U.S. National Science Foundation (NSF) Reviewer, 2025
• NeurIPS, 2025, 2024, 2023, 2022
• ICML, 2025, 2024, 2023, 2022
• ICLR, 2025, 2024
• AAAI, 2025, 2024, 2023
• AISTATS, 2025, 2024
• ICASSP, 2025, 2024
• InterSpeech, 2025, 2024, 2023
• MLSP, 2025, 2023
• HotEdge, 2020
• IEEE Internet of Things Journal (Impact Factor: 11.1), 2025
• IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 10.2), 2025
• IEEE Transactions on Circuits and Systems for Video Technology (Impact Factor: 8.3), 2025
• IEEE Transactions on Intelligent Vehicles (Impact Factor: 8.2), 2025
• IEEE Transactions on Artificial Intelligence (Impact Factor: 5.94), 2025
• Journal of Marine Science and Engineering (Impact Factor: 2.8), 2025
• Energies (Impact Factor: 3.3), 2025
• Engineering Reports (Impact Factor: 2.29), 2025
• ACM Transactions on Asian and Low-Resource Language Information Processing (Impact Factor: 2.0), 2025
• Electronics (Impact Factor: 2.6), 2025
• IEEE Transactions on Computers (Impact Factor: 3.7), 2025

Internal Committees

• Member of Ph.D. Subcommittee, Computer Science and Engineering Department, Oakland University, Fall 2024 – Present

Teaching

Instructor

• CIS 4140/5140— Deep Learning and Applications
  Winter 2025, 24 students, Oakland University
  Fall 2024, 14 students, Oakland University
  Average student evaluation in Winter 2025: 4.7/5.0 (CSI 4140, Evaluation Report), 5.0/5.0 (CSI 5140, Evaluation Report)
  Average student evaluation in Fall 2024: 5.0/5.0 (CSI 4140, Evaluation Report), 4.9/5.0 (CSI 5140, Evaluation Report)
• CSE 486 — Capstone Projects II
  Spring 2020, 144 students, Arizona State University
• CSE 485 — Capstone Projects I
  Fall 2019, 100 students, Arizona State University

Guest Lecturer

• CSE 531 — Distributed and Multiprocessor Operating Systems
  Fall 2023, 60 students, Arizona State University
  Topic: Intelligent Cloud+Edge Computing

Teaching Assistant

• CSE 531 — Distributed and Multiprocessor Operating Systems
  Fall 2023, 101 students, Arizona State University
• CSE 546 — Cloud Computing
  Spring 2022, 190 students, Arizona State University
  Spring 2021, 122 students, Arizona State University
• CSE 205 — Object-Oriented Program and Data
  Spring 2019, about 150 students, Arizona State University
  Fall 2021, about 150 students, Arizona State University
• CSE 230 — Computer Organization and Assembly Language Programming
  Summer 2019, 45 students, Arizona State University
• CSE 100 — Principles of Programming with C++
  Fall 2018, about 100 students, Arizona State University

Contact

Email: kaiqizhao@oakland.edu

LinkedIn: www.linkedin.com/in/kaiqizhao

Phone: 248-370-2211

Office: Room 514, Engineering Center, 115 Library Dr., Rochester, MI 48309