Edge Intelligence Lab

About us

Welcome to the Edge Intelligence Laboratory! Our team is initiated by Assoc. Prof. Chuntao Ding. Our laboratory is dedicated to the cutting-edge field of Edge Intelligence, where we explore the intersection of artificial intelligence and edge computing. Our diverse and talented team comprises both Ph.D. and Master’s students, each bringing unique perspectives and expertise to the table. Together, we form a dynamic group that fosters creativity, collaboration, and a shared passion for pushing the boundaries of edge intelligence. Led by a team of enthusiastic researchers, our mission is to develop innovative solutions that leverage the power of edge devices to process and analyze data locally, bringing intelligence closer to the source.

At the Edge Intelligence Lab, our primary research theme revolves around Edge Intelligence, which explores the integration of Artificial Intelligence and Machine Learning algorithms into edge devices. We are committed to advancing this field and making significant contributions to various domains, including IoT, smart cities, intelligent transportation, healthcare, and autonomous vehicles. By harnessing the power of edge computing and machine learning, we aim to build intelligent, efficient and secure systems that can operate seamlessly in real-time, right at the edge of the network.

For more info

Research Institute: School of Artificial Intelligence, Beijing Normal University.
Email: ctding@bnu.edu.cn

Selected publications

2025

TSC

A Resource-Efficient Multiple Recognition Services Framework for IoT Devices

Chuntao Ding, Zhuo Liu, Ao Zhou, and 3 more authors

IEEE Transactions on Services Computing, 2025

Bib

@article{ding.tsc2024a-resource-efficient,
  author = {Ding, Chuntao and Liu, Zhuo and Zhou, Ao and Yu, Jinhui and Li, Yidong and Wang, Shangguang},
  journal = {IEEE Transactions on Services Computing},
  title = {A Resource-Efficient Multiple Recognition Services Framework for IoT Devices},
  year = {2025},
  volume = {18},
  number = {1},
  pages = {29-42},
  doi = {10.1109/TSC.2024.3512949},
}

2024

TMC

A Resource-Efficient Feature Extraction Framework for Image Processing in IoT Devices

Chuntao Ding, Yidong Li, Zhichao Lu, and 2 more authors

IEEE Transactions on Mobile Computing, 2024

Bib

@article{ding.tmc2024a-resource-efficient,
  title = {A Resource-Efficient Feature Extraction Framework for Image Processing in IoT Devices},
  author = {Ding, Chuntao and Li, Yidong and Lu, Zhichao and Wang, Shangguang and Guo, Song},
  journal = {IEEE Transactions on Mobile Computing},
  year = {2024},
  volume = {23},
  number = {1},
  pages = {42--55},
  doi = {10.1109/TMC.2022.3218402},
}

2023

CVPR

Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives

Chuntao Ding, Zhichao Lu, Shangguang Wang, and 2 more authors

In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Bib

@inproceedings{ding.cvpr2023mitigating,
  title = {Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives},
  author = {Ding, Chuntao and Lu, Zhichao and Wang, Shangguang and Cheng, Ran and Boddeti, Vishnu Naresh},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages = {7756--7765},
  year = {2023},
  doi = {10.1109/CVPR52729.2023.00749}
}

TMC

Towards Transmission-Friendly and Robust CNN Models over Cloud and Device

Chuntao Ding, Zhichao Lu, Felix Juefei-Xu, and 3 more authors

IEEE Transactions on Mobile Computing, 2023

Bib

@article{ding.tmc2023towards,
  title = {Towards Transmission-Friendly and Robust CNN Models over Cloud and Device},
  author = {Ding, Chuntao and Lu, Zhichao and Juefei-Xu, Felix and Boddeti, Vishnu Naresh and Li, Yidong and Cao, Jiannong},
  journal = {IEEE Transactions on Mobile Computing},
  year = {2023},
  volume = {22},
  number = {10},
  pages = {6176--6189},
  doi = {10.1109/TMC.2022.3186496}
}

TPDS

TFormer: A Transmission-Friendly ViT Model for IoT Devices

Zhichao Lu, Chuntao Ding, Felix Juefei-Xu, and 3 more authors

IEEE Transactions on Parallel and Distributed Systems, 2023

Bib

@article{lu.tpds2023tformer,
  title = {TFormer: A Transmission-Friendly ViT Model for IoT Devices},
  author = {Lu, Zhichao and Ding, Chuntao and Juefei-Xu, Felix and Boddeti, Vishnu Naresh and Wang, Shangguang and Yang, Yun},
  journal = {IEEE Transactions on Parallel and Distributed Systems},
  volume = {34},
  number = {2},
  pages = {598--610},
  year = {2023},
  doi = {10.1109/TPDS.2022.3222765}
}

2022

TMC

Resource-aware Feature Extraction in Mobile Edge Computing

Chuntao Ding, Ao Zhou, Xiulong Liu, and 2 more authors

IEEE Transactions on Mobile Computing, 2022

Bib

@article{ding.tmc2022resource-aware,
  title = {Resource-aware Feature Extraction in Mobile Edge Computing},
  author = {Ding, Chuntao and Zhou, Ao and Liu, Xiulong and Ma, Xiao and Wang, Shangguang},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {21},
  number = {1},
  pages = {321--331},
  year = {2022},
  doi = {10.1109/TMC.2020.3007456}
}