SHUO CHEN

I am currently a Research Scientist (≈Assistant Professor) at Center for Advanced Intelligence Project (AIP), RIKEN National Science Institute (理研), Japan.

Research Interest: I have a broad interest in machine learning and computer vision, in particular, metric learning, contrastive learning, regression analysis, subspace clustering, sparse representation, meta-learning, optimization, and deep learning.

I have moved to my new homepage.

Education & Experience: 

• Postdoc, Center for Advanced Intelligence Project, RIKEN National Science Institue, Japan,  August 2020 -- September 2023

• Visiting Ph.D., Data Science Lab, The University of Pittsburgh, USA,  November 2018 -- June 2019

• Algorithm Researcher, SenseTime, China,  August 2015 -- November 2015

• Ph.D. (D.Eng.), PCA-Lab, Nanjing University of Science and Technology (NJUST), China,  September 2016 -- July 2020

Awards & Honors

• Excellent Doctoral Dissertation Award, Chinese Institute of Electronics (CIE), China, 2022.

• RIKEN BAIHO Award (a.k.a. RIKEN Excellent Achievement Award,  Annual Selection Rate < 1%), RIKEN National Science Institute, Japan, 2022.

• Excellent Doctoral Dissertation Nomination, Chinese Association for Artificial Intelligence (CAAI), China, 2021.

• Excellent Doctoral Dissertation Award (Annual Selection Rate < 2%), Jiangsu Education Department, China, 2021.

• National Scholarship (Two Times, Annual Selection Rate < 2%), Ministry of Education, China, 2018 and 2019.

• Top 1% GPA Ranking, School of Computer Science & Engineering, NJUST, China, 2014 -- 2019.

• The 17th Mathematical Modeling Contest for Chinese Graduate Students, Honorable Mention, Ministry of Education, China, 2015.

• The 2nd  China Fuzzy Image Processing Contest, Honorable Mention, National Natural Science Foundation, China, 2015.

• The 34th Mathematical Modeling Contest for American College Students, Honorable Mention, SIAM, USA, 2013.

• The 2nd Software Programming Contest for Chinese College Students, Meritorious Winner, Ministry of Industry and Information Technology, China, 2012.

Selected Publications (Google Scholar)

Conference Papers

• Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama. Robust Similarity Learning with Difference Alignment Regularization, International Conference on Learning Representations (ICLR): 2024.

• Jie Xu, Shuo Chen, Yazhou Ren, Xiaoshuang Shi, Heng Tao Shen, Gang Niu, Xiaofeng Zhu. Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration, Advance in Neural Information Processing Systems (NeurIPS): 2023.

• Renke Wang (co-first), Guimin Que (co-first), Shuo Chen*, Xiang Li, Jun Li*, Jian Yang. Creative Birds: Self-Supervised Single-View 3D Style Transfer, International Conference on Computer Vision (ICCV): 2023.

• Jialiang Tang, Shuo Chen*, Gang Niu, Masashi Sugiyama, Chen Gong*. Distribution Shift Matters for Knowledge Distillation with Webly Collected Images, International Conference on Computer Vision (ICCV): 2023.

• Zhiqiang Yan, Xiang Li, Kun Wang, Shuo Chen*, Jun Li, Jian Yang*. Distortion and Uncertainty Aware Loss for Panoramic Depth Completion, International Conference on Machine Learning (ICML): 2023.

• Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu, Masashi Sugiyama. Learning Contrastive Embedding in Low-Dimensional Space, Advance in Neural Information Processing Systems (NeurIPS): 2022.

• Hanyu Xuan, Yihong Xu, Shuo Chen, Zhiliang Wu, Jian Yang, Yan Yan, Xavier Alameda-Pineda. Active Contrastive Set Mining for Robust Audio-Visual Instance Discrimination, International Joint Conference on Artificial Intelligence (IJCAI): 2022.

• Yesong Xu, Shuo Chen*, Jun Li, Jianjun Qian. Linearity-Aware Subspace Clustering, AAAI Conference on Artificial Intelligence (AAAI): 2022, oral.

• Jinchao Yang (co-first), Fei Guo (co-first), Shuo Chen, Jun Li, Jian Yang. Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR): 2022.

• Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama. Large-Margin Contrastive Learning with Distance Polarization Regularizer, International Conference on Machine Learning (ICML): 2021.

• Zongyan Han, Zhenyong Fu, Shuo Chen, Jian Yang. Contrastive Embedding for Generalized Zero-shot Learning, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR): 2021.

• Xiang Li, Wenhai Wang, Lijun Wu, Shuo Chen, Xiaolin Hu, Jun Li, Jinhui Tang, Jian Yang. Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection, Advance in Neural Information Processing Systems (NeurIPS): 2020.

• Xiang Li, Shuo Chen, Jian Yang. Understanding the Disharmony between Weight Normalization Family and Weight Decay, AAAI Conference on Artificial Intelligence (AAAI): 2020. [PDF]

• Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang. Curvilinear Distance Metric Learning, Annual Conference on Neural Information Processing Systems (NeurIPS): 2019. [PDF]

• Xiang Li, Shuo Chen, Xiaolin Hu, Jian Yang. Understanding the Disharmony between Dropout and Batch Normalization by Variance Shift, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR): 2019.

• Shuo Chen, Chen Gong, Jiang Yang, Ying Tai, Le Hui, Jun Li. Data-Adaptive Metric Learning with Scale Alignment, AAAI Conference on Artificial Intelligence (AAAI): 2019. [PDF]

• Shuo Chen, Chen Gong, Jiang Yang, Xiang Li, Yang Wei, Jun Li. Adversarial Metric Learning, International Joint Conference on Artificial Intelligence (IJCAI): 2018.  [PDF]

Journal Papers

• Sheng Wan, Yibing Zhan, Shuo Chen, Shirui Pan, Jian Yang, Dacheng Tao, Chen Gong. Boosting Graph Contrastive Learning via Adaptive Sampling, IEEE Transactions on Neural Network and Learning System (T-NNLS): 2023.

• Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama. Similarity-Agnostic Contrastive Learning with Alternative Self-Supervision, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI): in peer review.

• Hang Shao, Lei Luo, Jianjun Qian, Shuo Chen, Chuanfei Hu, Jian Yang. TranPhys: Spatiotemporal Masked Transformer Steered Remote Photoplethysmography Estimation, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT): 2023.

• Yesong Xu, Shuo Chen*, Chunyan Xu, Jun Li, Zongyan Han, Jian Yang*. Fast Subspace Clustering by Learning Projective Block Diagonal Representation, Pattern Recognition (PR): 2023.

• Shuo Chen, Chen Gong, Xiang Li, Jian Yang, Gang Niu, Masashi Sugiyama. Boundary-Restricted Metric Learning, Machine Learning Journal (MLJ): 2023.

• Zongyan Han, Zhenyong Fu, Shuo Chen, Jian Yang. Semantic Contrastive Embedding for Generalized Zero-Shot Learning, International Journal of Computer Vision (IJCV): 2022.

• Wei Zheng, Shuo Chen*, Zhenyong Fu, Jun Li, Jian Yang. Streaming Feature Selection via Graph Diffusion, Information Sciences (INS): 2022.

• Yesong Xu, Shuo Chen, Jun Li, Lei Luo, Jian Yang. Learnable Low-Rank Latent Dictionary for Subspace Clustering, Pattern Recognition (PR): 2021.

• Wei Zheng, Shuo Chen, Zhenyong Fu, Hui Yan, Fa Zhu, Jian Yang. Feature Selection Boosted by Unselected Features, IEEE Transactions on Neural Network and Learning System (T-NNLS): 2021.

• Yesong Xu, Shuo Chen, Jun Li, Zongyan Han, Jian Yang. Autoencoder-Based Latent Block-Diagonal Representation for Subspace Clustering, IEEE Transactions on Cybernetics (T-CYB): 2021.

• Xiang Li, Shuo Chen, Jian Yang. Generalization Bound Regularizer: A Unified Perspective for Understanding Weight Decay, Chinese Journal of Computers, 2021.

• Shuo Chen, Jian Yang, Yang Wei, Lei Luo, Gui-Fu Lu, Chen Gong. Delta-norm based Robust Regression with Applications to Image Analysis, IEEE Transactions on Cybernetics (T-CYB): 2019. [PDF] 

• Yang Wei, Chen Gong, Shuo Chen, Jian Yang, Tongliang Liu, Dacheng Tao. Harnessing Side Information for Classification under Label Noise, IEEE Transactions on Neural Network and Learning System (T-NNLS): 2019. [PDF]

• Shuo Chen, Jian Yang, Lei Luo, Yang Wei, Kai-Hua Zhang, Ying Tai. Low-Rank Latent Pattern Approximation with Applications to Robust Image Classification, IEEE Transactions on Image Processing (T-IP): 2017.  [PDF]

Professional  Activities

• Area Chair (AC): 

Neural Information Processing Systems (NeurIPS), 2022--2023

International Conference on Machine Learning (ICML), 2023--2024

International Conference on Learning Representations (ICLR), 2024

European Conference on Computer Vision (ECCV), 2024

• Conference Reviewer:

AAAI Conference on Artificial Intelligence (AAAI)

International Joint Conferences on Artificial Intelligence (IJCAI)

International Conference on Machine Learning (ICML)

Neural Information Processing Systems (NeurIPS)

International Conference on Learning Representations (ICLR)

IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR)

International Conference on Computer Vision (ICCV)

• Journal Reviewer: 

Journal of Machine Learning Research (JMLR)

IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)

IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)

IEEE Transactions on Image Processing (IEEE TIP)

IEEE Transactions on Cybernetics (IEEE TCYB)

Machine Learning Journal (MLJ)

International Journal on Computer Vision (IJCV)

• Workshop Organizer / Program Chair: 

International Workshop on Weakly Supervised Learning, 2023

Contact

Email: shuo.chen.ya [AT] foxmail.com; shuo.chen.ya [AT] riken.jp.

Address: 15th floor, Nihonbashi 1-chome Mitsui Building, Chuo-ku 1-4-1, Tokyo, Japan.