Mengwei Xu

Assistant Professor, Doctoral Advisor
State Key Laboratory of Networking and Switching Technology Computer Science Department
Beijing University of Posts and Telecommunications (BUPT)
Office: 1107, Research Building (新科研楼), BUPT (Xituchen campus), Haidian District, Beijing, P.R.China, 100876
Email: mwx AT bupt DOT edu DOT cn
Here is my Curriculum Vitae.

I'm an assistant professor in Beijing University of Posts and Telecommunications (BUPT). I received my doctoral and bachelor degrees from Peking University in 2020 and 2015, co-advised by Prof. Gang Huang and Prof. Xuanzhe Liu. I was a visiting scholar at Purdue ECE in 2019, working with Prof. Felix Xiaozhu I interned at MSRA System group from Mar. 2015 to Mar. 2016, mentored by Dr. Yunxin Liu. I also visited MSRA from Dec. 2020 through the "star-track" program.

I always look for highly self-motivated undergraduates and graduates. Please directly send your CV to me if you find my research interesting.

Research

I work on systems software, with focus on resource-constrained platforms like mobile and edge. Recently, I'm pushing the vision of ubiquitous learning, meaning that machine learning (training) can happen on any devices at anytime. I'm working on several related projects with my students.

AI systems on resource-constrained devices, e.g., smartphones, wearables, and IoT cameras. We are maintaining a paper list for this area. Check it out!
[ATC'21] zero-streaming camera [MobiSys'20] autonomous camera [WWW'19] empirical study [TMC'19] wearable-smartphone orchestration [MobiCom'18] vision cache [UbiComp'18] on-device learning
Designing and optimizing mobile systems for better performance, privacy, and user experience.
[UbiComp'18] input privacy [EuroSys'18] power awareness [WWW'17] app collusion [TMC'17] mobile resource scheduling
Designing new federated learning platforms.
[WWW'21] Heterogeneity-aware [arXiv] LAN-aware [arXiv] self-adaptive

🔥🔥 We have built an end-to-end cross-device FL platform. Here is the full code and demo. The repo will be actively maintained and you are welcome to join us!


Conference Publications

Google Scholar | dblp (* = equal contributions)

[arXiv] Hierarchical Federated Learning through LAN-WAN Orchestration
Jinliang Yuan, Mengwei Xu, Xiao Ma, Ao Zhou, Xuanzhe Liu, Shangguang Wang.
-- Using LAN to accelerate federated learning: why not?
[arXiv] Neural Architecture Search over Decentralized Data
Mengwei Xu, Yuxin Zhao, Kaigui Bian, Gang Huang, Xuanzhe Liu.
-- Bring the automation and privacy together!
[IMC'21] From Cloud to Edge: A First Look at Public Edge Platforms
Mengwei Xu, Zhe Fu, Xiao Ma, Li Zhang, Yanan Li, Feng Qian, Shangguang Wang, Ke Li, Jingyu Yang, Xuanzhe Liu.
The Internet Measurement Conference (IMC). Acceptance rate = 28.1% (55/196).
[arxiv] [slides] [data]
-- Edge computing is coming!
[FSE'21] TaintStream: Fine-Grained Taint Tracking for Big Data Platforms through Dynamic Code Translation
Chengxu Yang, Yuanchun Li, Mengwei Xu, Zhenpeng Chen, Yunxin Liu, Gang Huang, Xuanzhe Liu.
The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2021. Acceptance rate = 24.5% (97/396).
[slides] [code]
[USENIX ATC'21] Video Analytics with Zero-Streaming Cameras
Mengwei Xu*, Tiantu Xu*, Yunxin Liu, and Felix Xiaozhu Lin.
USENIX ATC 2021. Acceptance rate = 18.8% (64/341). Accepted to appear
[arXiv] [MobiCom'20 Demo] [slides] [1-min Demo] [5-min Demo]
-- A totally new paradigm for video analytics systems
[EMDL'21] Towards Ubiquitous Learning: A First Measurement of On-Device Training Performance
Dongqi Cai, Qipeng Wang, Yuanqiang Liu, Yunxin Liu, Shangguang Wang, Mengwei Xu.
The International Workshop on Embedded and Mobile Deep Learning (EMDL), co-located with ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) 2021.
[slides] [code]
- Time to look at the on-device training system: how can we go further?
[MM'21] Boosting Mobile CNN Inference through Semantic Memory
Yun Li, Chen Zhang, Shihao Han, Li Lyna Zhang, Baoqun Yin, Yunxin Liu, Mengwei Xu.
The ACM Multimedia (MM) 2021. Acceptance rate = 27.9% (542/1942).
[slides]
-- Learn how cache works from our brains.
[WWW'21] Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
Chengxu Yang, Qipeng Wang, Mengwei Xu, Shangguang Wang, Kaigui Bian, Xuanzhe Liu.
The Web Conference 2021. Acceptance rate = 20.6% (357/1736).
[arXiv] [slides] [code & data]
-- Keep in mind: federated learning happens on heterogeneous smartphones!
[MobiSys'20] Approximate Query Service on Autonomous IoT Cameras
Mengwei Xu, Xiwen Zhang, Yunxin Liu, Gang Huang, Xuanzhe Liu, Felix Xiaozhu Lin.
In Proceedings of the International Conference on Mobile Systems, Applications and Services. Acceptance rate = 19.4% (34/175).
[website] [arXiv] [slides] [presentation] [short video]
-- Be intelligent and autonomous, my dear camera.
[WWW'19] A First Look at Deep Learning Apps on Smartphones
Mengwei Xu, Jiawei Liu, Yuanqiang Liu, Felix Xiaozhu Lin, Yunxin Liu, Xuanzhe Liu.
The Web Conference 2019. Acceptance rate = 18% (225/1247).
[arXiv] [slides] [code & data]
-- We have interesting findings about how DL is used in real-world smartphone apps!
[MobiCom'18] DeepCache: Principled Cache for Mobile Deep Vision
Mengwei Xu, Mengze Zhu, Yunxin Liu, Felix Xiaozhu Lin, and Xuanzhe Liu.
In Proceedings of the 24th Annual International Conference on Mobile Computing and Networking. Acceptance rate = 22% (42/187).
[arXiv] [slides] [code] [short video]
-- A fine-grained cache system to reduce CNN computations on redundant input.
[IMWUT'18] DeepType: On-Device Deep Learning for Input Personalization Service with Minimal Privacy Concern
Mengwei Xu, Feng Qian, Qiaozhu Mei, Kang Huang, and Xuanzhe Liu.
In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
[slides]
-- AFAIK, the first work to demonstrate the benefit and feasibility to train DNNs on smartphones.
[IMWUT'18] PrivacyShield: A Mobile System for Supporting Subtle Just-in-time Privacy Provisioning through Off-Screen-based Touch Gestures
Saumay Pushp, Yunxin Liu, Mengwei Xu, Changyoung Koh, and Junehwa Song.
In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
[EuroSys'18] Power Sandbox: Power Awareness Redefined
Liwei Guo*, Tiantu Xu*, Mengwei Xu, Xuanzhe Liu, and Felix Xiaozhu Lin.
In Proceedings of the 13th EuroSys Conference. Acceptance rate = 16% (43/262).
[WWW'17] AppHolmes: Detecting and Characterizing App Collusion among Third-Party Android Markets
Mengwei Xu, Yun Ma, Xuanzhe Liu, Felix Xiaozhu Lin and Yunxin Liu.
In Proceedings of the 26th International World Wide Web Conference. Acceptance rate = 17% (164/966).
-- Your apps can maliciously start each other from background.

Journal Publications

[IEEE Pervasive Computing'21] A Case for Camera-as-a-Service
Mengwei Xu, Yunxin Liu, Xuanzhe Liu.
IEEE Pervasive Computing, Special Issue on Pervasive Video and Audio.
-- Our ambitious vision about future video systems
[JoS'20] Autonomous Learning System towards Mobile Intelligence (in Chinese)
Mengwei Xu, Yuanqiang Liu, Kang Huang, Xuanzhe Liu, Gang Huang.
Journal of Software.
[TMC'19] DeepWear: Adaptive Local Offloading for On-Wearable Deep Learning
Mengwei Xu, Feng Qian, Mengze Zhu, Feifan Huang, Saumay Pushp, Xuanzhe Liu.
IEEE Transactions on Mobile Computing.
-- Your wearables deserve deep learning as well!
[TMC'17] ShuffleDog: Characterizing and Adapting User-Perceived Latency of Android App
Gang Huang, Mengwei Xu, Felix Xiaozhu Lin, Yun Ma, Yunxin Liu, Saumay Pushp, Xuanzhe Liu.
The International Workshop on Embedded and Mobile Deep Learning (EMDL), co-located with ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) 2021.
IEEE Transactions on Mobile Computing.
-- Multi-task GPU scheduling on smartphones.
[TSC'16] MUIT: A Domain-Specific Language and its Middleware for Adaptive Mobile Web-based User Interfaces in WS-BPEL.
Xuanzhe Liu, Mengwei Xu, Teng Teng, Gang Huang, Hong Mei.
The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2021. Acceptance rate = 24.5% (97/396)
IEEE Transactions on Services Computing.

Academic Services

  • Vice Program Chair
    IEEE SAGC 2021;
  • Session Chair
    IEEE CLOUD 2021;
  • TPC Member
    ICDCS 2021, BigCom 2021, MobiArch@MobiCom 2021, ICWS 2021;
    MobiSys'19 Rising Stars Forum;
  • (External) Reviewer
    IMWUT, TMC, TSC, TIST, etc.

Teaching

  • TA with Distributed Machine Learning Systems at Peking University (Fall 2019)
  • TA with Operating System Practice at Peking University (Fall 2016, Spring 2017)
  • TA with Introduction to Computing at Peking University (Fall 2014, 2016)
  • TA with Foundations of Computer Application at Peking University (Spring 2015)

Invited Talks


Materials


Last Updated: Aug. 2021