Tianjin Huang

Hi, I'm an assistant professor in the Department of Computer Science at University of Exeter, and a long-term visiting researcher at Eindhoven University of Technology (TU/e). My research focuses on efficient and reliable machine learning systems, specifically in the following topics:

• Model Efficiency
• Model Editing
• Trustworthy AI
• AI for Science

I am open to collaborating with remote students and visitors (with or without research experience) who are interested in model compression, model editing, robustness, efficient training/tuning of foundation models and large language models, ai for science, etc. .^_^.

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News

• [July. 2024] One BMVC'24 accepted, Are Sparse Neural Networks Better Hard Sample Learners?

• [June 2024] Thrilled to co-organize NeurIPS 2024, Edge-Device Large Language Model Competition. Join us for the competition!

• [March. 2024] One ICLR'24 workshop accepted, Composing Knowledge and Compression Interventions for Language Models.

• [Oct. 2023] One Information Fusion accepted, Robust Spatiotemporal GCN.

• [Sep. 2023] One Complex Networks'2024 accepted, Heterophily-Based Graph Neural Network for Imbalanced Classification.

• [Sep. 2023] One NeurIPS'23 accepted, Channel-DST.

• [Jun. 2023] One ECML'23 accepted, Enhancing AT via Refining Optimization trajectories.

• [Apr. 2023] One ICML'23 accepted, Larger Kernel Serve better Teachers than Transformers.

• [Jan. 2023] One ICLR'23 accepted, Oral, Sparsity May Cry:SMC.

• [Nov. 2022] One LoG'22 accepted, Best Paper Award, Better GNN by Finding Graph Tickets.

• [Nov. 2022] One AAAI'23 accepted, Lottery Pools.

• [Jun. 2022] One ECML-PKDD'22 accepted, Hop-count based self-supervised anomaly detection.

Selected Publications (full list)

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets

Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu

Learning on Graphs Conference (LoG 2022)  /  Paper  /  Code

Best Paper Award

Are Large Kernels Better Teachers than Transformers for ConvNets?

Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu

ICML 2023  /  Paper  /  Code

RT-GCN: Gaussian-based spatiotemporal graph convolutional network for robust traffic prediction

Yutian Liu, Soora Rasouli, Melvin Wong, Tao Feng, Tianjin Huang*

Information Fusion  /  Paper  /  Code

IF=18.6

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!

Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang

ICLR 2023  /  Paper  /  Code

Spotlight Presentation

Dynamic sparsity is channel-level sparsity learner

Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu

NeurIPS 2023  /  Paper  /  Code

Enhancing Adversarial Training via Reweighting Optimization Trajectory

Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlaod Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy

ECML-PKDD 2023  /  Paper  /  Code

Hop-count based self-supervised anomaly detection on attributed networks

Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy

ECML-PKDD 2022  /  Paper  /  Code

Work Experience

University of Exeter

Assistant Professor, June 2024 -

Department of Computer Science

University of Aberdeen

Lecturer (Assistant Professor), Mar. 2024 - June 2024

The School of Natural and Computing Sciences

Eindhoven University of Technology

Postdoctoral Fellow, Feb. 2023 - Feb. 2024

Advisor: Professor Mykola Pechenizkiy

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