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
[Aug. 2023] Hosted and Co-organized by DKU Edge Intelligence Lab, the first Amazon DeepRacer event will come to DKU on August 25th. Amazon DeepRacerĀ 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.
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[Aug. 2023] Federated Learning research proposal received 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 Shao, who will become a PhD student at HKUST this Fall co-supervised by me and Prof. Xuanyu Cao!
[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:
- Session 1 (7th June): Prof. Salman Avestimehr (USC), Dr. Chaoyang He (FedML), video online available.
- Session 2 (14th June): Prof. Leandros Tassiulas (Yale), Prof. Qiang Yang (WeBank & HKUST), vedio online available.
- Session 3 (21th June): Dr. Bing Luo (AIRS & Yale), Dr. Shiqiang Wang (IBM), vedio online available.
- Session 4 (28th June): Dr. Peter Kairouz (Google), Prof. Bo Li (UIUC), vedio online available.
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!!