Jianglin (Johnny) Lu 盧江林

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SMILE Lab,
Department of ECE,
College of Engineering,
Northeastern University,
360 Huntington Avenue, Boston, MA 02115, USA

Email: jianglinlu at outlook dot com

Biography

I am a Ph.D. candidate in the SMILE Lab of the Department of ECE, Northeastern University (NEU), under the supervision of Prof. Yun Raymond Fu. I have interned at Adobe Research and Tencent Music Entertainment. My current research interests primarily focus on large language models, vision-language models, graph neural networks, and agents.

Selected Publications

Scale-Free Graph-Language Models. [PDF][Code]

Jianglin Lu, Yixuan Liu, Yitian Zhang, Yun Fu.

International Conference on Learning Representations (ICLR), 2025.

Latent Graph Inference with Limited Supervision. [PDF][Project Page][Code]

Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu.

Neural Information Processing Systems (NeurIPS), 2023.

Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning. [PDF] [Code]

Jianglin Lu, Jie Zhou, Yudong Chen, Witold Pedrycz, Kwok-Wai Hung.

IEEE Transactions on Cybernetics (TCYB), 2023.

Generalized Embedding Regression: A Framework for Supervised Feature Extraction. [PDF] [Code]

Jianglin Lu, Zhihui Lai, Hailing Wang, Yudong Chen, Jie Zhou, Linlin Shen.

IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

Low-Rank Adaptive Graph Embedding for Unsupervised Feature Extraction. [PDF] [Code]

Jianglin Lu, Hailing Wang, Jie Zhou, Yudong Chen, Zhihui Lai, Qinghua Hu.

Pattern Recognition (PR), 2021.

Target Redirected Regression with Dynamic Neighborhood Structure. [PDF] [Code]

Jianglin Lu, Jingxu Lin, Zhihui Lai, Hailing Wang, Jie Zhou.

Information Sciences (INS), 2021.

Uncertainty-Guided Pixel Contrastive Learning for Semi-Supervised Medical Image Segmentation. [PDF][Code]

Tao Wang, Jianglin Lu, Zhihui Lai, Heng Kong, Jiajun Wen.

International Joint Conference on Artificial Intelligence (IJCAI), 2022.

Local Graph Convolutional Networks for Cross-Modal Hashing. [PDF][Code ]

Yudong Chen, Sen Wang, Jianglin Lu, Zhi Chen, Zheng Zhang, Zi Huang.

ACM International Conference on Multimedia (ACM MM), 2021.

Invited Talks

Latent Graph Inference from Shallow Methods to GNNs [Slides], invited by Prof. Sarah Ostadabbas @ ACLab, Feb. 2024

Professional Services

Conference Reviewer: ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, KDD, MM, AISTATS,

Journal Reviewer: TPAMI, TIP, TKDE, TNNLS, TKDD, PR.

Personal Links

Awesome Papers in Machine Learning, Computer Vision, Pattern Recognition, and Data Mining [Link]

Introduction to Vision Language Models [Notes]

Introduction to Domain Adaptation [Notes]

Introduction to Graph Neural Networks [Notes]