Humans interact and obtain information from machines equipped with algorithms in daily activities, such as browsing the web, using ChatGPT, driving, trading stocks, etc. Not only has the interaction of humans and AI-enabled machines become more frequent, but also the interactions among increasingly autonomous machines have increased, forming a collaborative human-machine ecosystem. In this project, we aim to consider microscopy and macroscopy of this unique technological ecology of humans and machines to discover viable strategies to facilitate cooperative collective intelligence.

Since 1900, humankind has experienced two world wars, economic depressions, environmental disasters, and the COVID-19 pandemic. Repeated crises are lurking around humanity. Governments are practising an optimization problem of social resource allocation with variances, such as human interactions and information dissemination. To manage public emergencies, my future will be designing a model that can simulate the world dynamically, and provide prediction and management policy urgently desired to minimize the damage.

I am working on the "Rethink Digital Contact Tracing System " project with Dr Manuel Cebrian and Dr Kate Farrahi. In this project, I treat digital contact tracing as a simplified information system and propose a leader-follower mean-field game by considering individual cost, system effectiveness, and societal cost.

With the wide deployment of low-cost Internet of Things (IoT) in an increasing number of applications such as smart cities, new challenges have emerged concerning the market of digital services to compensate for the lack of processing, computation, and other resources of IoT. At the same time, the complexity of interplay among stakeholders has grown in size, granularity, and variation of trust. In this project, we consider an IoT market with heterogeneous buyers. The buyers interact with the resource supplier dynamically with specific resource demands. This work introduces a broker between the supplier and the buyers, equipped with Distributed Ledger Technologies (DLT) providing a service for market security and trustworthiness. 

I was on the EU H2020 project "Secure and Safe Internet of Things" with Prof. Martin Reed and his team. My research was “Blockchain assisted software-defined network", which focused on using blockchain for flow verification/validation in a software-defined IoT network. I studied the incentive mechanisms for the servers to participate in blockchain operations. Computational resource and energy consumption of private, public, and hybrid blockchain are the critical criteria in the works. I have published two journal papers and one conference paper regarding this topic.

During my PhD years, I dedicated my research to sensory data collection, incentive mechanisms, and sensory task execution in mobile crowdsensing. This project is under "Research and Application on Storage Resource Virtualization of  Distributed Systems", National Sci-Tech Support Plan of China under Grant No. 2014BAH02F03-1, 2014/01-2016/12.