北京雁栖湖应用数学研究院 北京雁栖湖应用数学研究院

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关于我们
院长致辞
理事会
协作机构
参观来访
人员
管理层
科研人员
博士后
来访学者
行政团队
学术支持
学术研究
研究团队
公开课
讨论班
期刊
招生招聘
教研人员
博士后
学生
会议
学术会议
工作坊
论坛
学院生活
住宿
交通
配套设施
周边旅游
意见建议
新闻
新闻动态
通知公告
资料下载
清华大学 "求真书院"
清华大学丘成桐数学科学中心
清华三亚国际数学论坛
上海数学与交叉学科研究院
河套数学与交叉学科研究院
BIMSA > BIMSA 计算数学讨论班 BIMSA 计算数学讨论班 Learning the Antarctic Sea-Ice Cycle: Season-Aware Transformers for Year-Ahead Forecasting
Learning the Antarctic Sea-Ice Cycle: Season-Aware Transformers for Year-Ahead Forecasting
组织者
Theory and Computation of PDE Team
演讲者
邓权灵
时间
2026年10月15日 15:00 至 16:00
地点
Online
线上
Zoom 518 868 7656 (BIMSA)
摘要
Antarctic sea-ice concentration forecasting must resolve complex spatial structure while tracking dependencies that span months and a strong but changing annual cycle. This talk presents a hybrid convolutional Transformer for monthly forecasts up to one year ahead. A CNN or UNet encoder compresses each field before factorized temporal and spatial self-attention, preserving local structure while making global mixing practical. Two additions expose the seasonal cycle directly to the model: Fourier-based month-aware positional encoding and a learnable cosine bias on temporal attention. Using NSIDC Sea Ice Index data from 1978-2024, the proposed variants outperform statistical baselines and SEAS5 at the reported horizons while remaining competitive with a multi-source UNet despite using sea-ice concentration alone. Ablations show larger gains at the 12-month horizon, and attention maps reveal clearer periodic structure. The talk concludes with limitations and directions for physics-guided forecasting.
演讲者介绍
Dr. Quanling Deng is an Assistant Professor at the Yau Mathematical Sciences Center (YMSC), Tsinghua University and an Honorary Lecturer at the Australian National University. Before joining YMSC, he held positions at Curtin University (Research Associate, 2016–2020), the University of Wisconsin–Madison (Van Vleck Visiting Assistant Professor, 2020–2022), and the Australian National University (Lecturer, 2022–2025). He got his PhD in Mathematics at the University of Wyoming in 2016. He has a broad interest in Computational and Applied Mathematics and AI. Inspired by Hilbert’s Sixth Problem, he pioneered a particle–continuum multiscale modeling paradigm for sea ice floes and developed the LEMDA framework that unifies multiscale observations. He also introduced SoftFEM, SoftIGA, and high-order boundary penalty techniques, resolving long-standing challenges in finite elements and isogeometric analysis. His research has been published in leading venues, including MCOM, CMAME, JAMES, ICLR, and the SIAM journals, with over 50 peer-reviewed publications to date.
北京雁栖湖应用数学研究院
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No. 544, Hefangkou Village Huaibei Town, Huairou District Beijing 101408

北京市怀柔区 河防口村544号
北京雁栖湖应用数学研究院 101408

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