I am currently a PhD student in Computer Science at the Cambridge Computer Laboratory, supervised by Prof. Mateja Jamnik. My research is generously supported by the Google PhD Fellowship. My research interest primarily lies at the intersection of structured tabular data and explainable artificial intelligence (XAI). In particular, my work focuses on:
- tabular foundation models
- tabular generative modelling
- trustworthy AI solutions for scientific applications
Before joining Cambridge, I was fortunate to work as a research intern on embodied AI at MT Lab and Cola Laboratory under the supervision of Prof. Si Liu.
If you would like to discuss anything related to XAI, structured tabular data, or any other interesting topics, please feel free to reach out via: silencejiang12138 [at] gmail [dot] com.
Education
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University of CambridgePhD in Computer Science2023 - present -
University of CambridgeMPhil in Advanced Computer Science2022 - 2023
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Beihang UniversityBEng in Computer Science and Technology2018 - 2022
Honors & Awards
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Google PhD Fellowship2025
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ICLR 2025 Early Career Scholar Award for SynthData2025
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NeurIPS 2024 Scholar Award2024
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St Edmund's College Tutorial Award2024
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St Edmund's College Prize for Academic Excellence2023
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National Scholarship2022
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Changzhao Qian & Xingyuan Shen Scholarship2021
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Academic Excellence Scholarship2018-2021
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Dean's Honours List2018-2021
News
Selected Publications (view all )
TabStruct: Measuring Structural Fidelity of Tabular Data
Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik
The Fourteenth International Conference on Learning Representations 2026
Oral (Top 1.18%)
TabStruct: Measuring Structural Fidelity of Tabular Data
Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik
The Fourteenth International Conference on Learning Representations 2026
Oral (Top 1.18%)
TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models
Andrei Margeloiu*, Xiangjian Jiang*, Nikola Simidjievski, Mateja Jamnik (* equal contribution)
The Thirty-Eighth Annual Conference on Neural Information Processing Systems 2024
TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models
Andrei Margeloiu*, Xiangjian Jiang*, Nikola Simidjievski, Mateja Jamnik (* equal contribution)
The Thirty-Eighth Annual Conference on Neural Information Processing Systems 2024
DropKey for Vision Transformer
Bonan Li, Yinhan Hu, Xuecheng Nie, Congying Han, Xiangjian Jiang, Tiande Guo, Luoqi Liu
Computer Vision and Pattern Recognition Conference 2023
DropKey for Vision Transformer
Bonan Li, Yinhan Hu, Xuecheng Nie, Congying Han, Xiangjian Jiang, Tiande Guo, Luoqi Liu
Computer Vision and Pattern Recognition Conference 2023
Multi-view Human Body Mesh Translator
Xiangjian Jiang*, Xuecheng Nie*, Zitian Wang, Luoqi Liu, Si Liu (* equal contribution)
arXiv preprint 2022
Work done while interning at MT Lab
Multi-view Human Body Mesh Translator
Xiangjian Jiang*, Xuecheng Nie*, Zitian Wang, Luoqi Liu, Si Liu (* equal contribution)
arXiv preprint 2022
Work done while interning at MT Lab
Towards Real-world X-ray Security Inspection: A High-quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection
Renshuai Tao, Yanlu Wei, Xiangjian Jiang, Hainan Li, Haotong Qin, Jiakai Wang, Yuqing Ma, Libo Zhang, Xianglong Liu
International Conference on Computer Vision 2021
Towards Real-world X-ray Security Inspection: A High-quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection
Renshuai Tao, Yanlu Wei, Xiangjian Jiang, Hainan Li, Haotong Qin, Jiakai Wang, Yuqing Ma, Libo Zhang, Xianglong Liu
International Conference on Computer Vision 2021