邓岳
职称\职位:教授/博导
电子邮箱：ydeng@buaa.edu.cn
办公地点：沙河主楼D508

基本情况

近年来，围绕航天智能、医疗智能及金融智能，以第一/通讯作者身份在Nature Methods及IEEE Transactions等刊物发表论文30余篇，其中影响因子高于10的期刊论文8篇，并在Springer出版人工智能英文专著一部。曾获得IEEE Transactions on Fuzzy Systems 2020年度最佳论文奖（第一作者），Microsoft Research Fellow，中国自动化学会、中国人工智能学会优秀博士论文奖 担任AAAI、IJCAI及ICCV等多个人工智能会议的程序委员，入选国家高层次人才引进计划（青年项目）优先资助。

研究方向

人工智能与交叉领域研究

研究成果

代表性论文
(仅列出第一与通讯作者文章)
[1] Yue Deng, Feng Bao, Steven Altschuler, Lani Wu: Scalable Analysis of Cell-type Composition from Single-cell Transcriptomics using Deep Recurrent Learning, Nature Methods, 16(4).March 2019 (影响因子:28.467)
[2] Yue Deng, Zhiquan Ren, Youyong Kong, Feng Bao, Qionghai Dai. A Hierarchical Fused Fuzzy Deep Neural Network for Data Classification. IEEE Trans. on Fuzzy Systems. 25(4), 1006-1012 (2017) (IEEE Transactions on Fuzzy Systems 2020最佳论文奖)
[3] Yue Deng, Qionghai Dai, Risheng Liu, Zengke Zhang, Sanqing Hu Low-Rank Structure Learning via Nonconvex Heuristic Recovery. IEEE Trans. on Neural Netw. Learning Systems 24(3): 383-396 (2013) (IEEE智能计算学会亮点论文，并被科技日报报道)
[4] Yue Deng, Feng Bao, Zhiquan Ren, Youyong Kong, Qionghai Dai. Deep Direct Reinforcement Learning for Financial Signal Representation and Trading. IEEE Trans. on Neural Networks and Learning Systems. 28(3):653-664 (2017). (两年来阅读量11000次, IEEE TNNLS热点论文前五)
[5] Yue Deng, Feng Bao, Mulong Du, Meilin Wang, Qionghai Dai: Information transduction capacity reduces the uncertainties in annotation-free isoform discovery and quantification. Nucleic acids research, 45(15), e143-e143 (2017).
[6] Yue Deng, Feng Bao, Mulong Du, Zhiquan Ren, Qingzhao Zhang, Yanyu Zhao, Jinli Suo, Zhengdong Zhang, Meilin Wang, and Qionghai Dai. Probabilistic natural mapping of gene-level tests for genome-wide association studies. Briefings in bioinformatics 19(4) 545-553 (2017).
[7] Yue Deng, Youyong Kong, Feng Bao, and Qionghai Dai: Sparse coding-inspired optimal trading system for HFT industry. IEEE Trans. on Industrial Informatics 11(2), 467-475 (2015).
[8] Yue Deng, Feng Bao, Xuesong Deng, Ruiping Wang, Youyong Kong and Qionghai Dai:
Deep and Structured Robust Information Theoretic Learning for Image Analysis. IEEE Transactions on Image Processing 25(9): 4209-4221 (2016)
[9] Yue Deng, Yipeng Li, Yanjun Qian, Xiangyang Ji, Qionghai Dai: Visual Words Assignment via Information-Theoretic Manifold Embedding. IEEE Trans. on Cybernetics 44(10): 1924-1937 (2014)
[10] Yue Deng, Yanyu Zhao, Zhiquan Ren, Youyong Kong, Feng Bao and Qionghai Dai. Discriminant Kernel Assignment for Image Coding. IEEETrans. on Cybernetics. 47(6), 1434-1445 (2017)
[11] Yue Deng, Yebin Liu, Qionghai Dai, Zengke Zhang, Yao Wang: Noisy Depth Maps Fusion for Multiview Stereo via Matrix Completion. IEEE Journal of Selected Topics in Signal Processing 6(5): 566-582 (2012)
[12] Yue Deng, Qionghai Dai, Zengke Zhang: Graph Laplace for Occluded Face Completion and Recognition. IEEE Trans. on Image Processing 20(8): 2329-2338 (2011)
[13] Yue Deng, Steven Altschuler, Lani Wu: PHOCOS: Inferring Multi-Feature Phenotypic Crosstalk Networks. Bioinformatics. 2016 Jun 15; 32(12):i44-i51.
[14] Yue Deng, Yilin Shen, Hongxia Jin: Adversarial Active Learning for Sequence Labeling and Generation. International Joint Conferences on Artificial Intelligence, 2018
[15] Yue Deng, Yilin Shen, Hongxia Jin: Disguise Neural Networks for Click-through Rate Prediction. International Joint Conferences on Artificial Intelligence 2017
[16] Yue Deng, Yilin Shen, Hongxia Jin: Learning Assistance from An Adversarial Critic for Multi-output Prediction, International Joint Conferences on Artificial Intelligence 2019
[17] Tian Tan, Feng Bao, Yue Deng, Alex Jin, and Qionghai Dai: Cooperative Deep Reinforcement Learning for Large-Scale Traffic Grid Signal Control. IEEE Trans. on Cybernetics (2019).
[18] Feng Bao, Yue Deng, Zhiquan Ren, Youyong Kong, Qionghai Dai: Learning Deep Landmarks for Imabalced Data Classification. IEEE Trans. on Neural Networks and Learning Systems (2019)