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Dr Steven Xiaotian Dai
Lecturer

Interests

Dr. Xiaotian (Steven) Dai is a Lecturer (Assistant Professor) in the Real-Time and Distributed Systems group. His research interests include:

  • Timing analysis, task scheduling and allocation for multi-cores
  • Assurance of timing for autonomous and cyber-physical systems
  • Digital Twins for flexibility and resilience

Xiaotian Dai received a PhD from the University of York in 2019 (with Best Thesis). He joined the Real-Time Systems group in 2015 as a PhD research student, supervised by Prof. Alan Burns. His PhD research involves cooperatively designing control systems and real-time task scheduling for Cyber-Physical Systems (CPS), where various flexible scheduling task models are proposed and implemented to investigate the scheduling impact on control performance. He received a M.Sc. in Control Systems from the University of Sheffield in 2014, and a B.Sc. in Control Engineering in 2011.

Xiaotian Dai was a postdoctoral researcher on two research projects from 2019-2023. He worked on safety assurance of cyber-physical systems (H2020 DEIS project), based on an OMG safety standard SACM. He then worked on time assurance and optimization of 5G base stations (MOCHA project) to meet the low latency required by 5G uRLLC for safety-critical systems.

He is a member of IEEE CS, IEEE RAS and ACM SIGBED. He serves as a reviewer and a program committee member of many prestigious real-time and design automation conferences.

For more about me: https://xiaotiandai.com

Qualifications

  • PhD, Real-Time Systems (York, UK)
  • MSc, Automatic Control and Systems Engineering (Sheffield, UK)
  • BSc, Automatic Control (Nanjing, China)

Career

  • Lecturer, Cyber-Physical Systems, University of York (2023-now)
  • Research Associate, Real-Time Systems, University of York (2019-2023)

Departmental and University Roles

  • Student Disability Representative (Deputy On-Campus)

Photo

Contact details

Department of Computer Science
University of York
Deramore Lane
York
YO10 5GH

Phone: +44 (0)1904 325500

Office: CSE/136

E-mail:

Research Group: