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李昊
复旦大学人工智能创新与产业研究院研究员、博导
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详细介绍
李昊
复旦大学人工智能创新与产业研究院研究员、博导
个人履历：
李昊：复旦大学人工智能创新与产业研究院研究员、博士生导师，上海科学智能研究院副院长，中国气象局重点创新团队首席科学家。曾任北京三星通讯研究院算法工程师、阿里巴巴达摩院技术总监，是业内首个泛自然资源AI引擎-AI Earth、最大的以图搜图产品-拍立淘创始人。李昊的研究方向为：AI+气象：气象大模型，多模态大模型，图像视频生成，深度学习模型压缩与加速等，实现人工智能在电商、遥感、气象、安防、IOT等场景的大规模落地。。参与研发国内第一代基于自适应光学的高分辨率活体视网膜显微镜。申请发明专利100余项，授权30余项；已发表CVPR、ICCV、NeurIPS、ICML、AAAI等人工智能顶会60余篇。带领团队获得国际知名竞赛排行榜第一名15项。
论文代表：
A machine learning model that outperforms conventional global subseasonal forecast models [J]. Nat Commun, 2024, 15(1): 6425.
SwinVRNN: A Data‐Driven Ensemble Forecasting Model via Learned Distribution Perturbation[J]. Journal of Advances in Modeling Earth Systems, 2023, 15(2): e2022MS003211.
FuXi: A cascade machine learning forecasting system for 15-day global weather forecast. arXiv preprintarXiv:2306.12873.
Dash: Semi-supervised learning with dynamic thresholding[C]//International Conference on Machine Learning. PMLR, 2021: 11525-11536.
Epro-pnp: Generalized end-to-end probabilistic perspective-n-points for monocular object pose estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2781-2790).
.Multi-domain learning and identity mining for vehicle re-identification[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2020: 582-583.
Dr loss: Improving object detection by distributional ranking[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020: 12164-12172.
Tracking features in retinal images of adaptive optics confocal scanning laser ophthalmoscope using KLT-SIFT algorithm," Biomed. Opt. Express 1, 31-40 (2010).
Measurement of oxygen saturation in small retinal vessels with adaptive optics confocal scanning laser ophthalmoscope[J]. Journal of biomedical optics, 2011, 16(11): 110504-110504-3.
Transreid: Transformer-based object re-identification. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 15013-15022).
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling; proceedings of the arXiv, F, 2019 [C].
Extremely low bit neural network: Squeeze the last bit out with admm[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2018, 32(1).
Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework [J]. 2021.
Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation.ISPRS Journal of Photogrammetry and Remote Sensing, 175, 20-33.
FuXi-S2S: An accurate machine learning model for global subseasonal forecasts.arXiv preprint arXiv:2312.09926, 2023.
FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model[J]. arXiv preprint arXiv:2310.19822, 2023.
讲座主题：
《人工智能在气象预测中的应用-伏羲气象大模型》
《用人工智能赋能地球科学》
邀请老师演讲、授课请致电：19821197419 阎老师[微信同号]
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