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黄俊

2025-02-25 浏览次数:

姓名

黄俊

性别


导师

情况

博导

学历

博士

职称

副教授

职务

副院长

邮编

243032

办公地点

逸夫楼309

电子邮箱

huangjun.cs@ahut.edu.cn

黄俊,副教授,博士生/硕士生导师,计算机科学与技术学院副院长(主持工作)。2017年博士毕业于中国科学院大学,2019.9-2020.10在东京大学从事博士后研究,现担任安徽省人工智能学会常务理事、安徽省计算机学会理事、安徽省计算机学会青工委副主任、CCF多媒体专委会执委。担任Intelligent Data Analysis期刊编委,多个重要国际期刊的审稿人和国际会议的程序委员会成员。

作为项目负责人承担了国家自然科学基金青年基金、CCF-蚂蚁科研基金、安徽省高校协同创新项目、安徽省教育厅优秀青年人才支持计划重点项目、安徽省教育厅高校重点项目等。近年来,发表学术论文30余篇,其中以第一或通讯作者发表CCF A/B类国际期刊和会议论文9篇。获“2017年度中国科学院院长优秀奖”、“2018年度中国科学院百篇优秀博士论文奖”、“2019年度安徽省科技进步奖三等奖”、“2021年度ACM中国新星奖(合肥分会)”、“2023年度安徽省科技进步奖三等奖”。

主要从事人工智能相关技术及应用研究。欢迎感兴趣同学积极报考!


[1] 国家自然科学基金青年项目,基于类属特征学习的鲁棒高效多标记学习方法研究,28万,主持,结题

[2] 安徽省高校协同创新项目,多模态内窥镜成像数据的多元属性获取与知识推理,100万,主持,在研

[3] CCF-蚂蚁科研基金,基于半监督学习的多源数据融合智能运维算法研究,25万,主持,结题

[1] Jun Huang, Guorong Li, Qingming Huang, Xindong Wu, Learning label Specific Features and Dependent Class Labels for Multi-Label Classification, IEEE Transactions on Knowledge and Data Engineering, 28(12):3309-3323, 2016. (CCF A)

[2] Jun Huang, Yang Yang, Hang Yu, Jianguo Li, Xiao Zheng, Twin Graph-based Anomaly Detection via Attentive Multi-Modal Learning for Microservice System, Proceeding of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), pp.66-78, 2023. (CCF A)

[3] Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi, Discovering Latent Class Labels for Multi-Label Learning, Proceedings of the International Joint Conference on Artificial Intelligence-Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI), pp. 3058-3064, 2020. (CCF A)

[4] Jun Huang, Linchuan Xu, Kun Qian, Jing Wang, Kenji Yamanishi, Multi-Label Learning with Missing and Completely Unobserved Labels, Data Mining and Knowledge Discovery, 35:1061-1086, 2021. (CCF B)

[5] Jun Huang, Feng Qin, Xiao Zheng, Zekai Cheng, Zhixiang Yuan, Weigang Zhang,  Qingming Huang, Improving Multi-Label Classification with Missing Labels by Learning Label-Specific Features, Information Sciences, 492:124-146, 2019. (CCF B)

[6] Jun Huang, Guorong Li, Qingming Huang, Xindong Wu, Joint Feature Selection and Classification for Multi-Label Learning, IEEE Transactions on Cybernetics, 48(3):876-889, 2018. (CCF B)

[7] Jun Huang, Guorong Li, Qingming Huang, Xindong Wu, Learning label Specific Features for Multi-Label Classification, Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 181–190, 2015. (CCF B)

[8] Jun Huang, Guorong Li, Shuhui Wang, Weigang Zhang, Qingming Huang, Group sensitive Classifier Chains for multi-label classification, Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, 2015. (CCF B)

[9] Jun Huang, Guorong Li, Shuhui Wang, Zhe Xue, Qingming Huang, Multi-label Classification by Exploiting Local Positive and Negative Pairwise Label Correlation, Neurocomputing, 257:164-174, 2017.

[10] Lei Feng*, Jun Huang*, Senlin Shu, Bo An, Regularized Matrix Factorization for Multilabel Learning With Missing Labels, IEEE Transactions on Cybernetics, 52(5):3710-3721, 2022. (CCF B)