中国科学院大学硕士研究生导师信息：陈广勇

　　考研中一般在复试期间大家会联系硕士研究生导师，因为提前联系运气好的话，导师看到你的简历后可能对你非常感兴趣，在不违背原则的前提下没准会对你的复试指点一二。那在和导师邮件沟通的过程中如果你对导师的学术著作颇有研究或者在考研前就已经瞄准某位导师，那就很有必要对于硕士研究生导师的信息提前熟悉了解，方便以后的沟通。下面新东方在线考研频道为大家分享：“中国科学院大学硕士研究生导师信息：陈广勇”文章。

　　陈广勇 男 中国科学院深圳先进技术研究院

　　电子邮件： gy.chen@siat.ac.cn

　　通信地址： 深圳市南山区学苑大道1068号

　　邮政编码： 518048

　　研究领域机器学习理论及其应用

　　教育背景

　　学历

　　2012年，南京大学，电子科学与工程学院，本科

　　2016年，香港中文大学，计算机科学与工程系，博士

　　工作经历2020 至今: 中国科学院深圳先进技术研究院， 副研究员

　　2018 - 2020: 腾讯量子实验室，高级研究员

　　2016 - 2018: 香港中文大学，博士后研究员

　　论文发表# denotes visiting or intern students supervised by me, * denotes corresponding authors.

　　Accelerated Prediction of Cu-based Single-Atom Alloy Catalysts for CO2 Reduction by Machine Learning.

　　Dashuai Wang, Runfeng Cao, Shaogang Hao, Chen Liang, Guangyong Chen, Pengfei Chen, Yang Lie, Xiaolong Zou

　　Green Energy & Environment, JCR Q1, 2021.

　　Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning.

　　Danruo Deng, Guangyong Chen*, Jianye Hao, Qiong Wang, Pheng-Ann Heng.

　　2021 Conference on Neural Information Processing Systems (NeurIPS), CCF A, 2021.

　　Learning Regularizer for Monocular Depth Estimation with Adversarial Guidance.

　　Guibao Shen#, Yingkui Zhang, jialu Li, Mingqiang Wei, Qiong Wang*, Guangyong Chen*, Pheng-Ann Heng.

　　The 29th ACM International Conference on Multimedia (ACMMM), CCF A, 2021.

　　A Rotation-invariant Framework for Deep Point Cloud Analysis.

　　Xianzhi Li, Ruihui Li, Guangyong Chen, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng.

　　IEEE Transactions on Visualization and Computer Graphics (TVCG), JCR Q1, 2021.

　　RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions.

　　Xiaorui Wang, Yuquan Li, Jiezhong Qiu, Guangyong Chen, Huanxiang Liu, Benben Liao, Chang-Yu Hsieh, Xiaojun Yao

　　Chemical Engineering Journal, JCR Q1, 2021.

　　Hyperbolic Relational Graph Convolution Networks Plus: a Simple but Highly Efficient QSAR-modeling Method.

　　Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dongsheng Cao, Tingjun Hou

　　Briefings in Bioinformatics, JCR Q1, 2021.

　　Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.

　　Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng Cao, Jian Wu & Tingjun Hou*

　　Journal of Cheminformatics, JCR Q1, 2021.

　　Noise against noise: stochastic label noise helps combat inherent label noise.

　　Pengfei Chen#, Guangyong Chen*, Junjie Ye*, Jingwei Zhao, Pheng Ann Heng.

　　Ninth International Conference on Learning Representations (ICLR, Top Conference @ AI), Spotlight, 2021.

　　Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise.

　　Pengfei Chen#, Junjie Ye*, Guangyong Chen*, Jingwei Zhao, Pheng Ann Heng.

　　Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, CCF A), 2021.

　　Robustness of Accuracy Metric and its Inspiration in Learning with Noisy Labels.

　　Pengfei Chen#, Junjie Ye*, Guangyong Chen*, Jingwei Zhao, Pheng Ann Heng.

　　Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, CCF A), 2021.

　　Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction.

　　Hongyao Tang#, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Jianye Hao

　　Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, CCF A), 2021.

　　Q-value Path Decomposition for Deep Multiagent Reinforcement Learning.

　　Yaodong Yang#, Jianye Hao, Guangyong Chen*, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei.

　　Thirty-seventh International Conference on Machine Learning (ICML, CCF A), 2020.

　　Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning.

　　Weiwen Liu#, Feng Liu, Ruiming Tang*, Ben Liao, Guangyong Chen*, Pheng Ann Heng.

　　Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020.

　　PMD: An Optimal Transportation-Based User Distance for Recommender Systems.

　　Yitong Meng#, Xinyan Dai, Xiao Yan, James Cheng, Weiwen Liu, Jun Guo, Benben Liao, Guangyong Chen.

　　European Conference on Information Retrieval (ECIR), 2020.

　　Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels.

　　Pengfei Chen#, Benben Liao, Guangyong Chen*, Shengyu Zhang.

　　Thirty-sixth International Conference on Machine Learning (ICML, CCF A), 2019.

　　Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models.

　　Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard Zemel, Shengyu Zhang.

　　Representation Learning on Graphs and Manifolds, ICLR 2019 workshop.(Alchemy Contest)

　　Psrec: Social Recommendation with Pseudo Ratings.

　　Yitong Meng, Guangyong Chen, Jiajin Li, Shengyu Zhang.

　　Proceedings of the 12th ACM Conference on Recommender Systems (RecSys), 2018.

　　Large-Scale Bayesian Probabilistic Matrix Factorization with Memo-Free Distributed Variational Inference.

　　Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng.

　　ACM Transactions on Knowledge Discovery from Data (TKDD, JCR Q1) 12.3 (2018): 1-24.

　　Efficient and Robust Emergence of Norms through Heuristic Collective Learning.

　　Jianye Hao, Jun Sun Sun, Guangyong Chen, Zan Wang, Chao Yu, Zhong Ming.

　　ACM Transactions on Autonomous and Adaptive Systems (TAAS, CCF B) 12.4 (2017): 1-20.

　　Learning to Aggregate Ordinal Labels by Maximizing Separating Width.

　　Guangyong Chen, Shengyu Zhang, Di Lin, Hui Huang, Pheng Ann Heng.

　　Thirty-fourth International Conference on Machine Learning (ICML, CCF A) , 2017.

　　Cascaded Feature Network for Semantic Segmentation of RGB-D Images.

　　Di Lin, Guangyong Chen, Daniel Cohen-Or, Pheng-Ann Heng, Hui Huang.

　　In Proceedings of the IEEE International Conference on Computer Vision (ICCV, CCF A), 2017.

　　A Bayesian Nonparametric Approach to Dynamic Dyadic Data Prediction.

　　Fengyuan Zhu, Guangyong Chen, Pheng-Ann Heng.

　　IEEE 16th International Conference on Data Mining (ICDM, CCF B), 2016

　　Blind Image Denoising via Dependent Dirichlet Process Tree.

　　Fengyuan Zhu, Guangyong Chen *, Jianye Hao, Pheng-Ann Heng.

　　IEEE transactions on pattern analysis and machine intelligence (TPAMI, CCF A), 39.8, (2016): 1518-1531.

　　From Noise Modeling to Blind Image Denoising.

　　Fengyuan Zhu, Guangyong Chen, Pheng-Ann Heng.

　　In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR, CCF A), 2016.

　　An Efficient Statistical Method for Image Noise Level Estimation.

　　Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng.

　　In Proceedings of the IEEE International Conference on Computer Vision (ICCV, CCF A), 2015.

　　以上就是新东方在线考研频道为大家分享的文章：“中国科学院大学硕士研究生导师信息：陈广勇”。建议大家给导师发邮件题目直接写“姓名 xxx专业硕士自荐信”等，让硕士研究生导师一眼就能知道你的目的。内容主要分成两个部分：第一，要说明自己的情况。第二，要表明对老师研究方向的兴趣。