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Introduction

The DKU Edge Intelligence Lab, under the guidance of Dr. Bing Luo, is dedicated to the exploration and advancement of cutting-edge interdisciplinary research, spanning federated and distributed machine learning, wireless communications, networking, game theory, and optimization, with practical applications in edge-based artificial intelligence (Edge AI), privacy computing, Internet of Things (IoT), and the evolution of 5G/6G wireless systems.

News

[July. 2024] We will organize the “Tech4Good: Economic and Computational Advances in Distributed Systems” workshop at the 44th IEEE International Conference on Distributed Computing Systems (ICDCS) 2024 in New Jersey. Schedule can be found here.

[May. 2024] Received DKU-Duke Travel Grant to support my travel to Duke University in the coming year.

[May. 2024] Received Hou Tu Research (HTR) Fund from DKU Foundation, to support my interdisciplinary research with Wuhan University.

[Apr. 2024] Three of my supervised DKU undergraduate teams have won 2024 Student Innovation and Entrepreneurship (Dachuang) Project funding — two at the National level and one at the Provincial level. Congratulations to the teams!

[Apr. 2024] Our paper “Tackling System-Induced Bias in Federated Learning: A Pricing-based Incentive Mechanism” got accepted in IEEE ICDCS 2024, Federated Learning Track. This is a joint work with student and faculty at SUSTech..

[Mar. 2024] Our paper “Optimal Mechanism Design for Heterogeneous Client Sampling in Federated Learning” got accepted in IEEE Transactions on Mobile Computing (TMC). This is a joint work with SYSU and ZJU-UIUC.

[Mar. 2024] We presented our FedCampus and FedKit projects at the Flower AI Summit 2024, one of the world’s largest Federated Learning conference, in London, UK.

[Mar. 2024] Our paper on federated unlearning got accepted in Privacy Regulation and Protection in Machine Learning Workshop at ICLR 2024 (PML-ICLR’ 24).

[Feb. 2024] My lab organized a Generative AI field trip at AWS Shanghai, with details can be found here.

[Feb. 2024] Our paper “Adaptive Heterogeneous Client Sampling for Federated Learning over Wireless Networks” got accepted at IEEE Transactions on Mobile Computing (TMC).

[Feb. 2024] Our work “FedKit: Enabling Cross-Platform Federated Learning for Android and iOS” got accepted at IEEE INFOCOM 2024 Demo. Congratulations to my supervised DKU undergraduate students Sichang He (lead), Beilong Tang, and Boyan Zhang on this system project. Demo video is available on both YouTube and Bilibili. Details refer to research highlights.

[Feb. 2024] We are orgnizing a fieldtrip to AWS Shanghai, the theme is about GAI.

[Feb. 2024] Delighted to have been elevated to IEEE Senior member.

[Jan. 2024] Two FL papers got accepted in ICC 2024, one on “Client Sampling in Wireless Networks” ; one on “Federated Unlearning”.

[Dec. 2023] One paper on “Personalized LDP for FL” got accepted in ICASSP 2024, collaborative work in supervising undergraduate students at ZJU-UIUC.

[Nov. 2023] Federated Campus (FedCampus) is an application of the privacy protection on smart devices using Federated Learning and Federated Analytics techniques. It aims to provide an insight of the DKU campus with data privacy protection mechanism. Each participant will get a watch for tracking the health data for our research. This project launches at 2023/11/24.

[Aug. 2023] Hosted and Co-organized by DKU Edge Intelligence Lab, the first Amazon DeepRacer event will come to DKU on August 25th. Amazon DeepRacer is the fastest way to get rolling with reinforcement learning (RL) with a fully autonomous 1/18th scale race car driven by reinforcement learning, 3D racing simulator, and a global racing league. Developers can have the unique opportunity to get hands-on to train, evaluate, and tune RL models in the online simulator, deploy their models onto Amazon DeepRacer for a real-world autonomous experience.



[Aug. 2023] Federated Learning research proposal received 1,000,000 RMB funding from the 2023 Suzhou Basic Research Program (Frontier Technology Research). This project (PI: Dr. Bing Luo) is joint with China Mobile (Suzhou) R&D Center and Soochow University.
[Jun. 2023] Our paper on differential private federated analytics has been accepted by Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities(FL-ICML’23). Congratulations to my supervised CUHKSZ undergraduate student Jiaqi Shan.

[May. 2023] Our paper on federated reinforcement learning for robotics has been accepted by ICDCS 2023 Demo and Poster program. Congratulations to my supervised CUHKSZ undergraduate students Wenli Xiao (admitted by CMU Robotics Institute) and Tingwei Ye(now in NYU)!

[Apr. 2023] Our paper on incentivizing unbiased federated learning has been accepted to ICDCS 2023 (Track on AI for Distributed Systems and Distributed Systems for AI)

[Mar. 2023] Our paper “Optimization Design for Federated Learning in Heterogeneous 6G Networks” got accepted in IEEE Network, Special Issue on 6G Network AI Architecture for Customized Services and Applications, 2023.

[Jan. 2023] I was elected as the Executive Committee at the Technical Committee of Computational Economics (TCCE), China Computer Federation (CCF)

[Sep. 2022] I joined Duke Kunshan University (DKU) as a Tenure-Track Assistant Professor.

[June, 2022] Prof. Jianwei Huang and I have organized a series of federated learning online seminars at AIRS in this June. The invited speakers and talk details are as follows:

Recruiting

Interested applicants (majoring in EE/CS or related) with strong mathematical and machine learning backgrounds, please email me your CV, transcript, awards, and publications (if any) at bing.luo@dukekunshan.edu.cn.

Note: please make your email subject as [PhD/RA/research scientist/Intern Application] Name-School-Major.

Scholarship/Salary will be highly competitive!!

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