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Kai Zhao

University of California, Los Angeles

赵凯博士 目前是 加州大学洛杉矶分校 的博士后研究员， 与 Kyung Hyun Sung 教授共同从事医学图像处理相关研究。 他于 2020 年获得 南开大学 计算机科学与技术博士学位， 博士导师是 程明明 教授。 同年，他入选腾讯校招技术大咖（腾讯应届生最高技术职级），并加入 腾讯优图实验室 担任高级研究员。 赵凯本科和硕士均毕业于上海大学。 硕士导师是 沈为 教授 (现上海交通大学教授)。

赵凯博士的研究领域主要包括 计算机视觉，几何， 和 机器学习。 他在计算机视觉和机器学习相关的顶级期刊和会议上发表论文20余篇， 包括 IEEE TPAMI, CVPR, NeurIPS, ICCV, ECCV 等顶级期刊和会议， 多篇论文入选 ESI 高被引，谷歌学术 总引用 5,000 余次。 他关于掌纹识别的研究被 《麻省理工科技评论》 报道， 并应用于 微信刷掌支付 中。 他是很多开源库（例如 PyTorch 和 mmdetection）的活跃贡献者。

Professional Experience:

  • Mar 2022~: 博士后，加州大学洛杉矶分校，洛杉矶。
  • Oct 2020~Feb 2022: 高级研究员，腾讯优图实验室，上海。
  • Sep 2018~Jan 2019: 研究实习生，松下研发中心，新加坡。
  • Sep 2017~Jun 2020: 博士生，南开大学，天津。
  • Jul 2016~Nov 2016: 研究实习生，腾讯优图实验室，上海。
  • Sep 2014~Jun 2017: 硕士生，上海大学，上海。
  • Sep 2010~Jun 2014: 本科生，上海大学，上海。

招生与指导

如果你对我的研究方向感兴趣，欢迎与我联系。 请先看我的研究兴趣 或者我的论文列表， 然后给我发邮件，简要介绍一下你的背景和兴趣。

对于本科生，请合理安排学业和研究时间，如果能保证每周有超过 20 小时的科研时间， 然后再与我联系。如果无法保证这个时间，建议先专心学业。

对于即将入学的研究生，如果你有较强的编程能力、数学基础、英语读写能力， 请发一页纸的简历和一封自荐信给我。

联系方式

  • 10945 Le Conte Avenue, Los Angeles, CA 90024, USA.
  • kzkaizhao (发邮件时请说明来意并尽量简洁直接)

Publications:

  • Kaifeng Pang and Kai Zhao* and Alex Ling Yu Hung and Haoxin Zheng and Ran Yan and Kyunghyun Sung, "NExpR: Neural Explicit Representation for fast arbitrary-scale medical image super-resolution", Computers in Biology and Medicine, 2025. (IF=7, 中科院 2 区 ) (* 通讯作者) DOI: 10.1016/j.compbiomed.2024.109354  [PDF]  [Google Scholar] 
  • Kai Zhao and Alex Ling Yu Hung and Kaifeng Pang and Haoxin Zheng and Kyunghyun Sung, "MRI Super-Resolution with Partial Diffusion Models", IEEE Transactions on Medical Imaging, 2024. (IF=8.9, 中科院 1 区 Top) DOI: 10.1109/TMI.2024.3483109  [PDF]  [Google Scholar] 
  • Kai Zhao and Zuojie He and Alex Hung and Dan Zeng, "Dominant Shuffle: A Simple Yet Powerful Data Augmentation for Time-series Prediction", arXiv:2405.16456, 2024. [Google Scholar] 
  • Kai Zhao and Kaifeng Pang and Alex LingYu Hung and Haoxin Zheng and Ran Yan and Kyunghyun Sung, "A Deep Learning-Based Framework for Highly Accelerated Prostate MR Dispersion Imaging", Cancers, 2024. (IF=4.5, 中科院 3 区 ) DOI: 10.3390/cancers16172983  [PDF]  [Google Scholar] 
  • Alex Ling Yu Hung and Haoxin Zheng and Kai Zhao and Kaifeng Pang and Demetri Terzopoulos and Kyunghyun Sung, "Cross-Slice Attention and Evidential Critical Loss for Uncertainty-Aware Prostate Cancer Detection", International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024. [Google Scholar] 
  • Kai Zhao and Tao Wang and Ruixin Zhang and Wei Shen, "Adaptive feature alignment for adversarial training", Pattern Recognition Letters, 2024. (IF=3.9, 中科院 3 区 ) DOI: j.patrec.2024.10.004  [PDF]  [Google Scholar] 
  • Alex Ling Yu Hung and Kai Zhao and Haoxin Zheng and Ran Yan and Steven S Raman and Demetri Terzopoulos and Kyunghyun Sung, "Med-cDiff: Conditional medical image generation with diffusion models", Bioengineering, 2023. [Google Scholar] 
  • Yating Xu and Kai Zhao and Liangang Zhang and Mengyao Zhu and Dan Zeng, "Hyperspectral anomaly detection with vision transformer and adversarial refinement", International Journal of Remote Sensing, 2023. [Google Scholar] 
  • Kai Zhao and Lei Shen and Yingyi Zhang and Chuhan Zhou and Tao Wang and Ruixin Zhang and Shouhong Ding and Wei Jia and Wei Shen, "B'ezierpalm: A free lunch for palmprint recognition", European Conference on Computer Vision, 2022. DOI: 10.1007/978-3-031-19778-9_2  [PDF]  [Google Scholar] 
  • Xuehui Wang and Kai Zhao and Ruixin Zhang and Shouhong Ding and Yan Wang and Wei Shen, "Contrastmask: Contrastive learning to segment every thing", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022. [Google Scholar] 
  • Lei Shen and Yingyi Zhang and Kai Zhao* and Ruixin Zhang and Wei Shen, "Distribution alignment for cross-device palmprint recognition", Pattern Recognition, 2022. (IF=7.5, 中科院 1 区 Top) (* 通讯作者) DOI: 10.1016/j.patcog.2022.108942  [PDF]  [Google Scholar] 
  • Jia Li and Junjie Zhang and Fansheng Chen and Kai Zhao and Dan Zeng, "Adaptive material matching for hyperspectral imagery destriping", IEEE Transactions on Geoscience and Remote Sensing, 2022. [Google Scholar] 
  • Kai Zhao and Xuehui Wang and Xingyu Chen and Ruixin Zhang and Wei Shen, "Rethinking mask heads for partially supervised instance segmentation", Neurocomputing, 2022. (IF=5.5, 中科院 2 区 ) DOI: 10.1016/j.neucom.2022.10.003  [PDF]  [Google Scholar] 
  • Kai Zhao and Qi Han and Chang-Bin Zhang and Jun Xu and Ming-Ming Cheng, "Deep hough transform for semantic line detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021. (IF=20.8, 中科院 1 区 Top) DOI: 10.1109/TPAMI.2021.3077129  [PDF]  [Google Scholar] 
  • Shang-Hua Gao and Ming-Ming Cheng and Kai Zhao and Xin-Yu Zhang and Ming-Hsuan Yang and Philip Torr, "Res2net: A new multi-scale backbone architecture", IEEE transactions on pattern analysis and machine intelligence, 2019. (IF=20.8, 中科院 1 区 Top) [Google Scholar] 
  • Kai Zhao and Shanghua Gao and Wenguan Wang and Ming-Ming Cheng, "Optimizing the F-measure for threshold-free salient object detection", Proceedings of the IEEE/CVF international conference on computer vision, 2019. [PDF]  [Google Scholar] 
  • Kai Zhao and Jingyi Xu and Ming-Ming Cheng, "Regularface: Deep face recognition via exclusive regularization", Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2019. [PDF]  [Google Scholar] 
  • Wei Shen and Yilu Guo and Yan Wang and Kai Zhao and Bo Wang and Alan Yuille, "Deep differentiable random forests for age estimation", IEEE transactions on pattern analysis and machine intelligence, 2019. (IF=20.8, 中科院 1 区 Top) [Google Scholar] 
  • Kai Zhao and Wei Shen and Shanghua Gao and Dandan Li and Ming-Ming Cheng, "Hi-Fi: Hierarchical Feature Integration for Skeleton Detection", Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018. DOI: 10.24963/ijcai.2018/166  [PDF]  [Google Scholar] 
  • Wei Shen and Yilu Guo and Yan Wang and Kai Zhao and Bo Wang and Alan L Yuille, "Deep regression forests for age estimation", Proceedings of the IEEE conference on computer vision and pattern recognition, 2018. [Google Scholar] 
  • Wei Shen and Kai Zhao and Yuan Jiang and Yan Wang and Xiang Bai and Alan Yuille, "Deepskeleton: Learning multi-task scale-associated deep side outputs for object skeleton extraction in natural images", IEEE Transactions on Image Processing, 2017. [Google Scholar] 
  • Wei Shen and Kai Zhao and Yilu Guo and Alan L Yuille, "Label distribution learning forests", Advances in neural information processing systems, 2017. [Google Scholar] 
  • Wei Shen and Kai Zhao and Yuan Jiang and Yan Wang and Zhijiang Zhang and Xiang Bai, "Object skeleton extraction in natural images by fusing scale-associated deep side outputs", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016. [Google Scholar] 

The list is generated from publications.bib. Please visit my Google Scholar for full publication list.

Academic Services:

  • 会议审稿: CVPR, ICCV, ECCV, ICML, ICLR, NeurIPS, AISTAT, ACCV
  • 期刊审稿: IEEE TPAMI, IEEE TIP, IEEE TNNLS, IEEE TMM, Pattern Recognition
  • Guest Editor: MDPI Diagnostics
School of Athens
The School of Athens.