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

Conference

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.

Label Self-Adaption Hashing for Image Retrieval. [PDF] [Code]

Jianglin Lu, Zhihui Lai, Jingxu Lin, Qinghong Lin, Jie Zhou.

International Conference on Pattern Recognition (ICPR), 2020.

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.

Journal

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), 2024.

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.

Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization. [PDF]

Jianglin Lu, Hailing Wang, Jie Zhou, Mengfan Yan, Jiajun Wen.

Information Sciences (INS), 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.

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]