EdgeAI refers to the ability to run various AI applications directly on edge devices, hence minimizing or even eliminating the need to rely on the cloud. Given its huge potential to enable new opportunities for various IoT applications (e.g., image classification, object detection, autonomous driving, language processing, etc.), edge computing/IoT is currently one of the hottest research areas. Our research is primarily focused on developing new energy-aware machine learning techniques and hardware prototypes that leverage the network and the system characteristics to enable edge/IoT computing.
International Conference on Learning Representations (ICLR), 2023.
Model Elasticity for Hardware Heterogeneity in Federated Learning Systems Proceedings Article
In: Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network (FedEdge), pp. 19-24, 2022.
In: ACM Transactions on Embedded Computing Systems (TECS), 2022.
In: The Conference on Robot Learning, 2021.
In: ACM Transactions on Embedded Computing Systems, vol. 20, no. 63, pp. 1-26, 2021.
In: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) , 2020.