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Chengshun Shang

PhD researcher
International Center for Numerical Methods in Engineering (CIMNE); Universitat Politècnica de Catalunya (UPC)
cshang (at) cimne.upc.edu


Short Bio

Chengshun Shang holds a Bachelor’s degree in Mining Engineering from Shandong University of Science and Technology (China), awarded in 2018. He later earned his Master’s degree in Geotechnical Engineering from Shandong University (China) in 2021. Since 2021, Chengshun has been pursuing his Ph.D. as a candidate at CIMNE, where he actively contributes as a developer to the open-source software Kratos Multiphysics (DEMApplication).

Over the past five years, Chengshun has dedicated his research efforts to the Discrete Element Method (DEM) and its coupling techniques, including DEM-CFD and DEM-FEM. His research primarily revolves around studying rock mechanical behavior and the evolution of geotechnical engineering disasters. His Ph.D. research focuses on establishing a numerical framework based on the Discrete Element Method for modeling the mechanics of both weak and strong sandstone.

NEED TO BE UPDATED

My research lies at the intersection of computer vision and machine learning – with a special focus on building intelligent visual systems that are continual and data-efficient. My research interests include continual learning, few-shot learning, semi-supervised learning, generative models, 3D geometry models, and medical imaging.

I am currently on the 2023-2024 academic job market, looking for faculty positions in CS, CSE, ECE, IEOR, etc., related to Artificial Intelligence, Computer Vision, and Machine Learning. Please feel free to contact me if you are interested. I am also happy to give talks on my research in related seminars.

News

Publications [Google Scholar][DBLP]

  1. Preprint
    Wufei Ma*, Qihao Liu*, Jiahao Wang*, Xiaoding Yuan, Angtian Wang, Yi Zhang, Zihao Xiao, Guofeng Zhang, Beijia Lu, Ruxiao Duan, Yongrui Qi, Adam Kortylewski, Yaoyao Liu, Alan Yuille
    ( Corresponding author)
    Under review.

  2. MICCAI
    Yixiao Zhang, Xinyi Li, Huimiao Chen, Alan Yuille, Yaoyao Liu, Zongwei Zhou
    ( Corresponding authors)
    International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023.

  3. CVPR
    Qianru Sun*, Yaoyao Liu*, Tat-Seng Chua, Bernt Schiele
    (* Equal contribution)
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

Teaching

Invited Talks

Learning from Imperfect Data: Incremental Learning and Few-shot Learning.

Meta-transfer Learning for Few-shot Learning.

Learning to Self-train for Semi-supervised Few-shot Classification.

Multi-class Incremental Learning.

Services

Organization Committee

Area Chairs

Senior Program Committee

Conference Reviewers

Journal Reviewers

Contact

Address: 3400 N. Charles St., Baltimore, MD 21218-2625
Office Location: Malone Hall 248
Email: cshang (at) cimne.upc.edu
Phone: (857) 209-8688



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