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

Jianglin

Biography

I am a second-year Ph.D. student in the SMILE Lab of the Department of ECE, Northeastern University (NEU), under the supervision of Prof. Yun Raymond Fu. My current research interests primarily focus on large language models, vision-language models, and graph neural networks.

Selected Publications

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.

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.

Experiences

Northeastern University

Research Assitant, 01.2023--Now

Supervisor: Yun Raymond Fu

Adobe Research

Research Intern, 09.2024--11.2024

Mentors: Simon Jenni, Kushal Kafle, Jing Shi, Handong Zhao

Tencent Music Entertainment

Research Intern, 11.2020--04.2021

Mentors: Kwok-Wai Hung, Simon Lui

Invited Talks

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

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]

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