Jiangtao is currently an Associate Professor (equivalent to Reader Position) with Center for Intelligent Healthcare, Coventry University. Before Joining in Coventry Univ, he was a lecturer in Lancaster University and Peking Univeristy, respectively. His research interests include Pervasive and Mobile Computing, Crowdsensing, Digital Health, Internet of Things, and Smart Cities. Jiangtao has developed a strong international reputation for his research on Mobile Crowdsensing/Crowdsourcing systems, specifically within the domains of cost and quality joint optimization. He is among the pioneering researchers who introduce the novel mechanisms to optimize sensing quality and cost in task allocation – a fundamental research issue and a maker or breaker in urban crowd sensing. With several novel research perspectives, Jiangtao has achieved a number of top conference and journal publications (e.g, UbiComp, PerCom, CSCW, AAAI, IJCAI, ICDM, IPSN, CIKM, IEEE Trans. on Mobile Computing, IEEE Trans. on Human-Machine Systems, IEEE Computer, and so forth). The results have been validated extensively using real-world data showing superior performance. These works are highly cited and recognized as evident by distinguished talk invitations from prestigious universities such as Nanyang Technological University (Singapore), National University of Singapore, and the University of New South Wales (Australia). As key author of these works, have been invited to organize and chair three IEEE international workshops on Crowdsensing. Jiangtao also serves for the journal editorial board such as Personal and Ubiquitous Computing, Frontiers in Sustainable Cities, etc, and PC members of multiple international conferences.

For more details, please visit his personal research homepage at:

 https://jiangtaowang.wixsite.com/website 

Ubiquitous computing, Mobile crowdsensing/crowdsroucing, Digital Health,  Internet of Things.

Jiangtao is a computer scientist in the areas of pervasive and mobile computing, Internet of Things, data science, and artificial intelligence. With particular interest in their applications in digital health, human wellbeing and environment sensing, he collaborates closely with clinicians, environment engineers, industrial partners, and government policy makers to move ubiquitous computing technology into the pathways of health care in terms of both individual and population level. With the goal of enhancing the quality of life for all people, he is now leading or participating in several research projects in mobile health sensing, healthcare data analytics, and population health monitoring.