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Siyuan Yan
I am a first-year Ph.D. student in Monash Medical AI Group (MMAI) at Monash University, working with A/Prof. Zongyuan Ge.
I am primarily interested in trustworthy AI and its application in medical fields, i.e. out-of-domain generalization, debiasing, and explainability. Before coming to Monash University, I received my master's degree at the Australian National University under the supervision of Prof. Nick Barnes and Dr. Jing Zhang.
Email  / 
Linkedin  / 
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Github
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News
[Aug 2024] Batch updates: PLDG was accepted to TMI 2024; our large-scale ophthalmic surgical workflow understanding dataset OphNet was accepted to ECCV 2024.
[Sep 2023] One paper is accepted to NeurIPS 2023 D&B track, where we release the largest expert-level video datasets for Nursing Procedure Activity Understanding.
[Jun 2023] One paper is accepted to MICCAI 2023, about dermoscopic artifacts-inspired domain generalization in skin lesion recognition.
[Feb 2023] One paper is accepted to CVPR 2023, about discovering, explaining, and mitigating biases in dermatology AI.
[Dec 2021] Our work on physical prior-based stochastic smoke segmentation is accepted to AAAI 2022.
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Research
Most of my recent research is about understanding deep learning generalization behavior under distribution shift. I am also particularly interested in building medical foundation models and developing generative AI assistants.
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Ming Hu*, Lin Wang*, Siyuan Yan*(equal contribution), Don Ma, Qingli Ren, Peng Xia, Wei Feng, Peibo Duan, Lie Ju, Zongyuan Ge
NeurIPS 2023 Datasets and Benchmarks Track
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Siyuan Yan, Chi Liu, Zhen Yu, Lie Ju, Dwarikanath Mahapatra, Brigid Betz-Stablein, Victoria Mar, Monika Janda, Peter Soyer, Zongyuan Ge
IEEE Transactions on Medical Imaging
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Siyuan Yan,Chi Liu, Zhen Yu, Lie Ju, Dwarikanath Mahapatrainst, Victoria Mar,
Monika Janda, Peter Soyer, Zongyuan Ge
MICCAI 2023
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Siyuan Yan, Jing Zhang, Nick Barnes
AAAI 2022 (15% acceptance rate, Student Travel Award)
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Professional activities
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Conference Reviewer for CVPR, ICCV, ECCV, Neurips, AAAI, ACM MM and MICCAI.
Journal Reviewer for TMI and TIP.
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