Xuanyi Dong

About Me ([GitHub] [Google Scholar] [Full Publications])

I am a research scientist at Google Brain. I received a Ph.D. degree from the School of Computer Science, University of Technology Sydney (UTS). My research interests included automated deep learning (AutoDL) and its application to real world problems. In the past, I was fortunate to work at Google, Facebook, Amazon, Microsoft, UTS, etc.

Selected Industrial Experience

Feb 2022 - Present, Research Scientist, Google Brain
Jul 2021 - Feb 2022, Applied Scientist, Amazon Web Services (AWS) AI
Jan 2016 - Jun 2021, Researcher at Google, Facebook (Meta), Microsoft, Baidu, Alibaba, etc.

Selected Invited Talks

May 2021: Extend the Search from Arch to HP, Hardware, System, Keynote Speaker at NAS@ICLR2021
Apr 2021: Extend the Search from Architecture to HP, Hardware, System, 4Paradigm, MSRA
Sep 2020: Efficient Differentiable Automated Deep Learning, UT Austin
Summer 2020: Towards Efficient and Reproducible NAS, Baidu USA, 1st VALSE Student Seminar
Summer 2019: Efficient NAS and Its Applications to Computer Vision, YITUTech, Baidu, SCUT, SUST

Selected Publications

AutoHAS: Efficient Hyperparameter and Architecture Search
Xuanyi Dong, Mingxing Tan, Adams Wei Yu, Daiyi Peng, Bogdan Gabrys, Quoc V. Le
in NAS@ICLR, 2021
[arXiv] [Slides] [BibTex]
A weight sharing-based hyperparameter and architecture search approach, improving MobileNet/ResNet/EfficientNet/BERT.

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size
Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys
in IEEE TPAMI, 2021
[arXiv] [IEEE] [API] [Package] [Project] [BibTex] [ICLR]
An algorithm-agnostic NAS benchmark with information of 15,625 neural cell candidates for architecture topology and 32,768 for architecture size on three datasets, and we also provide 13 NAS baselines in a single codebase.

Network Pruning via Transformable Architecture Search
Xuanyi Dong and Yi Yang
in NeurIPS, 2019
[arXiv] [NeurIPS] [Code] [Logs] [Project] [Poster] [BibTex]
Search for the network size in a differentiable way.

Searching for A Robust Neural Architecture in Four GPU Hours
Xuanyi Dong and Yi Yang
in CVPR, 2019
[ arXiv ] [ CVPR ] [ Code ] [ BibTex ]
Introduce differentiable neural sampling into gradient-based NAS.

Awards and Honors

2021 Global Top 100 Chinese Rising Stars in AI
Google PhD Fellowship (2019) and Baidu Scholarship (2020)
AutoCV2 2019: IMAGE + VIDEO Automated Computer Vision challenge, Rank 4st / 34 teams.
TRECVID 2016: Video Localization Task, Rank 1st.
ILSVRC 2015: Rank 3rd on Object Detection and 2nd on Object Localization.
ACM International Collegiate Programming Contest (ICPC) (2014~2015): 2 Gold and 1 Silver Medals.

Academic Services

Executive Area Chair at Vision And Learning SEminar (VALSE) [SIX]

Senior Area Chair at AutoML Conference 2022

Organizer
ICCV 2021 Workshop -- Neural Architectures: Past, Present and Future

Journal Reviewer
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPMAI)
International Journal of Computer Vision (IJCV)
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
Pattern Recognition (PR) [Outstanding Reviewer]

Conference Reviewer or Senior Program Committee
Neural Information Processing Systems (NeurIPS) 2019 - 2022
International Conference on Machine Learning (ICML) 2021 - 2022
International Conference on Learning Representations (ICLR) 2021 - 2022
Computer Vision and Pattern Recognition (CVPR) 2019 - 2022
European Conference on Computer Vision (ECCV) 2020
International Conference on Computer Vision (ICCV) 2019, 2021
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2021
AAAI Conference on Artificial Intelligence (AAAI) 2020 - 2022
International Joint Conference on Artificial Intelligence (IJCAI) 2020 - 2022