个人简历

胡迪，分别于2014年和2019年获得西北工业大学学士和博士学位。曾任百度研究院人工智能研究员，于2020年9月加入中国人民大学，任助理教授。其主要研究方向为机器多模态感知与学习，以主要作者身份在领域顶级国际会议及期刊上发表论文10余篇，如 CVPR、ICCV、ECCV、AAAI等。攻博期间曾入选 CVPR Doctoral Consortium（大陆共4人）；荣获2019 ACM XI’AN 优博奖，2020中国人工智能学会优博奖；入选百度全球顶尖人工智能人才计划。受邀为CVPR、ICCV、ECCV、NeurIPS等多个国际高水平会议及期刊审稿。部分研究成果正同产业应用相结合以发挥其社会价值，如利用机器辅助手段提升视障人士的感知能力等。\r
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教育经历\r
2010-2019年 西北工业大学 本科-博士\r
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工作经历\r
2020年至今，中国人民大学高瓴人工智能学院，准聘助理教授\r
2019-2020年，百度研究院，人工智能研究员\r
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荣誉获奖\r
1、2020.9 荣获中国人工智能学会优秀博士论文奖\r
2、2019.8 入选百度『AIDU』全球顶尖人工智能人才计划\r
3、2019.8 荣获ACM XI’AN优秀博士论文奖（共2人）\r
4、2019.5 入选CVPR Doctoral Consortium博士生论坛（大陆共4人）\r
5、2018.7 荣获国家留学基金委赴卡内基梅隆大学联合培养学金

研究领域

""机器多模态感知与学习：以大脑的多通道知觉为背景，挖掘并探究多模态信息（如图像、声音、触觉等）在机器感知、推理与理解等""""

近期论文

1、Di Hu, Xuhong Li, LichaoMou, Pu Jin, Dong Chen, Liping Jing, Xiaoxiang Zhu, and Dejing Dou, Cross-Task Transfer for Multimodal Aerial Scene Recognition, In Proceedings of the European Conference on Computer Vision (ECCV), 2020.\r
2、Rui Qian, Di Hu, Heinrich Dinkel, Mengyue Wu, Ning Xu, and Weiyao Lin, Learning to Visually Localize Multiple Sound Sources via A Two-stage Manner, In Proceedings of the European Conference on Computer Vision (ECCV), 2020.\r
3、Di Hu, FeipingNie, and Xuelong Li, Deep Linear Discriminant Analysis Hashing, Sci Sin Inform, 2019. (CCF A)\r
4、Di Hu, FeipingNie, and Xuelong Li, Deep Multimodal Clustering for Unsupervised Audiovisual Learning, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (CCF A)\r
5、Di Hu, Dong Wang, FeipingNie, Qi Wang, and Xuelong Li, Listen to the Image, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (CCF A)\r
6、Di Hu, Chengze Wang, FeipingNie, and Xuelong Li, Dense Multimodal Fusion for Hierarchically Joint Representation, In Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019.\r
7、Di Hu, FeipingNie, and Xuelong Li, Discrete Spectral Hashing for Efficient Similarity Retrieval, IEEE Trans. Image Processing (TIP), 2018. (CCF A)\r
8、Di Hu, FeipingNie, and Xuelong Li, Deep Binary Reconstruction for Cross-modal Hashing, IEEE Trans. Multimedia (TMM), 2018.\r
9、Xuelong Li, Di Hu, and Xiaoqiang Lu, Image2song: Song Retrieval via Bridging Image Content and Lyric Words, In Proceedings of the IEEE Conference on Computer Vision (ICCV), 2017. (CCF A)\r
11、Xuelong Li, Di Hu, and FeipingNie, Deep Binary Reconstruction for Cross-modal Hashing, In Proceedings of the ACM Conference on Multimedia (ACMMM), 2017. (CCF A)\r
12、Xuelong Li, Di Hu, and FeipingNie, LargeGraphHashingwithSpectralRotation, In Proceedings of the AAAIConferenceonArtificialIntelligence (AAAI), 2017. (CCF A)\r
13、Di Hu, Xiaoqiang Lu, and Xuelong Li, Multimodal Learning via Exploring Deep Semantic Similarity, In Proceedings of the ACM Conference on Multimedia (ACMMM), 2016. (CCF A)\r
14、Di Hu, Xuelong Li, and Xiaoqiang Lu, Temporal Multimodal Learning in Audiovisual Speech Recognition, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (CCF A)\r
15、Di Hu, Zheng Wang, HaoyiXiong, Dong Wang, FeipingNie, and Dejing Dou, Heterogeneous Scene Analysis via Self-supervised Audiovisual Learning, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.\r
16、Di Hu, LichaoMou, Qingzhong Wang, Junyu Gao, Yuansheng Hua, Dejing Dou, and Xiaoxiang Zhu, Does Ambient Sound Help? - Audiovisual Crowd Counting, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.\r
17、Yapeng Tian, Di Hu, Chenliang Xu, Co-Learn Sounding Object Visual Grounding and Visually Indicated Sound Separation in A Cycle, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.\r
18、Rui Qian, Di Hu, Heinrich Dinkel, Mengyue Wu, Ning Xu, Weiyao Lin, A Two-Stage Framework for Multiple Sound-Source Localization, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.
1、期刊审稿人: TIP, TKDE, TMM, Neurocomputing2、会议程序委员: NeurIPS 2020, CVPR 2018 2020, ICCV 2019, ECCV2020, AAAI 2018 2020, ACCV 2018 20203、联合组织者: ICDM 2019 Tutorial on Automated Deep Learning: Theory, Algorithms, Platforms, and Applications