XIAO, Jiashun

POSITION/TITLE

SRIBD, Medical Big Data Lab, Research Scientist

RESEARCH FIELD

Bioinformatics, Genome-wide association analysis (GWAS), statistical and machine learning methods for spatial transcriptome and multi-omics data

EMAIL

xiaojiashun@sribd.cn

EDUCATION BACKGROUND

Ph.D. in Mathematics, Hong Kong University of Science and Technology, 2018-2022

B.S. in Bioinformatics, Southern University of Science and Technology, 2013-2017

BIOGRAPHY

Dr. Xiao Jiashun is currently a research scientist in the Medical Big Data Laboratory of Shenzhen Institute of Big Data Research. He received a Ph.D. in Mathematics from Hong Kong University of Science and Technology in 2022, and a Bachelor's degree in Bioinformatics from Southern University of Science and Technology in 2017. He joined WeGene as a bioinformatics engineer from 207 to 2018. His research aims to develop statistical and machine learning methods for multi-omics data, including trans-ancestry association mapping, polygenic prediction with large-scale genetic data, and integrative analysis of single-cell and spatial transcriptomics data, etc. He has published several papers in international academic journals (AJHG, Bioinformatics, etc.) as the first or co-first author.

ACADEMIC PUBLICATIONS

Xiao, J.#, Cai, M.#, Yu, X., Hu, X., Chen, G., Wan, X., & Yang, C. (2022). Leveraging the local genetic structure for trans-ancestry association mapping. The American Journal of Human Genetics, 109(7), 1317-1337.

Xiao, J.#, Cai, M.#, Hu, X., Wan, X., Chen, G., & Yang, C. (2022). XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis. Bioinformatics, 38(7), 1947-1955.

Cai, M#., Xiao, J#., Zhang, S#., Wan, X., Zhao, H., Chen, G., & Yang, C. (2021). A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits. The American Journal of Human Genetics, 108(4), 632-655.

Yu X., Xiao J., Cai M., Jiao Y., Wan X., Liu J., Yang C. (2023). PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations. Bioinformatics, 39(2).

Yiming Chao, Yang Xiang, Jiashun Xiao, et al. (2023). Organoid-based single-cell spatiotemporal gene expression landscape of human embryonic development and hematopoiesis. Signal Transduction and Targeted Therapy, Under minor revision.

# co-first author

GAO, Anningzhe

POSITION/TITLE

Research Scientise

RESEARCH FIELD

Data Mining, Deep Neural Networks, Reinforcement Learning

EMAIL

gaoanningzhe@sribd.cn

EDUCATION BACKGROUND

Undergraduate: Department of Mathematics, Tsinghua University, 2016

Ph.D.: Department of Mathematics, University of California, Berkeley, 2021

Main Achievements/Honors:

Outstanding Graduate of Beijing (2016)

BIOGRAPHY

Dr. Gao Anningzhe graduated with a bachelor's degree from the Department of Mathematics at Tsinghua University and earned a Ph.D. from the Department of Mathematics at the University of California, Berkeley. Following graduation, Dr. Gao worked as a Senior Algorithm Researcher at Tencent and currently holds the position of Research Scientist at the Shenzhen Big Data Research Institute. His research interests include data mining, deep learning, and large-scale natural language models.

ACADEMIC PUBLICATIONS

1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020

GAO, Anningzhe

POSITION/TITLE

Research Scientise

RESEARCH FIELD

Data Mining, Deep Neural Networks, Reinforcement Learning

EMAIL

gaoanningzhe@sribd.cn

EDUCATION BACKGROUND

Undergraduate: Department of Mathematics, Tsinghua University, 2016

Ph.D.: Department of Mathematics, University of California, Berkeley, 2021

Main Achievements/Honors:

Outstanding Graduate of Beijing (2016)

BIOGRAPHY

Dr. Gao Anningzhe graduated with a bachelor's degree from the Department of Mathematics at Tsinghua University and earned a Ph.D. from the Department of Mathematics at the University of California, Berkeley. Following graduation, Dr. Gao worked as a Senior Algorithm Researcher at Tencent and currently holds the position of Research Scientist at the Shenzhen Big Data Research Institute. His research interests include data mining, deep learning, and large-scale natural language models.

ACADEMIC PUBLICATIONS

1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020

GAO, Anningzhe

POSITION/TITLE

Research Scientise

RESEARCH FIELD

Data Mining, Deep Neural Networks, Reinforcement Learning

EMAIL

gaoanningzhe@sribd.cn

EDUCATION BACKGROUND

Undergraduate: Department of Mathematics, Tsinghua University, 2016

Ph.D.: Department of Mathematics, University of California, Berkeley, 2021

Main Achievements/Honors:

Outstanding Graduate of Beijing (2016)

BIOGRAPHY

Dr. Gao Anningzhe graduated with a bachelor's degree from the Department of Mathematics at Tsinghua University and earned a Ph.D. from the Department of Mathematics at the University of California, Berkeley. Following graduation, Dr. Gao worked as a Senior Algorithm Researcher at Tencent and currently holds the position of Research Scientist at the Shenzhen Big Data Research Institute. His research interests include data mining, deep learning, and large-scale natural language models.

ACADEMIC PUBLICATIONS

1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020

GAO, Anningzhe

POSITION/TITLE

Research Scientise

RESEARCH FIELD

Data Mining, Deep Neural Networks, Reinforcement Learning

EMAIL

gaoanningzhe@sribd.cn

EDUCATION BACKGROUND

Undergraduate: Department of Mathematics, Tsinghua University, 2016

Ph.D.: Department of Mathematics, University of California, Berkeley, 2021

Main Achievements/Honors:

Outstanding Graduate of Beijing (2016)

BIOGRAPHY

Dr. Gao Anningzhe graduated with a bachelor's degree from the Department of Mathematics at Tsinghua University and earned a Ph.D. from the Department of Mathematics at the University of California, Berkeley. Following graduation, Dr. Gao worked as a Senior Algorithm Researcher at Tencent and currently holds the position of Research Scientist at the Shenzhen Big Data Research Institute. His research interests include data mining, deep learning, and large-scale natural language models.

ACADEMIC PUBLICATIONS

1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020

LIU, Siqi

TITLE/POSITON

Research Scientist

RESEARCH DIRECTION

Medical Image Analysis, Biometric Security, Computer Vision, Deep Learning

EMAIL

siqiliu@sribd.cn

EDUCATION BACKGROUND

Ph.D. in Hong Kong Baptist University 

B.Sc. in Sun Yat-sen University

BIOGRAPHY

刘斯奇博士现为深圳大数据研究院医疗大数据实验室研究科学家。他在中山大学获得学士学位，后赴香港浸会大学深造，于2021年获计算机科学博士学位并继续博士后研究工作至2022年。刘斯奇博士在2014年于京都大学进行访问交流。他的研究兴趣包括胃肠镜影像分析，病例图像分析等医学影像分析相关方向，生物识别安全，计算机视觉和深度学习。他在ECCV, AAA, IJCAI, IEEE TIFS 等计算机视觉与模式识别领域顶级会议和期刊发表文章数篇，并连续担任CVPR、ICCV、ECCV、ICLR、AAAI、IJCAI、WACV、IEEE TPAMI、TIP、TIFS、TDSC、TBIOM等顶级会议和期刊审稿人。

PAPER

  • SQ. Liu, X. Lan, and PC. Yuen, “Learning Temporal Similarity of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2022.
  • SQ. Liu, X. Lan, and PC. Yuen, “Multi-Channel Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2021.
  • SQ. Liu, and PC. Yuen, “A General Remote Photoplethysmography Estimator with Spatiotemporal Convolutional Network,” FG, 2020.
  • SQ. Liu, X. Lan, and PC. Yuen, “Temporal Similarity Analysis of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” WACV, 2020.
  • SQ. Liu, X. Lan, PC. Yuen, “Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection” in ECCV, 2018.
  • SQ. Liu, PC. Yuen, S. Zhang, G. Zhao,”3D Mask Face Anti-spoofing with Remote Photoplethysmography” in ECCV, 2016.
  • SQ. Liu, B. Yang, PC. Yuen, G. Zhao, “A 3D Mask Face Anti-spoofing Database with Real World Variations.” in CVPRW, 2016.
  • C. Yin, SQ. Liu, VWS. Wong, PC. Yuen, “Learning Sparse Interpretable Features For NAS Scoring From Liver Biopsy Images,” IJCAI, 2022.
  • C. Yin, SQ. Liu, R. Shao, and PC. Yuen, “Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification,” MICCAI, 2021. (Oral (11.3%))
  • J. Du, SQ. Liu, B. Zhang, and PC. Yuen, “Weakly Supervised rPPG Estimation for Respiratory Rate Estimation,” ICCVW, 2021.
  • W. Lou, X. Yu, C. Liu, X. Wan, G. Li, SQ. Liu, H. Li, “Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images.” In NeurIPS, 2022

PUBLICATION

  • SQ. Liu, PC. Yuen, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Hand- book of Biometric Anti-Spoofing (Third Edition): Presentation Attack Detection and Vulnerability Assessment, Springer, 2022.
  • SQ. Liu, PC. Yuen, X. Li, and G. Zhao, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Handbook of Biometric Anti-Spoofing (Second Edition): Presentation Attack Detection, Springer, 2019.

PATENT

  • PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
LIU, Siqi

TITLE/POSITON

Research Scientist

RESEARCH DIRECTION

Medical Image Analysis, Biometric Security, Computer Vision, Deep Learning

EMAIL

siqiliu@sribd.cn

EDUCATION BACKGROUND

Ph.D. in Hong Kong Baptist University 

B.Sc. in Sun Yat-sen University

BIOGRAPHY

刘斯奇博士现为深圳大数据研究院医疗大数据实验室研究科学家。他在中山大学获得学士学位，后赴香港浸会大学深造，于2021年获计算机科学博士学位并继续博士后研究工作至2022年。刘斯奇博士在2014年于京都大学进行访问交流。他的研究兴趣包括胃肠镜影像分析，病例图像分析等医学影像分析相关方向，生物识别安全，计算机视觉和深度学习。他在ECCV, AAA, IJCAI, IEEE TIFS 等计算机视觉与模式识别领域顶级会议和期刊发表文章数篇，并连续担任CVPR、ICCV、ECCV、ICLR、AAAI、IJCAI、WACV、IEEE TPAMI、TIP、TIFS、TDSC、TBIOM等顶级会议和期刊审稿人。

PAPER

  • SQ. Liu, X. Lan, and PC. Yuen, “Learning Temporal Similarity of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2022.
  • SQ. Liu, X. Lan, and PC. Yuen, “Multi-Channel Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2021.
  • SQ. Liu, and PC. Yuen, “A General Remote Photoplethysmography Estimator with Spatiotemporal Convolutional Network,” FG, 2020.
  • SQ. Liu, X. Lan, and PC. Yuen, “Temporal Similarity Analysis of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” WACV, 2020.
  • SQ. Liu, X. Lan, PC. Yuen, “Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection” in ECCV, 2018.
  • SQ. Liu, PC. Yuen, S. Zhang, G. Zhao,”3D Mask Face Anti-spoofing with Remote Photoplethysmography” in ECCV, 2016.
  • SQ. Liu, B. Yang, PC. Yuen, G. Zhao, “A 3D Mask Face Anti-spoofing Database with Real World Variations.” in CVPRW, 2016.
  • C. Yin, SQ. Liu, VWS. Wong, PC. Yuen, “Learning Sparse Interpretable Features For NAS Scoring From Liver Biopsy Images,” IJCAI, 2022.
  • C. Yin, SQ. Liu, R. Shao, and PC. Yuen, “Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification,” MICCAI, 2021. (Oral (11.3%))
  • J. Du, SQ. Liu, B. Zhang, and PC. Yuen, “Weakly Supervised rPPG Estimation for Respiratory Rate Estimation,” ICCVW, 2021.
  • W. Lou, X. Yu, C. Liu, X. Wan, G. Li, SQ. Liu, H. Li, “Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images.” In NeurIPS, 2022

PUBLICATION

  • SQ. Liu, PC. Yuen, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Hand- book of Biometric Anti-Spoofing (Third Edition): Presentation Attack Detection and Vulnerability Assessment, Springer, 2022.
  • SQ. Liu, PC. Yuen, X. Li, and G. Zhao, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Handbook of Biometric Anti-Spoofing (Second Edition): Presentation Attack Detection, Springer, 2019.

PATENT

  • PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
LIU, Siqi

TITLE/POSITON

Research Scientist

RESEARCH DIRECTION

Medical Image Analysis, Biometric Security, Computer Vision, Deep Learning

EMAIL

siqiliu@sribd.cn

EDUCATION BACKGROUND

Ph.D. in Hong Kong Baptist University 

B.Sc. in Sun Yat-sen University

BIOGRAPHY

刘斯奇博士现为深圳大数据研究院医疗大数据实验室研究科学家。他在中山大学获得学士学位，后赴香港浸会大学深造，于2021年获计算机科学博士学位并继续博士后研究工作至2022年。刘斯奇博士在2014年于京都大学进行访问交流。他的研究兴趣包括胃肠镜影像分析，病例图像分析等医学影像分析相关方向，生物识别安全，计算机视觉和深度学习。他在ECCV, AAA, IJCAI, IEEE TIFS 等计算机视觉与模式识别领域顶级会议和期刊发表文章数篇，并连续担任CVPR、ICCV、ECCV、ICLR、AAAI、IJCAI、WACV、IEEE TPAMI、TIP、TIFS、TDSC、TBIOM等顶级会议和期刊审稿人。

PAPER

  • SQ. Liu, X. Lan, and PC. Yuen, “Learning Temporal Similarity of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2022.
  • SQ. Liu, X. Lan, and PC. Yuen, “Multi-Channel Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2021.
  • SQ. Liu, and PC. Yuen, “A General Remote Photoplethysmography Estimator with Spatiotemporal Convolutional Network,” FG, 2020.
  • SQ. Liu, X. Lan, and PC. Yuen, “Temporal Similarity Analysis of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” WACV, 2020.
  • SQ. Liu, X. Lan, PC. Yuen, “Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection” in ECCV, 2018.
  • SQ. Liu, PC. Yuen, S. Zhang, G. Zhao,”3D Mask Face Anti-spoofing with Remote Photoplethysmography” in ECCV, 2016.
  • SQ. Liu, B. Yang, PC. Yuen, G. Zhao, “A 3D Mask Face Anti-spoofing Database with Real World Variations.” in CVPRW, 2016.
  • C. Yin, SQ. Liu, VWS. Wong, PC. Yuen, “Learning Sparse Interpretable Features For NAS Scoring From Liver Biopsy Images,” IJCAI, 2022.
  • C. Yin, SQ. Liu, R. Shao, and PC. Yuen, “Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification,” MICCAI, 2021. (Oral (11.3%))
  • J. Du, SQ. Liu, B. Zhang, and PC. Yuen, “Weakly Supervised rPPG Estimation for Respiratory Rate Estimation,” ICCVW, 2021.
  • W. Lou, X. Yu, C. Liu, X. Wan, G. Li, SQ. Liu, H. Li, “Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images.” In NeurIPS, 2022

PUBLICATION

  • SQ. Liu, PC. Yuen, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Hand- book of Biometric Anti-Spoofing (Third Edition): Presentation Attack Detection and Vulnerability Assessment, Springer, 2022.
  • SQ. Liu, PC. Yuen, X. Li, and G. Zhao, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Handbook of Biometric Anti-Spoofing (Second Edition): Presentation Attack Detection, Springer, 2019.

PATENT

  • PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
LIU, Siqi

TITLE/POSITON

Research Scientist

RESEARCH DIRECTION

Medical Image Analysis, Biometric Security, Computer Vision, Deep Learning

EMAIL

siqiliu@sribd.cn

EDUCATION BACKGROUND

Ph.D. in Hong Kong Baptist University 

B.Sc. in Sun Yat-sen University

BIOGRAPHY

刘斯奇博士现为深圳大数据研究院医疗大数据实验室研究科学家。他在中山大学获得学士学位，后赴香港浸会大学深造，于2021年获计算机科学博士学位并继续博士后研究工作至2022年。刘斯奇博士在2014年于京都大学进行访问交流。他的研究兴趣包括胃肠镜影像分析，病例图像分析等医学影像分析相关方向，生物识别安全，计算机视觉和深度学习。他在ECCV, AAA, IJCAI, IEEE TIFS 等计算机视觉与模式识别领域顶级会议和期刊发表文章数篇，并连续担任CVPR、ICCV、ECCV、ICLR、AAAI、IJCAI、WACV、IEEE TPAMI、TIP、TIFS、TDSC、TBIOM等顶级会议和期刊审稿人。

PAPER

  • SQ. Liu, X. Lan, and PC. Yuen, “Learning Temporal Similarity of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2022.
  • SQ. Liu, X. Lan, and PC. Yuen, “Multi-Channel Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection,” IEEE Transactions on Information Forensics and Security (TIFS), 2021.
  • SQ. Liu, and PC. Yuen, “A General Remote Photoplethysmography Estimator with Spatiotemporal Convolutional Network,” FG, 2020.
  • SQ. Liu, X. Lan, and PC. Yuen, “Temporal Similarity Analysis of Remote Photoplethysmography for Fast 3D Mask Face Presentation Attack Detection,” WACV, 2020.
  • SQ. Liu, X. Lan, PC. Yuen, “Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection” in ECCV, 2018.
  • SQ. Liu, PC. Yuen, S. Zhang, G. Zhao,”3D Mask Face Anti-spoofing with Remote Photoplethysmography” in ECCV, 2016.
  • SQ. Liu, B. Yang, PC. Yuen, G. Zhao, “A 3D Mask Face Anti-spoofing Database with Real World Variations.” in CVPRW, 2016.
  • C. Yin, SQ. Liu, VWS. Wong, PC. Yuen, “Learning Sparse Interpretable Features For NAS Scoring From Liver Biopsy Images,” IJCAI, 2022.
  • C. Yin, SQ. Liu, R. Shao, and PC. Yuen, “Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification,” MICCAI, 2021. (Oral (11.3%))
  • J. Du, SQ. Liu, B. Zhang, and PC. Yuen, “Weakly Supervised rPPG Estimation for Respiratory Rate Estimation,” ICCVW, 2021.
  • W. Lou, X. Yu, C. Liu, X. Wan, G. Li, SQ. Liu, H. Li, “Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images.” In NeurIPS, 2022

PUBLICATION

  • SQ. Liu, PC. Yuen, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Hand- book of Biometric Anti-Spoofing (Third Edition): Presentation Attack Detection and Vulnerability Assessment, Springer, 2022.
  • SQ. Liu, PC. Yuen, X. Li, and G. Zhao, “Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks,” Handbook of Biometric Anti-Spoofing (Second Edition): Presentation Attack Detection, Springer, 2019.

PATENT

  • PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
LI, Haofeng

POSITION/TITLE 

SRIBD Research Scientist

RESEARCH FIELD

Medical Image Analysis, Computer Vision, Deep Neural Networks

3、EMAIL

lhaof@sribd.cn

PERSONAL WEBSITE

http://haofengli.net/ 

EDUCATION BACKGROUND

PhD, The University of Hong Kong

BSc, Sun Yat-sen University

BIOGRAPHY

Dr. Haofeng Li received his Ph.D. degree in computer science from The University of Hong Kong (2015-2020) and his B.Sc. degree in computer science from Sun Yat-sen University (2011-2015). In June 2020, he joined Shenzhen Research Institute of Big Data (SRIBD). His research interests include medical image analysis, computer vision and deep neural networks. He already published 15 papers on the well-known conferences and journals, including IEEE TMI, MedIA, MICCAI, ICCV, AAAI, ACM MM, IEEE TIP, IEEE TCyb, ISBI etc. Dr. Haofeng Li is the reviewer of IEEE TPAMI, IEEE TIP, IEEE TCYB, Pattern Regconition, Neurocomputing, NeurIPS 2022, MICCAI 2023 etc. He is the principle investigator (PI) that leads a project supported by National Natural Science Foundation of China (NSFC) and a project supported by Guangdong Basic and Applied Basic Research Foundation. He led a team to obtain the 2nd place of NeurIPS cell segmentation challenge (out of 100 teams). He is recruiting students and team members. For more details, please visit http://haofengli.net/ 

7、ACADEMIC PUBLICATIONS

* Joint first authors  # Corresponding author

  1. Wei Lou, Haofeng Li#(Corresponding), Guanbin Li, Xiaoguang Han, Xiang Wan, Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework, IEEE Transactions on Medical Imaging (TMI, IF=11.037), 2022.11
  2. Junjia Huang, Haofeng Li#(Corresponding), Guanbin Li#, Xiang Wan, Attentive Symmetric Autoencoder for Brain MRI Segmentation, Early Accept (top 13%) in MICCAI, 2022.09
  3. Haofeng Li, Junjia Huang, Guanbin Li, Zhou Liu, Yihong Zhong, Yingying Chen, Yunfei Wang, Xiang Wan, View-Disentangled Transformer for Brain Lesion Detection, International Symposium on Biomedical Imaging (ISBI), 2022.03
  4. Jiutao Yue*, Haofeng Li* (Joint first author), Pengxu Wei, Guanbin Li, Liang Lin, Robust Real-World Image Super-Resolution against Adversarial Attacks, ACM Multimedia (CCF A), 2021.10
  5. Hong-Yu Zhou*, Chengdi Wang*, Haofeng Li* (Joint first author), Gang Wang, Shu Zhang, Weimin Li, Yizhou Yu, SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation, Medical Image Analysis (IF = 8.545), 2021.08
  6. Haofeng Li, Yirui Zeng, Guanbin Li, Liang Lin, Yizhou Yu, Online Alternate Generator against Adversarial Attacks, IEEE Transactions on Image Processing (TIP, CCF A, IF=10.856), 2020.09
  7. Haofeng Li, Guanqi Chen, Guanbin Li, Yizhou Yu, Motion Guided Attention for Video Salient Object Detection, IEEE International Conference on Computer Vision (ICCV, CCF A), 2019.11
  8. Haofeng Li, Guanbin Li, Yizhou Yu, ROSA: Robust Salient Object Detection Against Adversarial Attacks, IEEE Transactions on Cybernetics (JCR Q1, IF=11.079), 2019
  9. Haofeng Li, Guanbin Li, Liang Lin, Hongchuan Yu, Yizhou Yu, Context Aware Semantic Inpainting, IEEE Transactions on Cybernetics (JCR Q1), 2018
  10. Xiang He, Sibei Yang, Guanbin Li, Haofeng Li, Huiyou Chang, Yizhou Yu, Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks, Oral Presentation in AAAI (CCF A), 2019
  11. Kan Wu, Guanbin Li, Haofeng Li, Jianjun Zhang, Yizhou Yu, Harvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment, ACM Transactions on Multimedia Computing, Communications and Applications TOMM (CCF B), 2019
LI, Haofeng

POSITION/TITLE 

SRIBD Research Scientist

RESEARCH FIELD

Medical Image Analysis, Computer Vision, Deep Neural Networks

3、EMAIL

lhaof@sribd.cn

PERSONAL WEBSITE

http://haofengli.net/ 

EDUCATION BACKGROUND

PhD, The University of Hong Kong

BSc, Sun Yat-sen University

BIOGRAPHY

Dr. Haofeng Li received his Ph.D. degree in computer science from The University of Hong Kong (2015-2020) and his B.Sc. degree in computer science from Sun Yat-sen University (2011-2015). In June 2020, he joined Shenzhen Research Institute of Big Data (SRIBD). His research interests include medical image analysis, computer vision and deep neural networks. He already published 15 papers on the well-known conferences and journals, including IEEE TMI, MedIA, MICCAI, ICCV, AAAI, ACM MM, IEEE TIP, IEEE TCyb, ISBI etc. Dr. Haofeng Li is the reviewer of IEEE TPAMI, IEEE TIP, IEEE TCYB, Pattern Regconition, Neurocomputing, NeurIPS 2022, MICCAI 2023 etc. He is the principle investigator (PI) that leads a project supported by National Natural Science Foundation of China (NSFC) and a project supported by Guangdong Basic and Applied Basic Research Foundation. He led a team to obtain the 2nd place of NeurIPS cell segmentation challenge (out of 100 teams). He is recruiting students and team members. For more details, please visit http://haofengli.net/ 

7、ACADEMIC PUBLICATIONS

* Joint first authors  # Corresponding author

  1. Wei Lou, Haofeng Li#(Corresponding), Guanbin Li, Xiaoguang Han, Xiang Wan, Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework, IEEE Transactions on Medical Imaging (TMI, IF=11.037), 2022.11
  2. Junjia Huang, Haofeng Li#(Corresponding), Guanbin Li#, Xiang Wan, Attentive Symmetric Autoencoder for Brain MRI Segmentation, Early Accept (top 13%) in MICCAI, 2022.09
  3. Haofeng Li, Junjia Huang, Guanbin Li, Zhou Liu, Yihong Zhong, Yingying Chen, Yunfei Wang, Xiang Wan, View-Disentangled Transformer for Brain Lesion Detection, International Symposium on Biomedical Imaging (ISBI), 2022.03
  4. Jiutao Yue*, Haofeng Li* (Joint first author), Pengxu Wei, Guanbin Li, Liang Lin, Robust Real-World Image Super-Resolution against Adversarial Attacks, ACM Multimedia (CCF A), 2021.10
  5. Hong-Yu Zhou*, Chengdi Wang*, Haofeng Li* (Joint first author), Gang Wang, Shu Zhang, Weimin Li, Yizhou Yu, SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation, Medical Image Analysis (IF = 8.545), 2021.08
  6. Haofeng Li, Yirui Zeng, Guanbin Li, Liang Lin, Yizhou Yu, Online Alternate Generator against Adversarial Attacks, IEEE Transactions on Image Processing (TIP, CCF A, IF=10.856), 2020.09
  7. Haofeng Li, Guanqi Chen, Guanbin Li, Yizhou Yu, Motion Guided Attention for Video Salient Object Detection, IEEE International Conference on Computer Vision (ICCV, CCF A), 2019.11
  8. Haofeng Li, Guanbin Li, Yizhou Yu, ROSA: Robust Salient Object Detection Against Adversarial Attacks, IEEE Transactions on Cybernetics (JCR Q1, IF=11.079), 2019
  9. Haofeng Li, Guanbin Li, Liang Lin, Hongchuan Yu, Yizhou Yu, Context Aware Semantic Inpainting, IEEE Transactions on Cybernetics (JCR Q1), 2018
  10. Xiang He, Sibei Yang, Guanbin Li, Haofeng Li, Huiyou Chang, Yizhou Yu, Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks, Oral Presentation in AAAI (CCF A), 2019
  11. Kan Wu, Guanbin Li, Haofeng Li, Jianjun Zhang, Yizhou Yu, Harvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment, ACM Transactions on Multimedia Computing, Communications and Applications TOMM (CCF B), 2019
LI, Haofeng

POSITION/TITLE 

SRIBD Research Scientist

RESEARCH FIELD

Medical Image Analysis, Computer Vision, Deep Neural Networks

3、EMAIL

lhaof@sribd.cn

PERSONAL WEBSITE

http://haofengli.net/ 

EDUCATION BACKGROUND

PhD, The University of Hong Kong

BSc, Sun Yat-sen University

BIOGRAPHY

Dr. Haofeng Li received his Ph.D. degree in computer science from The University of Hong Kong (2015-2020) and his B.Sc. degree in computer science from Sun Yat-sen University (2011-2015). In June 2020, he joined Shenzhen Research Institute of Big Data (SRIBD). His research interests include medical image analysis, computer vision and deep neural networks. He already published 15 papers on the well-known conferences and journals, including IEEE TMI, MedIA, MICCAI, ICCV, AAAI, ACM MM, IEEE TIP, IEEE TCyb, ISBI etc. Dr. Haofeng Li is the reviewer of IEEE TPAMI, IEEE TIP, IEEE TCYB, Pattern Regconition, Neurocomputing, NeurIPS 2022, MICCAI 2023 etc. He is the principle investigator (PI) that leads a project supported by National Natural Science Foundation of China (NSFC) and a project supported by Guangdong Basic and Applied Basic Research Foundation. He led a team to obtain the 2nd place of NeurIPS cell segmentation challenge (out of 100 teams). He is recruiting students and team members. For more details, please visit http://haofengli.net/ 

7、ACADEMIC PUBLICATIONS

* Joint first authors  # Corresponding author

  1. Wei Lou, Haofeng Li#(Corresponding), Guanbin Li, Xiaoguang Han, Xiang Wan, Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework, IEEE Transactions on Medical Imaging (TMI, IF=11.037), 2022.11
  2. Junjia Huang, Haofeng Li#(Corresponding), Guanbin Li#, Xiang Wan, Attentive Symmetric Autoencoder for Brain MRI Segmentation, Early Accept (top 13%) in MICCAI, 2022.09
  3. Haofeng Li, Junjia Huang, Guanbin Li, Zhou Liu, Yihong Zhong, Yingying Chen, Yunfei Wang, Xiang Wan, View-Disentangled Transformer for Brain Lesion Detection, International Symposium on Biomedical Imaging (ISBI), 2022.03
  4. Jiutao Yue*, Haofeng Li* (Joint first author), Pengxu Wei, Guanbin Li, Liang Lin, Robust Real-World Image Super-Resolution against Adversarial Attacks, ACM Multimedia (CCF A), 2021.10
  5. Hong-Yu Zhou*, Chengdi Wang*, Haofeng Li* (Joint first author), Gang Wang, Shu Zhang, Weimin Li, Yizhou Yu, SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation, Medical Image Analysis (IF = 8.545), 2021.08
  6. Haofeng Li, Yirui Zeng, Guanbin Li, Liang Lin, Yizhou Yu, Online Alternate Generator against Adversarial Attacks, IEEE Transactions on Image Processing (TIP, CCF A, IF=10.856), 2020.09
  7. Haofeng Li, Guanqi Chen, Guanbin Li, Yizhou Yu, Motion Guided Attention for Video Salient Object Detection, IEEE International Conference on Computer Vision (ICCV, CCF A), 2019.11
  8. Haofeng Li, Guanbin Li, Yizhou Yu, ROSA: Robust Salient Object Detection Against Adversarial Attacks, IEEE Transactions on Cybernetics (JCR Q1, IF=11.079), 2019
  9. Haofeng Li, Guanbin Li, Liang Lin, Hongchuan Yu, Yizhou Yu, Context Aware Semantic Inpainting, IEEE Transactions on Cybernetics (JCR Q1), 2018
  10. Xiang He, Sibei Yang, Guanbin Li, Haofeng Li, Huiyou Chang, Yizhou Yu, Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks, Oral Presentation in AAAI (CCF A), 2019
  11. Kan Wu, Guanbin Li, Haofeng Li, Jianjun Zhang, Yizhou Yu, Harvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment, ACM Transactions on Multimedia Computing, Communications and Applications TOMM (CCF B), 2019
LI, Haofeng

POSITION/TITLE 

SRIBD Research Scientist

RESEARCH FIELD

Medical Image Analysis, Computer Vision, Deep Neural Networks

3、EMAIL

lhaof@sribd.cn

PERSONAL WEBSITE

http://haofengli.net/ 

EDUCATION BACKGROUND

PhD, The University of Hong Kong

BSc, Sun Yat-sen University

BIOGRAPHY

Dr. Haofeng Li received his Ph.D. degree in computer science from The University of Hong Kong (2015-2020) and his B.Sc. degree in computer science from Sun Yat-sen University (2011-2015). In June 2020, he joined Shenzhen Research Institute of Big Data (SRIBD). His research interests include medical image analysis, computer vision and deep neural networks. He already published 15 papers on the well-known conferences and journals, including IEEE TMI, MedIA, MICCAI, ICCV, AAAI, ACM MM, IEEE TIP, IEEE TCyb, ISBI etc. Dr. Haofeng Li is the reviewer of IEEE TPAMI, IEEE TIP, IEEE TCYB, Pattern Regconition, Neurocomputing, NeurIPS 2022, MICCAI 2023 etc. He is the principle investigator (PI) that leads a project supported by National Natural Science Foundation of China (NSFC) and a project supported by Guangdong Basic and Applied Basic Research Foundation. He led a team to obtain the 2nd place of NeurIPS cell segmentation challenge (out of 100 teams). He is recruiting students and team members. For more details, please visit http://haofengli.net/ 

7、ACADEMIC PUBLICATIONS

* Joint first authors  # Corresponding author

  1. Wei Lou, Haofeng Li#(Corresponding), Guanbin Li, Xiaoguang Han, Xiang Wan, Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework, IEEE Transactions on Medical Imaging (TMI, IF=11.037), 2022.11
  2. Junjia Huang, Haofeng Li#(Corresponding), Guanbin Li#, Xiang Wan, Attentive Symmetric Autoencoder for Brain MRI Segmentation, Early Accept (top 13%) in MICCAI, 2022.09
  3. Haofeng Li, Junjia Huang, Guanbin Li, Zhou Liu, Yihong Zhong, Yingying Chen, Yunfei Wang, Xiang Wan, View-Disentangled Transformer for Brain Lesion Detection, International Symposium on Biomedical Imaging (ISBI), 2022.03
  4. Jiutao Yue*, Haofeng Li* (Joint first author), Pengxu Wei, Guanbin Li, Liang Lin, Robust Real-World Image Super-Resolution against Adversarial Attacks, ACM Multimedia (CCF A), 2021.10
  5. Hong-Yu Zhou*, Chengdi Wang*, Haofeng Li* (Joint first author), Gang Wang, Shu Zhang, Weimin Li, Yizhou Yu, SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation, Medical Image Analysis (IF = 8.545), 2021.08
  6. Haofeng Li, Yirui Zeng, Guanbin Li, Liang Lin, Yizhou Yu, Online Alternate Generator against Adversarial Attacks, IEEE Transactions on Image Processing (TIP, CCF A, IF=10.856), 2020.09
  7. Haofeng Li, Guanqi Chen, Guanbin Li, Yizhou Yu, Motion Guided Attention for Video Salient Object Detection, IEEE International Conference on Computer Vision (ICCV, CCF A), 2019.11
  8. Haofeng Li, Guanbin Li, Yizhou Yu, ROSA: Robust Salient Object Detection Against Adversarial Attacks, IEEE Transactions on Cybernetics (JCR Q1, IF=11.079), 2019
  9. Haofeng Li, Guanbin Li, Liang Lin, Hongchuan Yu, Yizhou Yu, Context Aware Semantic Inpainting, IEEE Transactions on Cybernetics (JCR Q1), 2018
  10. Xiang He, Sibei Yang, Guanbin Li, Haofeng Li, Huiyou Chang, Yizhou Yu, Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks, Oral Presentation in AAAI (CCF A), 2019
  11. Kan Wu, Guanbin Li, Haofeng Li, Jianjun Zhang, Yizhou Yu, Harvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment, ACM Transactions on Multimedia Computing, Communications and Applications TOMM (CCF B), 2019
HU, Yujin

POSITION/TITLE

Development Engineer

RESEARCH FIELD

Medical image analysis

EMAIL

huyujin@sribd.cn

EDUCATION BACKGROUND

Biomedical Engineering, School of biomedical engineering, south-central minzu university, bachelor

Biomedical Engineering, School of Biomedical Engineering, medical School, Shenzhen University, master

HU, Yujin

POSITION/TITLE

Development Engineer

RESEARCH FIELD

Medical image analysis

EMAIL

huyujin@sribd.cn

EDUCATION BACKGROUND

Biomedical Engineering, School of biomedical engineering, south-central minzu university, bachelor

Biomedical Engineering, School of Biomedical Engineering, medical School, Shenzhen University, master