Basic Information

     Name: Badong, Chen (陈霸东)

     Birth Place: Ziyang City, Sichuan (四川资阳市)

     Hobbies: Playing Go (围棋), playing table tennis, watching movies, listening music, and so on.

    ORCID: 0000-0003-1710-3818 ; SCOPUS ID: 16177239100

   中文简介:陈霸东,西安交通大学人工智能与机器人研究所教授,博导。1997年和2003年毕业于重庆大学自动控制专业分别获学士和硕士学位,2008年毕业于清华大学计算机专业获博士学位,201010月至20129月在美国佛罗里达大学电气与计算机工程系做博士后研究。研究领域涵盖信号处理、机器学习、人工智能、认知计算、脑机接口、机器人。在国际知名期刊及会议发表学术论文300多篇,论文被引1.4万多次(H因子60)。入选斯坦福大学世界排名前2%科学家名单和Elsevier中国高被引学者榜单。出版学术专著6部,获授权国家发明专利20余件。获教育部自然科学一等奖、中国自动化学会自然科学一等奖、陕西省科学技术二等奖、吴文俊人工智能自然科学奖二等奖、IEEE汇刊TCDS杰出论文奖、中国自动化学会青年科学家奖等。入选国家级人才计划特聘教授及多项省级人才计划担任中国认知科学学会理事、IEEE汇刊TNNLS/TCDS/TCSVT编委、IEEE 面向信号处理的机器学习(MLSP)以及IEEE 认知与发展系统(CDS)技术委员会委员、MLSP2022大会共同主席,并担任国内多个学会的专业委员会委员。主持了多国家自然科学基金项目(含重点类项目3项),以及973计划课题、国家重点研发计划课题等科研项目。

       代表性学术贡献:系统的发展了熵学习理论,做出了几项奠基性工作,解决了学习机或滤波器在复杂噪声干扰下性能退化难题。该方向研究成果有: 1)解决了最大互相关熵学习的收敛性和鲁棒性分析等若干基本理论难题,数学上严格证明了最大互相关熵随机梯度和不动点迭代两种自适应算法的收敛性,并证明了其对噪声的鲁棒性,给出了大噪声干扰下最大互相关熵学习最优解的摄动范围;2)提出量化的最小误差熵准则,将原有误差熵损失函数的计算复杂度从O(N2)降为O(MN),解决了最小误差熵学习的计算瓶颈问题;3)提出多核互相关熵,建立了通用的熵损失函数模型,将多种熵学习准则纳入统一理论框架 。

Education & Working Experience

Education Background

 PhD in Computer Science and Technology, Tsinghua University, Beijing, China, June 2008

 M.S. in Control Theory and Engineering, Chongqing University, Chongqing, China, June 2003

 B.S. in Automatic Control, Chongqing University, Chongqing, China, June 1997

Working Experience

Oct., 2012 - Present:  Professor, Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China

Aug., 2017 - Nov., 2017:   Senior Research Fellow, Center of Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hongkong, China 

July, 2015 - Aug., 2015:  Visiting Research Scientist, School of Electrical and Electronics Engineering (EEE), Nanyang Technological University (NTU), Singapore 

Oct., 2010 - Sept., 2012:   Post-doctoral researcher, Department of Electrical and Computer Engineering (ECE), University of Florida, Gainesville, USA

July, 2008 - Aug., 2010:   Post-doctoral researcher, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, China

July, 2003 - July, 2004:   Software Engineer, ANYKA Software Co. Ltd., Guangzhou, China

July, 1997 - July, 2000:   Assistant Engineer, CHANGHONG Co. Ltd., Mianyang, Sichuan, China

Academic Activities

Memberships & Adjuncts:

中国自动化学会机器人智能专业委员会委员(2022-)

中国认知科学学会认知与类脑计算专委会委员(2021-)

IEEE SPS Signal Processing Theory and Methods (SPTM) Technical Committee Associate Member (2021-2023)

中国自动化学会共融机器人专业委员会委员(2020-)

中国认知科学学会理事(2019-)

中国电子学会智能无人系统分会第一届委员会委员(2018-)(PDF)

中国电科认知与智能实验室首席专家 (2018-2020)

IEEE SPS Machine Learning for Signal Processing (MLSP) Technical Committee Member (2018-2023)

中国机械工程学会机器人分会第一届委员会委员(2017-) (Certificate

中国自动化学会混合智能专业委员会委员(2017-) (Invited Talk

中国认知科学学会神经教育学分会理事(2017-) (Certificate

IEEE CIS Technical Committee on Cognitive and Developmental Systems (2017-)

中国认知科学学会认知计算与人工智能工作委员会委员(2017-)

中国自动化学会制造系统控制专业委员会委员(2016-)

中国康复技术转化及发展促进会智能康复专业委员会委员 (2016-)

“中国工程科技2035发展战略研究”信息与电子领域技术预见分析报告撰写组成员(2015)

陕西省生物医学工程学会康复医学工程专业委员会常委 (2014-)

陕西省自动化学会控制理论及应用专业委员会委员 (2014-)

中国人工智能学会脑机融合与生物机器智能专业委员会委员 (2014-)

IEEE 高级会员 (2013 - )

Editorial Activities:

Guest Editor of Special Issue "Brain-Inspired Computing under the Era of Large Model and Generative AI: Theory, Algorithms, and Applications" in Frontiers in Neuroscience (2024) 

Guest Editor of Special Issue "Information-Theoretic Methods in Deep Learning: Theory and Applications" in Entropy (2023) 

Guest Editor of Special Issue "Information Theoretic Methods for the Generalization, Robustness and Interpretability of Machine Learning" in IEEE TNNLS (2022) (CFP)

Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology (2022-2023)

Associate Editor of CAAI Transactions on Artificial Intelligence (2022-)

Associate Editor of Frontiers in Signal Processing (2021-)

Action Editor of Neural Networks (2021-2023)

Associate Editor of IET Cyber-systems and Robotics (2020-)

Associate Editor of IEEE Trans. on Cognitive and Developmental Systems (2018 -2022 )  

Guest Edior of Special Issue "Smart Healthcare: Artificial Intelligence with Applications in Biomedicine" in Journal of Ambient Intelligence and Humanized Computing(2017) (CFP)

Guest Edior of Special Issue "Neural Information Engineering" in Engineering (2017)

Guest Editor of Special Issue "Entropy in Signal Analysis" in Entropy (2016)

Associate Editor of Journal of The Franklin Institute (2015-2020)

Guest Editor of Special Issue "Information Theoretic Learning" in Entropy (2015)

Editorial Board of Entropy (2014 - )    (Certificate)

Associate Editor of IEEE Trans. on Neural Networks and Learning Systems (2013 -2019 )   (Certificate)

Conference Activities:

Workshop Organizer, the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, February 22-March 1, 2022, Vancouver, BC, Canada.

General Co-Chair, IEEE International Workshop on Machine Learning for Signal Processing (MLSP2022), August 22-25, 2022, Xi'an, China. (CFP)

Program Committee Member, the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022),August 1-5, 2022, Eindhoven, Netherlands.

Area Chair, the CAAI International Conference on Artificial Intelligence (CICAI 2021), May 29-30, 2021, Hangzhou, China.

Senior Program Committee Member, the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), August 21-26, 2021, Montreal, Canada.

Program Committee MemberIJCNN 2021, Virtual Event, July18-22, 2021.

Program Committee Member, the 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021),online on July 27-30, 2021.

Senior Program Committee Member,  the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI), July 11-17, 2020, Yokohama, Japan.

Program Chair, the 10th International Conference on Extreme Learning Machines (ELM2019), December 14-16, 2019, Yangzhou, China.

PC Member and Session Chair, the 3rd International Symposium on Image Computing and Digital Medicine (ISICDM2019), Aug 24-26, 2019, Xi'an, China.

Special Session Chair, the 2nd International Conference on Electronic Information and Communication Technology (ICEICT 2019), Jan. 21, 2019, Harbin, China.

Senior Program Committee Member,  the 28th International Joint Conference on Artificial Intelligence (IJCAI-2019), Macao, China.

2018年中国自动化大会(CAC2018)专题论坛25共同主席:我们的2030——青年科技工作者的责任与使命,中国. 西安.

论坛一(认知计算的基础理论)共同主席,第一届中国认知计算与混合智能学术大会(CCHI2018),中国. 西安.

Program Committee Member, IEEE International Workshop on Machine Learning for Signal Processing (MLSP2018), Aalborg, Denmark.

Program Committee Member, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018, New Orleans, Lousiana, USA.

Special Session Organizer, IJCNN 2018, Vancouver, Rio de Janeiro, Brazil, 2018.

Program Committee Member, IEEE International Workshop on Machine Learning for Signal Processing (MLSP2017), Tokyo, Japan.

Associate Editor, 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), Daegu, Korea, 2017.

Program Committee Member, 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, California, USA.

Member of the Program Committee, The 2016 IEEE Symposium on Neuromorphic Systems and Cyborg Intelligence (SNCI'16), Athens, Greece, 2016.

Member of the Program Committee, The 7th Chinese Conference on Pattern Recognition, CCPR 2016, Chengdu, China.

Co-Chair of the Invited Session on "Recent Advances on Adaptive Filtering and Its Applications", the 35th Chinese Control Conference(CCC), Chengdu, China, 2016.

Special Session Organizer, IJCNN 2016, Vancouver, Canada, 2016.

Session Chair, 8th International Conference on Knowledge Science, Engineering and Management (KSEM2015), Chongqing, China.

Technical Program Co-Chair, International Workshop on Vision, Communications and Circuits, Keio University, Japan, 2015 (PDF)

Scientific Advisory Committee, The 2nd International Electronic Conference on Entropy and Its Applications, 15-30, November, 2015.

Special Session Organizer, 2015 IEEE International Conference on Digital Signal Processing (DSP 2015), Singapore.        

Member of the Program Committee, Workshop on Graph-based Representations in Pattern Recognition (GbR2015), Beijing, China, 2015.  

Member of the Program Committee, IJCNN 2014, Beijing, China, 2014. 

Publicity Chair,  The Brain-Mind Workshop (BMW) , Beijing, China, 2013.

Invited Talks

  • "Information Theoretic Learning", 2023年2月18日,Keynote Speaker at ICDSP 2023 & ICCGV 2023,四川.成都

  • “基于功能磁共振成像的重性抑郁症脑动态特性与诊断模型”,2022年3月5日,“丝路医工精英论坛”暨西安交大第十二届医工协同科技创新学术年会,陕西.西安

  • 熵学习理论及在脑机接口中的应用”,2021年12月19日,第五届图像计算与数字医学国际研讨会(ISICDM2021),广西.桂林

  • 基于熵方法的机器学习:理论、算法与应用”,2021年7月25日,2021中国光谷人工智能大会暨企业家高峰论坛,湖北. 武汉

  • “熵学习理论的新进展”,2021年5月29日,第36届中国自动化学会青年学术年会(YAC2021),江西. 南昌

  • “核熵学习理论与方法2020年11月27日,第三届AI西湖前沿论坛 —5G下的智能控制与智能信息处理,浙江.杭州

  • 基于fMRI的视觉认知编解码2020年8月8日,云南省神经科学学会第二届学术年会会议,云南.昆明

  • Brain Visual Cognitive Decoding”,2019年12月14日,一带一路2019国际脑科学学术峰会,陕西.西安

  • 基于fMRI的视觉认知编解码”,Invited talk at the 3rd International Symposium on Image Computing and Digital Medicine (ISICDM2019), Aug 24-26, 2019, Xi'an, China

  • "Information Theoretic Learning", Keynote Presenter at 2019 2nd International Conference on Electronic Information and Communication Technology (ICEICT 2019), Jan. 21, 2019, Harbin, China (PDF)

  • Information Theoretic Learning”,2018年12月1日,中国自动化大会(CAC2018)“计算感知与模式识别”专题论坛,西安

  • 基于信息论方法的鲁棒估计与机器学习”,2018年10月19日,无人车定位与跟踪关键技术研讨会,北京

  • 信息理论学习”,2018年10月14日,第二届图像计算与数字医学国际研讨会(ISICDM)暨智能医学信息处理论坛,四川. 成都

  • 信息论学习与脑信号分析”,2018年9月8日,混合增强智能前沿讲习班,西安交通大学,西安

  • 核自适应滤波与宽度学习”,2018年5月31日,智能自动化学科前沿讲习班,中科院自动化研究所,北京 (PDF)

  • Neural Decoding from fMRI”,2018年5月19日,第33届中国自动化学会青年学术年会(YAC 2018),江苏.南京

  • 信息论学习与脑信号分析与处理”,2018年4月13日,2018国家机器人发展论坛共融机器人专论坛,浙江.绍兴 (PDF)

  • Neural Decoding from fMRI”, invited speech at Inernational Symposium on Computational and Cyborg Intelligence & IEEE CIS Winter School, Nov.14, 2017, Hangzhou, China  

  • Information Theoretic Learning”, November 13, 2017, Southwest University, Chongqing, China

  • Neural Encoding and Decoding from the fMRI Responses”, 2017年11月12日,CCFYOCSEF 重庆生物信息与健康交叉专题技术论坛(特邀讲者),重庆邮电大学,重庆  (PDF)

  • Information Theoretic Learning”, Keynote at 2017 6th International Conference on Computer Science and Network Technology (ICCSNT 2017), Oct. 21, 2017, Dalian, China (PDF

  • Information Theoretic Learning with Applications to EEG Analysis”, 2017年10月15日,2017天津脑-机媒体研讨会, 天津大学

  • Correntropic Measures Based Robust and Sparsity-aware Learning”, invited talk at the 10th International Conference on Intelligent Robotics and Applications (ICIRA 2017),  August 17, 2017, Wuhan, China

  • Information Theoretic Learning”, August 16, 2017, Huazhong University of Science and Technology, Wuhan, China

  • Information Theoretic Learning”, 2017年8月1日,中国自动化学会混合智能专业委员会成立大会暨混合增强智能学术沙龙,中国.西安

  • "Correntropy for Robust and Sparsity-aware Learning ", June 21, 2017, Beijing Institute of Technology, Beijing, China

  • "Correntropy for Robust and Sparsity-aware Learning ", June 20, 2017, Hangzhou Dianzi University, Hangzhou, China

  • 混合-增强智能(Hybrid-Augmented Intelligence)”,2017年4月6日,人工智能应用研讨会,国防科技大学,长沙

  • 核自适应滤波与神经信息解码”,2017年4月2日,2017国家机器人发展论坛,中国.山东.日照

  • 基于核自适应滤波的神经信息解码”,2016年12月8日,“机器人与智能系统”论坛,中国科学院深圳先进技术研究院,深圳

  • Kernel Adaptive Filtering with Application to Neural Decoding”,2016年12月4日,脑科学与信息科学交叉前沿论坛,西北工业大学

  • 基于fMRI的视觉认知'读脑术'”,2016年分子与神经影像教育部工程中心学术年会,西安电子科技大学

  • "Statistical Similarity Measures in Kernel Space", October 18, 2016, North China Electric Power University, Beijing, China

  • 脑机共融的康复机器人”,2016年10月15日,2016年“一带一路”健康管理与康复科学工程研讨会,西安交通大学(PDF

  • 数据驱动的'读脑术'”,2016年10月14日,“大数据的类脑计算与深度学习”国际研讨会,西安电子科技大学

  • "Nonlinear Statistical Similarity Measures in Kernel Space", July 6, 2016, IEEE CIS Summer School, Chengdu, China

  • "Local Similarity Measures for Robust and Sparsity-aware Learning ", June 2, 2016, Nanjing University of Posts and Telecommunications, Nanjing, China

  • "Robust Learning with Similarity Measures in Kernel Space", May 30, 2016, University of Science and Technology Beijing, Beijing, China

  • "Visual-cognitive Coding and Decoding Based on fMRI and its Application Prospect in Advanced Robot Systems",May 14,2016, Invited Speaker at 2016 International Forum on Core Component and Key Technology for Robot, Xi'an, China

  • "Correntropic Losses for Robust and Sparsity-aware Learning", April 25, 2016, Invited Talk at International Workshop on Computer Vision and Signal Processing (CVSP'16), Xi'an Jiaotong University, Xi'an, China

  • 基于fMRI的视觉认知编解码”,2016年4月13日,2016国家机器人发展论坛,中国.重庆.永川

  • "Online Kernel Learning for Neural Decoding", Nov. 24, 2015, Southwest University, Chongqing, China

  • "Similarity Measures in Kernel Space with Applications to Robust Signal Processing and Machine Learning", Nov. 3, 2015, Invited Speaker at TENCON 2015, Macau, China (Invitation Letter, Abstract, Certificate)

  • "Robust and Sparsity-Aware Similarity Measures in Kernel Space", Nov. 2, 2015, Yukawa Laboratory, Keio University, Japan

  • "Kernel Adaptive Filtering with Applications to Neural Decoding", Aug. 14, 2015, School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore (Seminar Announcement)

  • "Similarity Measures in Kernel Space", Dec. 10, 2014, School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore 

  •  "Brain Cognitive Function Decoding and Modelling", July 31, 2014, Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China

  •  "Some Recent Advances in Kernel Adaptive Filtering", July 25, 2013, Lab of Prof. X. Rong Li, Xi'an Jiaotong University, Xi'an, China

  •  "Quantifying Cognitive States of the Human Brain Using Measures of Dependence", Summer School on Intelligent Vehicle, July 8-12, 2013, Xi'an Jiaotong University, Xi'an, China

  • "Perception Action Cycle Learning", Symposium on Cognitive Science, April 22-23, 2013, Xi'an Jiaotong University, Xi'an, China

  • "Information Theoretic Learning and Kernel Adaptive Filtering", March 9, 2013, Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China

  • "Kernel Adaptive Filtering", October 20, 2012, Tsinghua University, Beijing, China

Patents

  • 陈霸东,李炳辉,谢宇清,任鹏举,郑南宁,一种高效的基于快速随机扩展树的路径规划方法,发明专利,申请号:2021102186274,授权公告号:CN112947459B

  • Pengju Ren, Long Fan, Boran Zhao, Pengchen Zong, Wenzhe Zhao, Fei Chen, Badong Chen, Nanning Zheng, Parallel Computing System, US Patent US20200120154A1,  Apr. 16, 2020. 

  • Pengju Ren, Xiaogang Wu, Hongwei Bi, Hang Wang, Hongbin Sun, Badong Chen, Nanning Zheng, Parallel scaling engine for multi-view 3DTV display and method thereof, US Patent US9924153B2, Mar. 20, 2018. 

  • 陈霸东,秦雪梅,任鹏举,袁泽剑,郑南宁,基于功率谱密度和互相关熵谱密度融合的特征提取方法,发明专利,申请号:2019102088518,授权公告号:CN110059564B

  • 陈霸东,杜少毅,许光林,高跃,崔迪潇,万腾,一种基于互相关熵配准的无人车定位融合方法,发明专利,申请号:2018105700357,授权公告号: CN109001789B

  • 陈霸东,张倩,杨启航,李炳辉,张璇,郑南宁,一种增强现实设备与移动机器人的配准方法,发明专利,申请号:2019112525431,授权公告号: CN111179341B

  • 杜少毅,许光林,高跃,崔迪潇,陈霸东,万腾,基于点到面距离和互相关熵配准的无人车位姿估计方法,发明专利,申请号:2018105700465,授权公告号: CN108868268B

  • 任鹏举,樊珑,赵博然,宗鹏陈,赵文哲,陈飞,陈霸东,郑南宁,一种并行计算的系统,发明专利,申请号:2018111777712,授权公告号: CN109445752B

  • 陈霸东,杨启航,李炳辉,张倩,秦雪梅,张璇,郑南宁,一种基于增强现实和多模态生物信号的轮椅机器人系统,发明专利,申请号:2019112536525,授权公告号: CN111134974B

  • 陈霸东,董继尧,郑南宁,一种基于互相关熵的共用空间模式空域特征提取方法,发明专利,申请号:2017105264669,授权公告号: CN107368849B

  • 任鹏举;吴晓刚,毕宏伟,孙宏滨,陈霸东,郑南宁,一种兼容不同分辨率和宽长比的多视频缩放模块及并行工作方法,发明专利,申请号:2017103320081,授权公告号:CN107147890B

  • 邵景莅,陈霸东,荣涛,黄大维,蒋伟平,一种故障电弧检测方法及检测装置,发明专利,申请号:2016104652380,授权公告号: CN105954628 B

  • 张雪涛,杨奔,陈霸东,姜沛林,王飞,一种基于量化最小残差熵准则的人眼注视点估计方法,发明专利,申请号:2018106632728,授权公告号: CN108960106B

  • 陈霸东; 王佳宜,吴昊,郑南宁,一种基于隐状态模型的fMRI自然图像解码方法,发明专利,申请号:201710318480X授权公告号: CN107248180B

  • 张雪涛; 李中常,王飞,陈霸东,王颖,姜沛林,郑南宁,一种基于相关熵的注视点估计方法,发明专利,申请号:2017102404747,授权公告号: CN107103293B

  • 李长军; 荣海军,董继尧,陈霸东,黄辉,基于运动想象脑-机接口的无人机虚拟控制方法及系统,发明专利,申请号:2017101711038,授权公告号: CN106959753B

  • 陈霸东,邢磊,郑南宁,基于最大混合互相关熵准则的自适应滤波方法,发明专利,申请号:2016101716963,授权公告号: CN105871356B

  • 陈霸东,肖建锋,郑南宁,一种插件式物流数据开放平台构建方法,发明专利,申请号:201510924957X,授权公告号: CN105404995B

  • 陈霸东,肖建锋,郑南宁,一种基于NFS的云存储网关系统的实现方法,发明专利,申请号:2015109244951,授权公告号: CN105407044B

  • 陈霸东,肖建锋,郑南宁,一种基于最小误差熵的凸组合自适应滤波器设计方法,发明专利,申请号:201510761007X,授权公告号: CN105306010B

  • 陈霸东,董继尧,李元昊,郑南宁,基于量化最小误差熵的共用空间模式空域特征提取方法,发明专利,申请号:2017113950858,授权公告号: CN107977651B

  • 陈霸东,陈涛,袁泽剑,郑南宁,基于立体视觉的智能车辆可行驶区域探测方法,发明专利,申请号:2018109102899,授权公告号: CN109241855B

Honors and awards

  1. 2022年教育部自然科学一等奖(3/6)

  2. 2022年中国物流与采购联合会科技进步二等奖(3/9)

  3. 2020年吴文俊人工智能自然科学二等奖(2/2)

  4. 2019年陕西省第十四届自然科学优秀论文二等奖(1/5)

  5. 2019年中国自动化学会自然科学一等奖(1/3)

  6. 2018年中国自动化学会自然科学二等奖(2/3)

  7. 2018年陕西省科学技术奖励二等奖(1/5)

  8. 2018年中国自动化学会第四届“青年科学家奖”

  9. 2018年陕西省高等学校科学技术奖励一等奖(1/5)