李昊 - 复旦大学 - 人工智能创新与产业研究院

个人简介

教育经历 2012年获得中国科学院博士学位工作经历 2012-2013年，北京三星通讯研究院-算法工程师 2013-2022年，阿里巴巴达摩院-技术总监 2023年至今，复旦大学人工智能创新与产业研究院-研究员

研究领域

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

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Lei Chen,Xiaohui Zhong,Feng Zhang,Yuan Cheng,Yinghui Xu,Yuan Qi,Hao Li.(2023). FuXi: A cascade machine learning forecasting system for 15-day global weather forecast. arXiv preprintarXiv:2306.12873. Yi Xu,LeiShang,Jinxing Ye,Qi Qian,Yu-Feng Li,Baigui Sun,HaoLi,Rong Jin.Dash: Semi-supervised learning with dynamic thresholding[C]//International Conference on Machine Learning. PMLR, 2021: 11525-11536. Hansheng Chen, Pichao Wang, Fan Wang, Wei Tian, Lu Xiong, Hao Li(2022). 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). Shuting He, Hao Luo, Weihua Chen, Miao Zhang, Yuqi Zhang, Fan Wang, Hao Li, Wei JiangHe.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. Qi Qian, Lei Chen, Hao Li, Rong JinQian. Dr loss: Improving object detection by distributional ranking[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020: 12164-12172. Hao Li, Jing Lu, Guohua Shi, and Yudong Zhang, "Tracking features in retinal images of adaptive optics confocal scanning laser ophthalmoscope using KLT-SIFT algorithm," Biomed. Opt. Express 1, 31-40 (2010). Li Hao, Lu J, Shi G, et al. 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. He, S., Luo, H., Wang, P., Wang, F., Li, H., & Jiang, W. (2021). Transreid: Transformer-based object re-identification. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 15013-15022). Qian Q, Shang L, Sun B, et al. Softtriple loss: Deep metric learning without triplet sampling[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision. 2019: 6450-64 Leng C, Dou Z, Li H, et al. Extremely low bit neural network: Squeeze the last bit out with admm[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2018, 32(1). Zhou Q, Yu C, Wang Z, et al. Instant-teaching: An end-to-end semi-supervised object detection framework[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021: 4081-4090. Li, Y., Shi, T., Zhang, Y., Chen, W., Wang, Z., & Li, H. (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. Lei Chen, Xiaohui Zhong, Jie Wu, Deliang Chen, Shangping Xie, Qingchen Chao, Chensen Lin, Zixin Hu, Bo Lu, Hao Li, Yuan Qi. FuXi-S2S: An accurate machine learning model for global subseasonal forecasts.arXiv preprint arXiv:2312.09926, 2023. Xiaohui Zhong, Lei Chen, Jun Liu, Chensen Lin, Yuan Qi, Hao Li. FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model[J]. arXiv preprint arXiv:2310.19822, 2023. Yuan Hu, Lei Chen, Zhi Bin Wang, Hao Li. SwinVRNN: A Data‐Driven Ensemble Forecasting Model via Learned Distribution Perturbation[J]. Journal of Advances in Modeling Earth Systems, 2023, 15(2): e2022MS003211.