Our recent mini review article entitled “COVID-19 and Computer Audition: An Overview on What Speech & SoundAnalysis Could Contribute in theSARS-CoV-2 Corona Crisis” has been accepted and published on by Frontiers in Digital Health.

I have been appointed as the member of the Expert Committee of the Gesellschaft Chinesischer Informatiker in Deutschland e.V. (GCI，中国留德学者计算机学会)!

The GCI was founded in 1986, Karlsruhe City, Germany, which aims for building a bridge of experts, talents, and technologies between China and Germany in the field of Computer Science.

I have been appointed to be the Associate Editor of the journal BIO Integration.

I have been appointed to be the Associate Editor for the IEEE Transactions on Affective Computing (IF-2019: 7.512).

I was awarded the “Excellent Achievement Award” by the “2019 Zhejiang Lab Zhejiang Lab’s International Talent Fund for Young Professionals”, which was ranked as No. 1 in the group of Intelligent Sensing (totally 12 funded research projects). My research project (running time: 2019/08 to 2020/08) supported by the Zhejiang Lab was entitled “Heart sound Analysis and its Non-invasive healthcare Applications via Machine Intelligence (Project HANAMI)”. 

Our paper entitled “Are You Speaking with a Mask? An Investigation on Attention based Deep Temporal Convolutional Neural Networks for Mask Detection Task” was awarded the “Best Paper Award” jointly supported by the CMST and Frontiers.

We are pleased to announce that our recent work has been accepted by the IEEE Internet of Things Journal (IEEE IoTJ). The paper is entitled “Can Appliances Understand the Behaviour of Elderly via Machine Learning? A Feasibility Study”. Readers who are interested in AI for improving the life quality of the elderly group can refer to this paper.

We are organising the special session entitled “Computer Audition for Healthcare (CA4H)” in the upcoming ICASSP 2021. It is the first time attract contributions specialised in the topic on CA4H at the prestigious conference.

Our recent paper entitled “Can Machine Learning Assist Locating the Excitation of Snore Sound? A Review” is accepted and published online by IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI, IF-2019: 5.223). Readers who may be interested in computer audition based methods for non/less invasive methods for snore site location can refer to this paper.

We have a new opinion paper entitled “Computer Audition for Healthcare: Opportunities and Challenges” accepted and published by Frontiers in Digital Health. We give our perspectives and insights for applications in biomedical and health informatics by leveraging the power of computer audition (CA).