当前位置: X-MOL首页全球导师 国内导师 › 钱昆

个人简介

钱昆,北京理工大学教授、博士生导师,2021年入选“国家高层次人才计划(青年项目)”、北京理工大学“特立青年学者”支持计划。博士毕业于德国慕尼黑工业大学,师从情感计算与计算机听觉领域顶级专家Björn W. Schuller(博雅恩)教授。2018年至2021年于日本东京大学从事人工智能医学相关领域研究工作,期间入选全球著名青年科学家基金——“日本学术振兴会外国人特别研究员”项目(成功率:10.6%),目前共发表论文120余篇(第一作者/通讯作者80篇),SCI收录期刊论文41篇,包括IEEE Signal Processing Magazine、IEEE IoTJ、IEEE T-ITS、IEEE J-BHI、IEEE T-ASE、IEEE T-BME、ABME、JASA等领域内国际顶级期刊,累计IF-2022:258.0,单篇最大IF-2022:14.9(唯一第一作者),谷歌学术引用量超过2100次,谷歌学术h指数为27。钱博士现为IEEE高级会员,IEEE Transactions on Affective Computing(JCR Q1,IF-2022: 11.2)、Frontiers in Digital Health、BIO Integration等期刊编委,法国巴黎丝路商学院客座教授,中国留德学者计算机学会人工智能与大数据专家委员会专家委员,长期担任数十种领域内顶尖/权威期刊与国际会议审稿人。钱博士与世界顶尖高校如英国帝国理工学院、德国慕尼黑工业大学、日本东京大学等保持深入良好的合作关系,可以推荐团队优秀学者/学生进行学术访问与联合培养,欢迎有志向、爱探索、肯钻研的本科、硕士、博士(后)同学主动联系。 教育培训经历 2014年10月至2018年11月,德国慕尼黑工业大学,工学博士,电气工程与信息技术专业 2011年09月至2014年04月,南京理工大学,工学硕士,信号与信息处理专业 2007年09月至2011年06月,四川师范大学,工学学士,电子信息工程专业 工作经历 2021年08月至今,北京理工大学,教授、博导,脑健康工程责任教授 2019年09月至2021年07月,日本东京大学,日本学术振兴会外国人特别研究员 2018年11月至2019年09月,日本东京大学,特任研究员 2018年01月至2018年03月,美国卡内基梅隆大学,访问学者 2016年04月至2016年11月,日本东京工业大学,访问学者 2013年11月至2014年03月,新加坡南洋理工大学,访问学者 所获奖励/荣誉 2023年07月,中国发明协会“中医防治慢性疾病的精准诊疗与循证评价体系的建立与应用”,一等奖(排名第2) 2021年03月,Frontiers in Digital Health期刊“期刊大使奖” 2020年11月,之江国际青年人才基金“优秀成果奖”(智能感知组排名第一) 2019年12月,日本学术振兴会外国人特别研究员

研究领域

计算机听觉、情感计算、人工智能医学、智能信号与信息处理、脑科学

近期论文

查看导师新发文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Selected Publications *: Corresponding Author, #: Co-First Author. Kun Qian*, Zixing Zhang, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “Artificial Intelligence Internet of Things for the Elderly: From Assisted Living to Health-Care Monitoring”, IEEE Signal Processing Magazine (IF-2022: 14.9), vol.38, no.4, pp.78-88, 2021. Kun Qian*#, Maximilian Schmitt#, Huaiyuan Zheng*#, Tomoya Koike#, Jing Han, Juan Liu*, Wei Ji*, Junjun Duan, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Zixing Zhang, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “Computer Audition for Fighting the SARS-CoV-2 Corona Crisis — Introducing the Multi-task Speech Corpus for COVID-19”, IEEE Internet of Things Journal (IF-2022: 10.6), vol.8, no.21, pp.16035-16046, 2021. Kun Qian*, Tomoya Koike, Kazuhiro Yoshiuchi, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “Can Appliances Understand the Behaviour of Elderly via Machine Learning? A Feasibility Study”, IEEE Internet of Things Journal (IF-2022: 10.6), vol.8, no.10, pp.8343-8355, 2021. Zixing Zhang, Ding Liu, Jing Han, Kun Qian*, and Bj?rn W. Schuller, “Learning Audio Sequence Representations for Acoustic Event Classification”, Expert Systems with Applications (IF-2022: 8.5), vol.178, no.115007, pp.1-11, 2021. Kun Qian*#, Tomoya Koike#, Toru Nakamura, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “Learning Multimodal Representations for Drowsiness Detection”, IEEE Transactions on Intelligent Transportation Systems (IF-2022: 8.5), vol.23, no.8, pp.11539-11548, 2022. Fengquan Dong#, Kun Qian*#, Zhao Ren*, Alice Baird, Xinjian Li, Zhenyu Dai, Bo Dong, Florian Metze, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “Machine Listening for Heart Status Monitoring: Introducing and Benchmarking HSS–the Heart Sounds Shenzhen Corpus”, IEEE Journal of Biomedical and Health Informatics (IF-2022: 7.7), vol.24, no.7, pp.2082-2092, 2020. Kun Qian*, Christoph Janott, Maximilian Schmitt, Zixing Zhang, Clemens Heiser, Werner Hemmert, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “Can Machine Learning Assist Locating the Excitation of Snore Sound? A Review”, IEEE Journal of Biomedical and Health Informatics (IF-2022: 7.7), vol.25, no.4, pp.1233-1246, 2021. Liang Zhang*#, Kun Qian#, Jun Huang, Mao Liu, and Yasushi Shibuta, “Molecular Dynamics Simulation and Machine Learning of Mechanical Response in Non-equiatomic FeCrNiCoMn High Entropy Alloy”, Journal of Materials Research and Technology (IF-2022: 6.4), vol.13, pp.2043-2054, 2021. Zengjie Zhang, Kun Qian*, Bj?rn W. Schuller, and Dirk Wollherr, “An Online Robot Collision Detection and Identification Scheme by Supervised Learning and Bayesian Decision Theory”, IEEE Transactions on Automation Science and Engineering (IF-2022: 5.6), vol.18, no.3, pp.1144-1156, 2021. Lixian Zhu, Wanyong Qiu, Yu Ma, Fuze Tian, Mengkai Sun, Zhihua Wang, Kun Qian*, Bin Hu*, Yoshiharu Yamamoto, Bj?rn W. Schuller, “LEPCNet: A lightweight End-to-End PCG Classification Neural Network Model for Wearable Devices”, IEEE Transactions on Instrumentation & Measurement (IF-2022: 5.6), pp.1-12, in press, 2023. EI Journal paper Selected Publications *: Corresponding Author, #: Co-First Author. Yongzi Yu, Wanyong Qiu, Chen Quan, Kun Qian*, Zhihua Wang, Yu Ma, Bin Hu*, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “Federated Intelligent Terminals Facilitate Stuttering Monitoring”,in Proceedings of ICASSP, in press, pp.1-5, Rhodes Island, Greek, June 2023. Meishu Song, Andreas Triantafyllopoulos, Zijiang Yang, Hiroki Takeuchi, Toru Nakamura, Akifumi Kishi, Tetsuro Ishizawa, Kazuhiro Yoshiuchi, Xin Jing, Zhonghao Zhao, Vincent Karas, Kun Qian*, Bin Hu, Bj?rn W. Schuller, and Yoshiharu Yamamoto*, “Daily Mental Health Monitoring From Speech: A Real-World Japanese Dataset and Multitask Learning Analysis”, in Proceedings of ICASSP, in press, pp.1-5, Rhodes Island, Greek, June 2023. Kun Qian*, Tanja Schultz, and Bj?rn W. Schuller, “An Overview of the First ICASSP Special Session on Computer Audition for Healthcare”, in Proceedings of ICASSP, pp. 9002-9006, Singapore, May 2022. Shuai Yu, Yiwei Ding, Kun Qian*, Bin Hu*, Wei Li, Bj?rn W. Schuller, “A Glance-and-Gaze Network for Respiratory Sound Classification”, in Proceedings of ICASSP, pp. 9007-9011, Singapore, May 2022. Wanyong Qiu, Kun Qian*, Zhihua Wang, Yi Chang, Zhihao Bao, Bin Hu*, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “A Federated Learning Paradigm for Heart Sound Classification”, in Proceedings of EMBC, pp. 1045-1048, Glasgow, Scotland, UK, July 2022. Lixian Zhu, Kun Qian*, Zhihua Wang, Bin Hu*, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “Heart Sound Classification based on Residual Shrinkage Networks”, in Proceedings of EMBC, pp. 4469-4472, Glasgow, Scotland, UK, July 2022. Kun Qian*, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “Recent Advances in Computer Audition for Diagnosing COVID-19: An Overview”, in Proceedings of LifeTech, pp. 185-186, Nara, Japan, March 2021. Jing Han, Kun Qian*, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Juan Liu*, Huaiyuan Zheng*, Wei Ji*, Tomoya Koike, Xiao Li, Zixing Zhang, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety”, in Proceedings of INTERSPEECH, pp. 4946-4950, Shanghai, China, October 2020. Tomoya Koike, Kun Qian*, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “Learning Higher Representations from pre-trained Deep Models with Data Augmentation for the ComParE 2020 Challenge Mask Task”, in Proceedings of INTERSPEECH, pp. 2047-2051, Shanghai, China, October 2020. Tomoya Koike, Kun Qian*, Qiuqiang Kong, Mark D. Plumbley, Bj?rn W. Schuller, and Yoshiharu Yamamoto, “Audio for Audio is Better? An Investigation on Transfer Learning Models for Heart Sound Classification”, in Proceedings of EMBC, pp. 74-77, Montréal, Canada, July 2020. 中文论文 钱昆,董逢泉,任昭,戴振宇,董博,博雅恩,“心音识别的机遇与挑战:深圳心音数据库简介”,《复旦学报》(自然科学版),59 (3), 354-359. 乔玉,钱昆,赵子平,“基于机器听觉的鸟声识别的中文研究综述”,《复旦学报》(自然科学版),59 (3), 375-380.

学术兼职

2021年08月至今,北京理工大学医学技术学院脑健康工程责任教授 2021年02月至今,IEEE Senior Member(IEEE高级会员) 2021年01月至今,IEEE Transactions on Affective Computing期刊 Associate Editor 2021年01月至今,BIO Integration期刊 Associate Editor 2021年01月至今,中国留德学者计算机学会 人工智能与大数据专家委员会 专家委员 2020年08月至今,Icelandic Research Fund(冰岛科研基金)函评专家

推荐链接
down
wechat
bug