Guohao Li

PhD student in Computer Science

KAUST

Biography

Guohao Li is currently a PhD student in Computer Science at King Abdullah University of Science and Technology (KAUST). He is a member of the Image and Video Understanding Laboratory (IVUL) in the Visual Computing Center (VCC), advised by Prof. Bernard Ghanem. During his PhD studies, he worked at Intel ISL as a research intern with Dr. Vladlen Koltun and Dr. Matthias Müller. He also visited Prof. Fisher Yu’s lab at ETHz as a visiting researcher. His primary research interests are Graph Machine Learning, Computer Vision and Embodied AI. He has published related papers in top tier conferences and journals such as ICCV, CVPR, ICML, NeurIPS, RSS and TPAMI.

Interests

Graph Machine Learning
Computer Vision
Embodied AI

Education

PhD in CS, 2018-
King Abdullah University of Science and Technology
MSc in EE, 2015-2018
University of Chinese Academy of Science
Joint MSc in CS, 2015-2018
ShanghaiTech University
BEng in EE, 2011-2015
Harbin Institute of Technology

Updates

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

Recent & Upcoming Talks

Sequential Greedy Architecture Search for CNN&GCN

Apr 21, 2020 6:15 PM

UMass, AI Tech Comments

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DeepGCNs for Representation Learning on Graphs

Dec 9, 2019 6:15 PM

Stanford, Google AI, Oxford, Emory, Baidu PGL, Cerebras Systems ML, KAUST Conference AI (Best Spotlight Award), NeurIPS Meetup 2019, NVIDIA GTC China 2019, M2Lschool2021, Jiangmen Live Streaming

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