Updates

• 2023/02/15: ~I will be joining Stanford University as a postdoc in April 2023.~ [Canceled]. I will explore somethings new.

• 2022/10/05: I defended my PhD dissertation on the Towards Structured Intelligence with Deep Graph Neural Networks! Sincerely thanks to everyone who has supported me on this journey!!!

• 2022/08/04: I received the CEMSE Dean’s List Award for academic year 2021-2022 at KAUST

• 2022/07/31: Paper LC-NAS accepted at CVPRW’22 and 3DV’22

• 2022/06/20 We organized a tutorial on Graph Machine Learning for Visual Computing at CVPR’22

• 2022/05/09 I joined KUMO.AI as the first intern. I worked with the PyG team as a core contributor

• 2022/03/01: Paper FLAG accepted at CVPR’22. Code is available on Github

• 2022/02/15: Tutorial Graph Machine Learning for Visual Computing accepted at CVPR’22. Stay tuned!

• 2022/03/01: Paper ASSANet accepted at NeurIPS’21 as Spotlight. Code is available on Github

• 2021/10/14: Our GNN1000 is on State of AI Report 2021 (page 67)

• 2021/05/08: Paper GNN1000 accepted at ICML’21. Code is available on Github

• 2021/04/07: I joined CVL at ETHz as a visiting researcher supervised by Prof. Fisher Yu

• 2021/04/05: Extension of Paper DeepGCNs accepted at TPAMI as a Regular Paper in the speical issue on Graphs in Vision and Pattern Analysis

• 2021/03/03: Paper PU-GCN accepted at CVPR’21. Code is available on Github

• 2021/01/05 I was selected as one of the winning students of Yearly Student Awards in CS program, CEMSE, KAUST

• 2020/10/26 AI-sports team won the first place in NEOM AI challenge (Entertainment track)

• 2020/08/01 I joined Intel ISL as a PhD research intern hosted by Dr. Vladlen Koltun & Dr. Matthias Müller

• 2020/06/13: Preprint of DeeperGCN is on arXiv. The code of experiments on OGB can be found on our Github Repo

• 2020/02/23: Paper SGAS accepted at CVPR’20. Code is available on Github Repo

• 2019/11/26: I was invited to give a talk about DeepGCNs and its follow-up works at NVIDIA GTC China 2019 (Dec. 16-19)

• 2019/10/12: Additional experiments of DeepGCNs on PPI and PartNet are available on our Github Pytorch Repo. The preprint of our journal extension is on arxiv now

• 2019/08/01: Paper DeepGCNs accepted as Oral at ICCV’19. Code is available on Github

• 2019/04/30: Paper OIL accepted at RSS’19