Xiaoxi Zhang
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Xiaoxi Zhang

Xiaoxi Zhang 

Associate Processor,
School of Computer Science and Engineering
Sun Yat-sen University
Guangzhou, Guangdong, China

Office: Room 529L, NSCC Building
Phone: +86 020-39332111
E-mail: email img [AT] mail.sysu.edu.cn

About me

I received the B.E. degree in Electronics and Information Engineering from Huazhong University of Science and Technology (HUST) in 2013, and the Ph.D. degree in Computer Science from The University of Hong Kong (HKU) in 2017, under the supervision of Prof. Chuan Wu and Prof. Francis C.M. Lau. I was a Postdoctoral researcher during 2017-2020 in the department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), advised by Prof. Carlee Joe-Wong. In October of 2020, I joined the School of Computer Science and Engineering at Sun Yat-sen University (SYSU), as an Associate Professor (my official homepage at SYSU).

Research

My research interests include

  • Machine Learning

  • Distributed Systems

  • Edge Computing

  • Cloud Computing

  • 5G/6G Networks

Selected Recent Publications (full list, Google Scholar)

  1. "Rosevin: Employing Resource- and Rate-Adaptive Edge Super-Resolution for Video Streaming", IEEE INFOCOM 2024

  2. "TapFinger: Task Placement and Fine-Grained Resource Allocation for Edge Machine Learning", IEEE INFOCOM 2023 (journal version is published in TPDS)

  3. "An Offline-Transfer-Online Framework for Cloud-Edge Collaborative Distributed Reinforcement Learning", IEEE TPDS 2024

  4. "Learning with Side Information: Elastic Multi-resource Control for the Open RAN", IEEE JSAC 2024

  5. "AdaCoOpt: Leverage the Interplay of Batch Size and Aggregation Frequency for Federated Learning", IEEE/ACM IWQoS 2023 (Best paper candidate, top 6 in 264 submissions, journal version is published in IEEE TMC 2024)

  6. "EdgeC3: Online Management for Edge-Cloud Collaborative Continuous Learning", IEEE SECON 2023 (journal version will appear in TMC 2024)

  7. "Optimal Network Protocol Selection for Competing Flows via Online Learning", IEEE TMC 2023 (preliminary version appeared in IEEE ICNP 2019)

  8. "Machine Learning on Volatile Instances: Convergence, Runtime, and Cost Tradeoffs", IEEE/ACM ToN 2022 (preliminary version appeared in IEEE INFOCOM 2020)

  9. "Online Auctions in IaaS Clouds: Welfare and Profit Maximization with Server Costs", IEEE/ACM ToN 2017 (preliminary version appeared in ACM SIGMETRICS 2015)