Huaiyu Dai
Professor
Education
-
Ph.D.
2002
Electrical Engineering
Princeton University, NJ -
Master's
1998
Electrical Engineering
Tsinghua University, Beijing
Research Focus
- Communications and Signal Processing
Recent Publications
- Learning-Based Data Gathering for Information Freshness in UAV-Assisted IoT Networks (2023)
- Multi-Job Intelligent Scheduling With Cross-Device Federated Learning (2023)
- 60 GHz Outdoor Propagation Measurements and Analysis Using Facebook Terragraph Radios (2022)
- A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions (2022)
- A Truthful Auction for Graph Job Allocation in Vehicular Cloud-Assisted Networks (2022)
- Communication Efficient Federated Learning With Energy Awareness Over Wireless Networks (2022)
- Communication-Efficient Federated Learning via Predictive Coding (2022)
- Dynamic Interference Management for UAV-Assisted Wireless Networks (2022)
- Federated Learning via Plurality Vote (2022)
- Graph Neural Networks Meet Wireless Communications: Motivation, Applications, and Future Directions (2022)
Highlighted Awards
- University Faculty Scholars (2018)
Awards & Honors
- 2019 - Qualcomm Faculty Award
- 2018 - University Faculty Scholar
- 2017 - Best Paper Award, IEEE ICC
- 2017 - Executive Editorial Committee Member, IEEE Transactions on Wireless Communications
- 2017 - IEEE Fellow
- 2016 - Best Paper Award, IEEE INFOCOM BIGSECURITY Workshop
- 2015 - Area Editor, IEEE Transactions on Communications
- 2010 - Best Paper Award, IEEE MASS
Recent News
AI Researchers Tackle Longstanding ‘Data Heterogeneity’ Problem for Federated Learning
Posted on July 15, 2022 | Filed Under: News
NC State ECE researchers have developed a new approach to federated learning that allows them to develop accurate artificial intelligence (AI) models more quickly and accurately.
NC State ECE Faculty Members Ranked as Top Electronics and Electrical Engineers in United States
Posted on March 3, 2022 | Filed Under: News
Fourteen ECE faculty members have been ranked as the Top Electronics and Electrical Engineering Scientists in the United States.
Technique Smooths Path for ‘Federated Learning’ AI Training in Wireless Devices
Posted on February 1, 2022 | Filed Under: News
A new federated learning technique from ECE researchers drastically reduces the size of data transmissions, creating new opportunities for wireless AI training.