Meng Yang is an associate professor and a PhD tutor at School of Data and Computer Science at Sun Yat-Sen University, where he is part of Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education of China. He is an IEEE Senior Member, as well as a member of Top Talents of Guangdong Special Support Plan and Sun Yat-sen University Hundred Talents Program. Before that, he spent three years on the faculty of the School of Computer Science at Shenzhen University after he received his PhD from the Hong Kong Polytechnic University and his postdoc degree at ETH Zurich.

To date, he has published over 50 SCI journals or CCF class A recommended conference papers such as Int J Comput Vision, IEEE Trans.Neural Netw.Learn. Syst., IEEE Trans. Image Process and CVPR. As the first author or corresponding author, he has published more than 25 papers in Chinese Academy of Sciences Ranking Q2 journals and CCF class A recommended conferences and ECCV (one of the top-level computer vision conferences). Several of them were highly groundbreaking, and two were selected for ESI highly cited papers. His papers has been cited more than 12,700 times in Google Scholar. See the Google Scholar Profile for more details.

Kaifeng is an ancient capital of eight dynasties in China. Kaifeng

Tongxu is an ancient county town, named Xianping in Northern Song Dynasty. Tongxu

Cultural celebrities: Wang Gongchen(Number One Scholar of Song Dynasty)

Martial arts master: Chang Zhenfang,Zhang Wenguang

His laboratory focuses on the embodied intelligent understanding of vision and language, and studies theoretical algorithms and applications of machine learning and deep learning, including multi-modal perception, embodied AI, image recognition, semantic segmentation, generative adversarial networks, image translation, few-shot learning, and weakly supervised learning in computer vision. etc., as well as text classification, sentiment analysis, multi-hop Q & A, etc. in natural language processing.

Details

Postgraduate Students

Jie Ling (凌颉), 2019级

Haijian Wang (王海鉴), 2019级

Lei Liao (廖蕾), 2020级

Yu Gu (谷雨), 2020级

Siwei Su (苏思伟), 2020级

Xinzi Cao (曹心姿), 2020级

Kao Mao (毛凯), 2020级

Mao Feng (冯懋), 2021级

Chuzhao Huang (黄楚钊), 2021级

Guoying Sun (孙国英), 2021级

Jialu Liu (刘家璐), 2021级

Ni Yang (杨妮), 2021级

Song Hou (侯松), 2021级

Jibang Li (李济邦), 2021级

Undergraduate Students

Jinjie Mai (麦金杰), 2016级

Zifeng Chen (陈梓峰), 2016级

Jixian Peng (彭继贤), 2016级

Former Students

Yongjie Huang (黄永杰), 2019级

Jia Shuai (帅嘉), 2019级

Wenfeng Luo (罗文锋), 2018级

Pengfei Li (李鹏飞), 2018级

Peinqin Lin (林佩勤), 2018级

Shaomin Zheng (郑少敏), 2018级

Qin Zhong (钟琴), 2018级

Jiaming Chen (陈家铭), 2017级

Kangyin Ke (柯康银), 2017级

Weiri Liang (梁伟日), 2017级

Linbin Ye (叶林彬), 2017级

Hui Li (李辉), 2016级

Wei Wen (文伟), 2016级

Lin Chen (陈林), 2015级

Tiancheng Song (宋天成), 2013级

Multimedia, artificial intelligence, human-computer interaction related courses. Such as:

Multimedia Information Processing (Undergraduate Course)

Fundementials of Multimedia (Postgraduate Course)

Senior Member of Institute of Electrical and Electronics Engineers (IEEE)

Senior Member of China Computer Federation (CCF)

Member of Pattern Recognition Committee of China Artificial Intelligence Association

Member of 3rd Vision and Learning SEminar (VALSE) Online Organizing Committee (VOOC)

Member of American Association of Artificial Intelligence (AAAI)

Reviewers of top international journals such as IEEE TPAMI, TNNLS, TIP, TCSVT, TIFS, Pattern Recognition, Information Science, CVIU, Neurocomputing and international top conferences such as AAAI, ICML, ICCV.

教育部2017年高等学校科学研究优秀成果奖自然科学奖一等奖, 教育部, 自然科学, 省部一等奖, 2018.1.30，排名第二

2018年度第八届吴文俊人工智能科学技术奖自然科学二等奖, 中国人工智能学会, 自然科学二等奖, 2018.10.21，排名第三

2019年度ACM AI分会新星奖

2015年陕西省科学技术奖，自然科学二等奖，排名第七

L. Zhang, M. Yang( 学 生 一 作 ), and X. C. Feng, Sparse Representation or collaborative Representation: Which Helps Face Recognition? IEEE ICCV, 2011. (CCF A 类国际会议， Google 单篇引用 2456 次， Web of Science 核心集合引用 1649 次)。 国际模式识别最高奖（ KS Fu Prize） 奖励委员会主席、 英国皇家工程院院士 Josef Kittler 教授评价该工作提出了一种模式识别 new concept， 且在相似性能时展现了 much lower 计算开销。

W. Liu, Y. Wen, Z. Yu, M. Yang(通信作者), Large margin softmax loss for convolutional neural networks, ICML 2016. (CCF A 类国际会议， Google 单篇引用 1954 次， Web of Science 核心集 合引用 894 次)。 来自 Texas A&M University、 University of Florida 和上海交大学高校的知名学 者（如 Neural Networks 编委 Yoonsuck Choe），多次评价我们 ICML 论文 L-Softmax 方法为首 次(first)大间隔化深度网络 Softmax 损失。

M. Yang, L. Zhang, X.C. Feng, and D. Zhang, Sparse Representation based Fisher Discrimination Dictionary Learning for Image Classification, International Journal of Computer Vision, 109(3):209-232, 2014.（ CCF A 类国际刊物, IF=14.5， Google 单篇引用 558 次， ESI 高被引论文[2017-2025 年度]， 会议版本Google 单篇引用 1203 次）

M. Yang, L. Zhang, J. Yang and D. Zhang, Regularized Robust Coding for Face Recognition, IEEE Transactions on Image Processing, 22(5): 1753-1766, 2013. （ CCF A 类国际刊物, IF=12.1， Google 单篇引用 335 次, ESI 高被引论文[2016-2023]， 会议版本Google 单篇引用 762 次）

P.Q. Lin, M. Yang(通信作者), J.H. Lai, Deep Selective Memory Network With Selective Attention and Inter-Aspect Modeling for Aspect Level Sentiment Classification, IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 28, 1093-1106, 2021（ 中科院一区, IF=4.2, Google 单篇引用 26 次, 会议版本Google 单篇引用 60 次）。 国际 语言学会创始会士、 ACL Fellow Eduard Hovy 教授评价该工作获得 impressive performance