Kai Zhao, Ph.D.
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 4,000 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。
联系方式
- 10945 Le Conte Avenue, Los Angeles, CA 90024, USA.
- kzkaizhao.net (请发邮件和我联系,发邮件时请说明来意并尽量简洁直接。)
Publications:
- Pang, Kaifeng and Zhao, Kai* and Hung, Alex and Zheng, Haoxin and Yan, Ran and Sung, Kyunghyun, "NExpR: Neural Explicit Representation for Fast Arbitrary-scale Medical Image Super-resolution", Computers in Biology and Medicine, 2025, (* corresponding author)
- Zhao, Kai and Hung, Alex Ling Yu and Pang, Kaifeng and Zheng, Haoxin and Sung, Kyunghyun, "MRI Super-Resolution with Partial Diffusion Models", IEEE Transactions on Medical Imaging, 2024, DOI: 10.1109/TMI.2024.3483109
- Zhao, Kai and He, Zuojie and Hung, Alex and Zeng, Dan, "Dominant Shuffle: A Simple Yet Powerful Data Augmentation for Time-series Prediction", arXiv:2405.16456, 2024
- Zhao, Kai and Pang, Kaifeng and Hung, Alex LingYu and Zheng, Haoxin and Yan, Ran and Sung, Kyunghyun, "A Deep Learning-Based Framework for Highly Accelerated Prostate MR Dispersion Imaging", Cancers, 2024, DOI: 10.3390/cancers16172983
- Hung, Alex Ling Yu and Zheng, Haoxin and Zhao, Kai and Pang, Kaifeng and Terzopoulos, Demetri and Sung, Kyunghyun, "Cross-Slice Attention and Evidential Critical Loss for Uncertainty-Aware Prostate Cancer Detection", International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024
- Zhao, Kai and Wang, Tao and Zhang, Ruixin and Shen, Wei, "Adaptive feature alignment for adversarial training", Pattern Recognition Letters, 2024, DOI: j.patrec.2024.10.004
- Hung, Alex Ling Yu and Zhao, Kai and Zheng, Haoxin and Yan, Ran and Raman, Steven S and Terzopoulos, Demetri and Sung, Kyunghyun, "Med-cDiff: Conditional medical image generation with diffusion models", Bioengineering, 2023
- Xu, Yating and Zhao, Kai and Zhang, Liangang and Zhu, Mengyao and Zeng, Dan, "Hyperspectral anomaly detection with vision transformer and adversarial refinement", International Journal of Remote Sensing, 2023
- Zhao, Kai and Shen, Lei and Zhang, Yingyi and Zhou, Chuhan and Wang, Tao and Zhang, Ruixin and Ding, Shouhong and Jia, Wei and Shen, Wei, "B'ezierpalm: A free lunch for palmprint recognition", European Conference on Computer Vision, 2022
- Zhao, Kai and Han, Qi and Zhang, Chang-Bin and Xu, Jun and Cheng, Ming-Ming, "Deep hough transform for semantic line detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, DOI: 10.1109/TPAMI.2021.3077129
- Zhao, Kai and Shen, Lei and Zhang, Yingyi and Zhou, Chuhan and Wang, Tao and Zhang, Ruixin and Ding, Shouhong and Jia, Wei and Shen, Wei, "BezierPalm3D: Synthetical Pretraining for Palmprint Authentication", Inernational Journal of Computer Vision, under review
- Wang, Xuehui and Zhao, Kai and Zhang, Ruixin and Ding, Shouhong and Wang, Yan and Shen, Wei, "Contrastmask: Contrastive learning to segment every thing", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
- Shen, Lei and Zhang, Yingyi and Zhao, Kai* and Zhang, Ruixin and Shen, Wei, "Distribution alignment for cross-device palmprint recognition", Pattern Recognition, 2022, DOI: 10.1016/j.patcog.2022.108942, (* corresponding author)
- Li, Jia and Zhang, Junjie and Chen, Fansheng and Zhao, Kai and Zeng, Dan, "Adaptive material matching for hyperspectral imagery destriping", IEEE Transactions on Geoscience and Remote Sensing, 2022
- Zhao, Kai and Wang, Xuehui and Chen, Xingyu and Zhang, Ruixin and Shen, Wei, "Rethinking mask heads for partially supervised instance segmentation", Neurocomputing, 2022, DOI: 10.1016/j.neucom.2022.10.003
- Gao, Shang-Hua and Cheng, Ming-Ming and Zhao, Kai and Zhang, Xin-Yu and Yang, Ming-Hsuan and Torr, Philip, "Res2net: A new multi-scale backbone architecture", IEEE transactions on pattern analysis and machine intelligence, 2019
- Zhao, Kai and Gao, Shanghua and Wang, Wenguan and Cheng, Ming-Ming, "Optimizing the F-measure for threshold-free salient object detection", Proceedings of the IEEE/CVF international conference on computer vision, 2019
- Zhao, Kai and Xu, Jingyi and Cheng, Ming-Ming, "Regularface: Deep face recognition via exclusive regularization", Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2019
- Shen, Wei and Guo, Yilu and Wang, Yan and Zhao, Kai and Wang, Bo and Yuille, Alan, "Deep differentiable random forests for age estimation", IEEE transactions on pattern analysis and machine intelligence, 2019
- 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
- Shen, Wei and Guo, Yilu and Wang, Yan and Zhao, Kai and Wang, Bo and Yuille, Alan L, "Deep regression forests for age estimation", Proceedings of the IEEE conference on computer vision and pattern recognition, 2018
- Shen, Wei and Zhao, Kai and Jiang, Yuan and Wang, Yan and Bai, Xiang and Yuille, Alan, "Deepskeleton: Learning multi-task scale-associated deep side outputs for object skeleton extraction in natural images", IEEE Transactions on Image Processing, 2017
- Shen, Wei and Zhao, Kai and Guo, Yilu and Yuille, Alan L, "Label distribution learning forests", Advances in neural information processing systems, 2017
- Shen, Wei and Zhao, Kai and Jiang, Yuan and Wang, Yan and Zhang, Zhijiang and Bai, Xiang, "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
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
The logical, deterministic, and predictable nature of mathematics gives me some sense of security. I feel unsure about a conclusion until it is mathematically proven.