Xinwei Fang
Lecturer

Interests

My research interests lie in designing and developing trustworthy autonomous systems by understanding, detecting, and mitigating uncertainties that can be introduced at various stages of the system.

I consider autonomous systems to be both digital systems (those used by human experts to inform decisions regarding future action plans, such as software for object detection) and embodied systems (those that have a physical component and can take action based on system-generated decisions, such as self-driving cars).

My research involves studying the following areas:

1. Using machine learning or mathematical methods to extract information from raw sensing data.
2. Employing statistical methods to identify, understand, and mitigate the impact of uncertainties across the long chain of the system process.
3. Applying runtime monitoring and verification to ensure the system's compliance with various requirements.
4. Proactively adapting to disruptions, changes, or uncertainties before they cause issues.

I am particularly interested in the intersection of these techniques and in developing new methods for ensuring the trustworthiness of autonomous systems.

Qualifications

• Phd (2018), University of York
• MSc (2014), ITC, University of Twente
• BEng (2012), Vaasa Polytechnic

Career

• Lecturer, York (2023 - present)
• Research Associate, York (2018 - 2023)
• Marie Curie Early Stage Researcher, York (2014 - 2017)

Departmental and University Roles

• PGT ACS Programme Lead