职务/职称
深圳市大数据研究院医疗大数据实验室研究科学家
研究方向
医疗影像智能分析，计算机视觉，深度神经网络
电子邮箱
lhaof@sribd.cn
教育背景
香港大学计算机科学博士
中山大学计算机科学理学学士
主要成果/荣誉
NeurIPS 2022 细胞分割挑战赛全球亚军
主持中国国家自然科学基金项目
主持广东省基础与应用基础研究基金面上项目
个人介绍
李灏峰博士，现任深圳市大数据研究科学家，2015年于中山大学计算机系获理学学士学位，2020年于香港大学计算机系获博士学位。其研究方向包括医疗影像分析、脑核磁成像分析、组织病理学图像分析和计算机视觉等，在该方向著名国家期刊和会议发表论文20多篇，包括IEEE TMI, MedIA, MICCAI, ICCV, AAAI, ACM MM, IEEE TIP, IEEE TCyb, ISBI等。李灏峰博士是顶级期刊和会议IEEE TPAMI, IEEE TIP, IEEE TCYB, Pattern Regconition, Neurocomputing, NeurIPS 2022, MICCAI 2023等的审稿人。他是IEEE电气电子工程师学会、中国计算机学会和广东省卫生信息网络协会病理数字化应用分会的会员，被评为深圳市海外高层次人才，并入选深龙英才计划。他目前作为项目负责人主持中国国家自然科学基金项目一项，和广东省基础与应用基础研究基金面上项目一项。他曾带领他的团队于2022年12月获得NeurIPS 全球细胞分割挑战赛亚军（100多只参赛队伍）。更多细节详见 http://haofengli.net/
代表性论文
* 共同一作 # 通讯作者
1.Wei Lou, Haofeng Li#(通讯作者), 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#(通讯作者), 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* (共同一作), 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* (共同一作), 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
职务/职称
深圳市大数据研究院研究科学家
香港中文大学（深圳）数据科学学院助理教授
研究方向
自然语言处理、大模型
电子邮箱
wangbenyou@cuhk.edu.cn
教育背景
意大利帕多瓦大学博士
主要成果/荣誉
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award, 华为火花奖
个人介绍
王本友，香港中文大学（深圳）数据科学学院助理教授和医疗健康信息研究中心副主任、深圳市大数据研究院研究科学家。迄今为止，他曾获得了SIGIR 2017最佳论文提名奖、NAACL 2019最佳可解释NLP论文、NLPCC 2022最佳论文、华为火花奖和欧盟玛丽居里奖学金。其领导的研究团队开发的大模型包括多语言大模型凤凰（支持中文）、英文大模型Chimera以及医疗健康垂直领域大模型华佗GPT。
代表性论文
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI一区top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
职务/职称
深圳市大数据研究院研究科学家
香港中文大学（深圳）数据科学学院助理教授
研究方向
自然语言处理、大模型
电子邮箱
wangbenyou@cuhk.edu.cn
教育背景
意大利帕多瓦大学博士
主要成果/荣誉
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award, 华为火花奖
个人介绍
王本友，香港中文大学（深圳）数据科学学院助理教授和医疗健康信息研究中心副主任、深圳市大数据研究院研究科学家。迄今为止，他曾获得了SIGIR 2017最佳论文提名奖、NAACL 2019最佳可解释NLP论文、NLPCC 2022最佳论文、华为火花奖和欧盟玛丽居里奖学金。其领导的研究团队开发的大模型包括多语言大模型凤凰（支持中文）、英文大模型Chimera以及医疗健康垂直领域大模型华佗GPT。
代表性论文
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI一区top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
职务/职称
深圳市大数据研究院研究科学家
香港中文大学（深圳）数据科学学院助理教授
研究方向
自然语言处理、大模型
电子邮箱
wangbenyou@cuhk.edu.cn
教育背景
意大利帕多瓦大学博士
主要成果/荣誉
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award, 华为火花奖
个人介绍
王本友，香港中文大学（深圳）数据科学学院助理教授和医疗健康信息研究中心副主任、深圳市大数据研究院研究科学家。迄今为止，他曾获得了SIGIR 2017最佳论文提名奖、NAACL 2019最佳可解释NLP论文、NLPCC 2022最佳论文、华为火花奖和欧盟玛丽居里奖学金。其领导的研究团队开发的大模型包括多语言大模型凤凰（支持中文）、英文大模型Chimera以及医疗健康垂直领域大模型华佗GPT。
代表性论文
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI一区top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
职务/职称
深圳市大数据研究院研究科学家
香港中文大学（深圳）数据科学学院助理教授
研究方向
自然语言处理、大模型
电子邮箱
wangbenyou@cuhk.edu.cn
教育背景
意大利帕多瓦大学博士
主要成果/荣誉
NLPCC 2022 Best Paper
Best Explainable NLP Paper in NAACL 2019
Best Paper Award Honorable Mention in SIGIR 2017
Huawei Spark Award, 华为火花奖
个人介绍
王本友，香港中文大学（深圳）数据科学学院助理教授和医疗健康信息研究中心副主任、深圳市大数据研究院研究科学家。迄今为止，他曾获得了SIGIR 2017最佳论文提名奖、NAACL 2019最佳可解释NLP论文、NLPCC 2022最佳论文、华为火花奖和欧盟玛丽居里奖学金。其领导的研究团队开发的大模型包括多语言大模型凤凰（支持中文）、英文大模型Chimera以及医疗健康垂直领域大模型华佗GPT。
代表性论文
[1] Jianquan Li, Xiangbo Wu, Xiaokang Liu, Prayag Tiwari, Qianqian Xie. Benyou Wang. Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk. ACL 2023. (CCF A)
[2] Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, Benyou Wang. One Cannot Stand for Everyone! Leveraging Multiple User Simulators to train Task-oriented Dialogue Systems. ACL 2023. (CCF A)
[3] Benyou Wang, Qianqian Xie, Jiahuan Pei, Zhihong Chen, Prayag Tiwari, Zhao Li, Fu Jie. Pre-trained language models in biomedical domain: A systematic survey. ACM Computing Surveys. (SCI一区top)
[4] Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu. Exploring extreme parameter compression for pre-trained language models. ICLR 2022
[5] Peng Zhang, Wenjie Hui, Benyou Wang, Donghao Zhao, Dawei Song, Christina Lioma, Jakob Grue Simonsen. Complex-valued Neural Network-based Quantum Language Models. ACM Transactions on Information Systems. 2022. (CCF A)
[6] Benyou Wang, Emanuele Di Buccio, Massimo Melucci. Word2Fun: Modelling Words as Functions for Diachronic Word Representation. NeurIPS 2021 (CCF A)
[7] Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Grue Simonsen. On position embeddings in BERT. ICLR 2020.
[8] Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen. Encoding word order in complex embeddings. ICLR 2019
[9] Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song. Semantic Hilbert Space for Text Representation Learning. The Web Conference 2018 (WWW). (CCF A)
[10] Qiuchi Li, Benyou Wang, Massimo Melucci. CNM: An Interpretable Complex-valued Network for Matching. NAACL 2018. Best Explainable NLP Paper.(CCF B)
职务/职称
深圳市大数据研究院 医疗大数据实验室研究科学家
研究方向
医学影像分析，生物识别安全，计算机视觉，深度学习
电子邮箱
siqiliu@sribd.cn
教育背景
香港浸会大学 计算机科学博士
中山大学 理学学士
个人介绍
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。
主要论文：
- 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
著作（章节）：
- 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.
专利：
- PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
职务/职称
深圳市大数据研究院 医疗大数据实验室研究科学家
研究方向
医学影像分析，生物识别安全，计算机视觉，深度学习
电子邮箱
siqiliu@sribd.cn
教育背景
香港浸会大学 计算机科学博士
中山大学 理学学士
个人介绍
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。
主要论文：
- 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
著作（章节）：
- 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.
专利：
- PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
职务/职称
深圳市大数据研究院 医疗大数据实验室研究科学家
研究方向
医学影像分析，生物识别安全，计算机视觉，深度学习
电子邮箱
siqiliu@sribd.cn
教育背景
香港浸会大学 计算机科学博士
中山大学 理学学士
个人介绍
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。
主要论文：
- 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
著作（章节）：
- 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.
专利：
- PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
职务/职称
深圳市大数据研究院 医疗大数据实验室研究科学家
研究方向
医学影像分析，生物识别安全，计算机视觉，深度学习
电子邮箱
siqiliu@sribd.cn
教育背景
香港浸会大学 计算机科学博士
中山大学 理学学士
个人介绍
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。
主要论文：
- 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
著作（章节）：
- 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.
专利：
- PC. Yuen, SQ. Liu, S. Zhang, and G. Zhao, “3D Mask Face Anti-spoofing with Remote Photoplethysmography,” US Patent, 2019.
职务/职称
医疗大数据实验室 研究科学家
研究方向
数据挖掘，深度神经网络，强化学习
电子邮箱
gaoanningzhe@sribd.cn
教育背景
本科 清华大学数学系 2016
博士 加州大学伯克利数学系 2021
主要成果/荣誉
北京市优秀毕业生（2016）
个人介绍
高安凝哲博士本科毕业于清华大学数学系，博士毕业于加州大学伯克利数学系。毕业后在腾讯任高级算法研究员，现任深圳市大数据研究院研究科学家。研究方向有数据挖掘，深度学习及自然语言大模型。
代表性论文
1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020
职务/职称
医疗大数据实验室 研究科学家
研究方向
数据挖掘，深度神经网络，强化学习
电子邮箱
gaoanningzhe@sribd.cn
教育背景
本科 清华大学数学系 2016
博士 加州大学伯克利数学系 2021
主要成果/荣誉
北京市优秀毕业生（2016）
个人介绍
高安凝哲博士本科毕业于清华大学数学系，博士毕业于加州大学伯克利数学系。毕业后在腾讯任高级算法研究员，现任深圳市大数据研究院研究科学家。研究方向有数据挖掘，深度学习及自然语言大模型。
代表性论文
1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020
职务/职称
医疗大数据实验室 研究科学家
研究方向
数据挖掘，深度神经网络，强化学习
电子邮箱
gaoanningzhe@sribd.cn
教育背景
本科 清华大学数学系 2016
博士 加州大学伯克利数学系 2021
主要成果/荣誉
北京市优秀毕业生（2016）
个人介绍
高安凝哲博士本科毕业于清华大学数学系，博士毕业于加州大学伯克利数学系。毕业后在腾讯任高级算法研究员，现任深圳市大数据研究院研究科学家。研究方向有数据挖掘，深度学习及自然语言大模型。
代表性论文
1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020
职务/职称
医疗大数据实验室 研究科学家
研究方向
数据挖掘，深度神经网络，强化学习
电子邮箱
gaoanningzhe@sribd.cn
教育背景
本科 清华大学数学系 2016
博士 加州大学伯克利数学系 2021
主要成果/荣誉
北京市优秀毕业生（2016）
个人介绍
高安凝哲博士本科毕业于清华大学数学系，博士毕业于加州大学伯克利数学系。毕业后在腾讯任高级算法研究员，现任深圳市大数据研究院研究科学家。研究方向有数据挖掘，深度学习及自然语言大模型。
代表性论文
1. Anningzhe Gao, Essential dimension of moduli stack of polarized K3 surfaces , Proceedings of the American Mathematical Society, 2020
职务/职称
深圳市大数据研究院医疗大数据实验室研究科学家
研究方向
生物信息，数据挖掘，全基因组关联分析(GWAS)，基于空间转录组及多组学数据的统计模型开发
电子邮箱
xiaojiashun@sribd.cn
学历
博士，香港科技大学， 数学，2018.9-2022.8
学士，南方科技大学，生物信息学，2013.9-2017.7
工作经历
深圳市大数据研究院，研究科学家，2022.9-在职
深圳市早知道科技有限公司(WeGene), 生物信息工程师，2017.7-2018.8
代表论文
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 major revision.
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.
# co-first author
职务/职称
深圳市大数据研究院医疗大数据实验室研究科学家
研究方向
生物信息，数据挖掘，全基因组关联分析(GWAS)，基于空间转录组及多组学数据的统计模型开发
电子邮箱
xiaojiashun@sribd.cn
学历
博士，香港科技大学， 数学，2018.9-2022.8
学士，南方科技大学，生物信息学，2013.9-2017.7
工作经历
深圳市大数据研究院，研究科学家，2022.9-在职
深圳市早知道科技有限公司(WeGene), 生物信息工程师，2017.7-2018.8
代表论文
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 major revision.
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.
# co-first author
