Dr Mohammad Eissa

Department of Electronic and Electrical Engineering

Lecturer in Digital Electronics

EEE - Dr Mohammad Eissa - Staff Profile
Profile picture of EEE - Dr Mohammad Eissa - Staff Profile

I earned a Bachelor's degree in Computer Engineering followed by an MSc in Data Communication Engineering at the University of Sheffield. Then, I pursued a PhD with a focus on translational digital engineering in chronic conditions to sustain behaviour change.

I have had the privilege of holding several postdoctoral research associate roles in the Electronic and Electrical Engineering Department at the University of Sheffield. In these roles, I focused on researching novel statistical, machine learning and AI models and biomarkers. I've also ventured into digital healthcare technology with a mission to make it more inclusive and efficient. I've had the opportunity to collaborate closely with the Royal College of Arts, combining design and technology to create user-friendly healthcare solutions. My emphasis in this endeavour has been on highlighting the potential of digital technologies to enhance care, especially for vulnerable populations.

Furthermore, I've been an honorary researcher at Sheffield Teaching Hospitals. In this capacity, I was involved in analysing various aspects of diabetes care in clinical settings. This has encompassed examining the utilisation of insulin pumps and addressing the impact of the COVID-19 pandemic on people with diabetes. I've also been involved in the DAFNEplus randomised clinical trial in harnessing the power of digital technologies to enhance patient-centred care.

As I look ahead in my career, my focus remains on extending industrial partnerships in academia and further research, particularly in the healthcare technology and data-driven solutions domain. I'm passionate about System on Chip (SoC), hardware, and embedded implementations. Machine learning and AI hold a special place in my research interests due to their potential to significantly enhance decision-making and predictions in healthcare. Moreover, I actively work to make research practical and directly applicable in the real world.


PhD (Electronic and Electrical Engineering), University of Sheffield 2023

Research interests
  • Machine learning and AI
  • Digital healthcare technology
  • IoT applications 
  • System on Chip (SoC)
  • Hardware design

Journal articles

Teaching activities
  • EEE125
  • EEE232
  • EEE6225