师资队伍

黄鹂

新财经综合实验室

讲师、硕士生导师

E-maillihuang@swufe.edu.cn

办公室:柳林校区经世楼D205



n 教师简介

    黄鹂,现任西南财经大学计算机与人工智能学院(新财经综合实验室)讲师、硕士生导师。2021年毕业于电子科技大学,获得工学博士学位。黄鹂博士主要研究方向涉及机器学习、深度学习、自然语言处理、财经科技等,已在国际顶级期刊、国内外学术会议等发表十余篇,包括IEEE Transactions on Cybernetics、Neural Network and Applications、ICASSP、计算机学报等。

 

    欢迎对深度学习、自然语言处理(文本分析&文本生成)、金融科技等方向感兴趣的青年才俊报考我的研究生,我会尽快回复邮件并安排面谈。欢迎优秀本科生加入我的课题小组,目前课题小组与爱荷华州立大学、马里兰大学、代尔夫特理工大学等高校建立了长期合作关系。


n 研究领域

深度学习

自然语言处理

财经科技

n 讲授课程

  本科:操作系统、编译原理、人工智能实训、现代科技与人工智能

  硕士:人工智能概述


n 研究成果

代表性学术论文

[1]Li HuangHonemei WuGuisong Liu, Qiang Gao. “Attention Localness in Shared Encoder-Decoder Model for Text Summarization.” In 48th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). CCF -B类会议,语音信号处理国际顶会)

[2]Qiang Gao, Wei Wang, Li Huang, Xin Yang, Tianrui Li and Hamido Fujita. "Dual-grained Human Mobility Learning for Location-aware Trip Recommendation with Spatial-temporal Graph Knowledge Fusion", Information Fusion, 2023. (JCR一区Top)

[3]Xin Yang, Metoh Adler LOUA, Meijun Wu, Li Huang, and Qiang Gao. "Multi-granularity Stock Prediction with Sequential Three-way Decisions", Knowledge-Based Systems,2023. (SCI一区,财大A)

[4]Li Huang, Wenyu Chen, Youguo Liu, Shuai Hou, Hong Qu. “Summarization with Self-Aware Context Selecting Mechanism.” IEEE Transactions on Cybernetics, 2021, doi: 10.1109/TCYB.2020.3042230. 2021.JCR一区Top

[5]Li Huang, Wenyu Chen, Youguo Liu, He Zhang, Hong Qu. “Improving neural machine translation using gated state network and focal adaptive attention network.” Neural Computing & Application, 2021, Vol 33, pp. 15955–15967. (JCR二区)

[6]Li Huang, Wenyu Chen, Hong Qu. 2021. “Accelerating Transformer for Neural Machine Translation.” In 2021 13th International Conference on Machine Learning and Computing (ICMLC 2021). Association for Computing Machinery, 2021, pp. 191-197.

[7]Li Huang, Wenyu Chen, "Gated Residual Connection for Neural Machine Translation," In 16th International Computer Conference on Wavelet Active Media Technology and Information Processing, IEEE, 2019, pp. 258-261.

[8]Rubungo Andre Niyongabo, Hong Qu, Julia Kreutzer, Li Huang. “KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi.” In 28th International Conference on Computational Linguistics (COLING 2020), 2020: 5507-5521.CCF-B类会议,自然语言处理旗舰会议)

[9]Xiaomin Zhang, Li Huang, Hong Qu. “AHNN: An Attention-Based Hybrid Neural Network for Sentence Modeling.” In Natural Language Processing and Chinese Computing (NLPCC 2017), Springer, Vol 10619, pp. 731-740. CCF-C类会议)

[10]Mingsheng Fu, Hong Qu, Li Huang, Li Lu. “Bag of meta-words: A novel method to represent document for the sentiment classification.” Expert Systems with Applications, 2018, Vol 113, pp. 33-43. JCR二区, IF

[11]Li Zhou, Tingyu Wang, Hong Qu, Li Huang, Yuguo Liu. “A weighted GCN with Logical Adjacency Matrix for Relation Extraction.” In 24th European Conference on Artificial Intelligence (ECAI 2020), 2020 (325): 2314-2321. CCF-B类会议)

[12]刘贵松,郑余,解修蕊,黄鹂,丁浩伦。基于损失预测的双主动域适应算法研究。计算机学报。2023(3). (CCF-A类中文期刊)


专利

  [1]屈鸿,秦展展,侯帅,黄鹂,张晓敏。 一种引入多路选择融合机制的多标签长文本分类方法,2019-05-17,中国,ZL201910410661.4

[2]黄鹂,伍红梅,梁若暄,刘贵松,蒋太翔,殷光强。跨语际语言翻译的神经机器翻译模型构建及其翻译方法,2022-10-05,中国,202210808791.5

[3]屈鸿,黄鹂,王淼,张晓敏,刘洋军,张亦洲,程绍欢。一种基于分块机制的机器翻译方法,2018-11-06,中国,2018104893333

主要科研项目

[1]国家科学技术部,重点研发计划,2018AAA00202,神经元和模块功能特异化研究,2019.12-2023.12,在研,主研

[2]光华英才工程-青年教师成长计划项目,2022,在研,主持

[3]中央高校基本科研项目,2022020078,深度学习方法在方面级情感分析任务上的研究与应用,在研,主持

[4]西南财经大学引进人才科研启动资助项目(重点项目),移动性表征动态持续学习研究,2021-1至2021-12,已结题,主持

[5]四川省重点研发计划,2022YFG0314, 类脑智能芯片低功耗学习方法研究, 2022-1至2023-12, 在研,主研

[6]国家自然科学基金青年基金项目,61806040,具有时序迁移能力的Spiking-Transfer learning (脉冲-迁移学习)方法研究,2019-01 至 2021-12,主研,结题。