Shirui Pan
H指数:69
被引数:2.4万
个人简介
A Professor and an ARC Future Fellow with the School of Information and Communication Technology, Griffith University, Australia, and an Adjunct Professor at Monash University. He is a Co-Director of TrustAGI Lab. Before joining Griffith in 2022, he was Senior Lecturer (Associate Professor) with the Faculty of Information Technology, Monash University. He received his Ph.D degree in computer science from University of Technology Sydney (UTS), Australia. He is a Senior Member of IEEE and ACM, and a Fellow of Queensland Academy of Arts and Sciences (FQA). His research focuses on artificial intelligence and machine learning. He is recognized as one of the 2024 AI’s 10 to Watch and the recipient of the 2024 IEEE ICDM Tao Li Award. He has also been named among the AI 2000 AAAI/IJCAI Most Influential Scholars in Australia (2023, 2022).
教育背景
暂无内容
工作经历
2022.01 – 至今
Griffith University
Professor
2022.01 – 2025.12
Griffith University
ARC Future Fellow
2022.12
Monash University
Senior Lecturer (Associate Professor)
荣誉奖项
- 2026 Australian’s Leading Researcher in AI(2026)|The Australian’s 2026 Research magazine
- 2024 AI'10 to Watch(2024)
- 2024 IEEE ICDM Tao Li Award(2024)|IEEE ICDM
- 2021 ARC Future Fellow(2021)|Australian Research Council (ARC)
- Fellow of Queensland Academy of Arts and Sciences (QAAS)(2023)|Queensland Academy of Arts and Sciences
- World’s Top 2% Scientists(2023)|Stanford University
- Amazon Research Award(2022)
- IEEE ICDM Best Student Paper Award(2020)|IEEE ICDM
- IEEE CIS TNNLS Outstanding Paper Award(2024)|IEEE CIS TNNLS
- Top 10 Globally in AI 2000 Most Influential Scholars by AMiner in Artificial Intelligence (IJCAI)(2023)|AMiner
- FIT Dean’s Award for Excellence in Research by an Early Career Researcher(2021)|FIT
- Most Influential Papers in KDD (x1), IJCAI (x5), AAAI (x1), and CIKM (x1)(2022)|PaperDigest.org
- Vannevar Bush Best Paper Honorable Mention for JCDL-2020(2020)
- Future Fellowship(2022)|Australian Research Council (ARC)
- Senior Member of IEEE|IEEE
SRLST:一种用于空间转录组学分析的统一多模态表示学习框架
Bioinformatics
IF5.4
W-扩散:基于浅扩散机制的交通预测概率生成框架
面向结合多个知识图谱以支持大型语言模型推理
从少样本到零样本:迈向通用的图异常检测
时空感知偏好优化用于个性化放射学报告生成
LiSA: 一种带样本聚类的线性图转换器框架
对比知识嵌入与判别性自加权采样
Neural Networks
IF6.3
IEGSCL:交互增强图神经网络序列对比学习用于微观扩散预测
CAFE:基于跨视图自适应融合和聚类中心增强的鲁棒多视图聚类
基于静态属性和动态兴趣的多视角对比学习用于序列推荐
Applied Intelligence
IF3.5
用于药物发现和开发的大型语言模型
Patterns
IF7.4
DA-MoE:通过专家混合模型解决图级分析中的深度敏感性问题
Neural Networks
IF6.3
DACAD:多变量时间序列异常检测的领域自适应对比学习
通过社交网络平衡用户偏好:一种条件引导的社交推荐模型,用于缓解热门度偏差
NEURAL NETWORKS
IF6.3

