Yiyuan Han

Graduate Laboratory Assistant
School of Computer Science and Electronic Engineering (CSEE)
Postgraduate Research Student
School of Computer Science and Electronic Engineering
 Yiyuan Han


Ask me about
  • Signal Processing
  • MATLAB programming


Yiyuan Han is currently a PhD student at BCI-NE Lab (entry year: 2019), whose research interests mainly include brain-computer interface, biomedical signal processing and the neural signature of pain. Yiyuan obtained her B. Eng. in Information Engineering in 2019 from Southern University of Science and Technology in China as Magna Cum Laude. During her undergraduate study, she was working on human speech perception and acoustic signal processing under the supervision of Dr Fei Chen. In October 2019, she started her PhD in Computer Science at the University of Essex, under the supervision of Dr Sebastian Halder and Dr Elia Valentini. Now she is investigating the novel approach to assess pain in unresponsive patients based on electrophysiological signals, which is aiming at a pain assessment system based on transfer learning at bedside. GLA Teaching Modules: - Mathematics: CE142 Mathematics for Electronic & Telecommunications (20-21, 21-22) - Programming: (Python) CE151 Introduction to Programming (21-22) (JAVA) CE152 Object-Oriented Programming (19-20, 20-21) CE203 Application Programming (19-20, 20-21, 21-22) CE303 Advanced Programming (21-22) - Theory: CE235 Computer Security (20-21) CE314 Natural Language Engineering (21-22)


  • BEng Southern University of Science and Technology (2019)

Research and professional activities


Development of a novel approach to neurophysiological pain assessment in unresponsive patients

Improvements in intensive care have led to an increasing number of patients surviving traumatic brain injuries. Due to their injuries, these patients may be unable to self-report pain. Vital signs are not a reliable primary indicator of pain and methods such as functional magnetic resonance imaging cannot be applied at the bedside. Thus, the goal of this project is the development of a novel method based on the online analysis of electroencephalography (EEG) data to determine if a patient is exp

Supervisor: Sebastian Halder , Elia Valentini



Colchester Campus

Working pattern:

If you have any questions which I might be able to help, please email me to book an appointment.