Bio

MSRA

Zengqiang (John) Yan

PhD candidate, 2016-2020

I joined the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology in Sep. 2016 for PhD study, supervised by Prof. Kwang-Ting (Tim) Cheng. My research interests include computer vision, deep learning and medical image processing.

News

[2018.09] Finally, I have passed my PhD qualifying exam and become a PhD candidate! 😄 Two years to graduate! 😂

[2018.08] The revised paper, entitled "A Three-stage Deep Learning Model for Accurate Retinal Vessel Segmentation", has been submitted to IEEE Journal of Biomedical and Health Informatics (under review after major revision).

[2018.07] One paper, entitled "Large-area Depth Recovery for Planar Surfaces in RGB-D Images", has been submitted to IEEE Transactions on Multimedia (under review).

[2018.05] The paper, entitled "A Deep Model with Shape-preserving Loss for Gland Instance Segmentation", has been accepted by the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2018. See you in Spain! [pdf]

[2018.04] The paper, entitled "Joint Segment-level and Pixel-wise Losses for Deep Learning based Retinal Vessel Segmentation", has been accepted by IEEE Transactions on Biomedical Engineering (IEEE TBME). [pdf]

[2018.04] One paper, entitled "A Three-stage Deep Learning Model for Accurate Retinal Vessel Segmentation", has been submitted to IEEE Journal of Biomedical and Health Informatics (under review).

[2018.03] One paper, entitled "Joint Segment-level and Pixel-wise Losses for Deep Learning based Retinal Vessel Segmentation", has been submitted to IEEE Transactions on Biomedical Engineering (under review after major revision).

[2017.11] The paper, entitled "A Skeletal Similarity Metric for Quality Evaluation of Retinal Vessel Segmentation", has been accepted by IEEE Transactions on Medical Imaging (IEEE TMI). [pdf]

Experience

Internship @MSRA

2015.06 - 2015.12

During my internship at Microsoft Research Asia, I worked with Prof. Katsushi Ikeuchi (IEEE Fellow) on a very interesting topic about humanoid robots. With the help of great colleagues, we developed the learning-from-observation paradigm on two different kinds of robot platforms. The demo was selected to the TechFest 2016 of Microsoft.

MSRA

Visit @TAMU

2014.12 - 2015.04

During my visit at Texas A&M University, I worked with Prof. Zixiang Xiong (IEEE Fellow) on machine learning and depth image processing. Under the guidance of Prof. Xiong, I developed a large-area depth recovery algorithm for depth enhancement. The paper won the top 10% paper award at the IEEE Workshop on MMSP 2015.

TAMU

Award

HKUST Postgraduate Scholarship (2016-present)

Award of Excellence, Stars of Tomorrow Internship Program, Microsoft Research Asia 2016

HUAWEI Scholarship (2016)

Top 10% Paper Award, IEEE International Workshop on Multimedia Signal Processing 2015

Student Travel Grant Award, IEEE Signal Processing Society 2015

Selected Publication [All]

Under Review/Revision

Zengqiang Yan, Li Yu, and Zixiang Xiong, "Large-area Depth Recovery for Planar Surfaces in RGB-D Images," IEEE Transactions on Multimedia, 2018. (under review)

Zengqiang Yan, Xin Yang, and Kwang-Ting Cheng, "A Three-stage Deep Learning Model for Accurate Retinal Vessel Segmentation," IEEE Journal of Biomedical and Health Informatics, 2018. (under review after major revision)

Katsushi Ikeuchi, Zhaoyuan Ma, Zengqiang Yan, Shunsuke Kudoh, and Minako Nakamura, "Describing Upper Body Motions based on the Labanotation for Learning-from-Observation Robots," International Journal of Computer Vision (IJCV), 2018. (under review after major revision)

Journal

Zengqiang Yan, Xin Yang, and Kwang-Ting Cheng, "Joint Segment-level and Pixel-wise Losses for Deep Learning based Retinal Vessel Segmentation," IEEE Transactions on Biomedical Engineering, 2018. [pdf]

Zengqiang Yan, Xin Yang, and Kwang-Ting Cheng, "A Skeletal Similarity Metric for Quality Evaluation of Vessel Segmentation," IEEE Transactions on Medical Imaging 37(4), 1045-1057, 2017. [pdf]

Conference

Zengqiang Yan, Xin Yang, and Kwang-Ting Cheng, "A Deep Model with Shape-preserving Loss for Gland Instance Segmentation," in Proc. MICCAI, Sep. 2018. [pdf]

External Links