Dr Ningrong Lei

Dr Ningrong Lei PhD, MSc, FHEA

Associate Professor in Systems Engineering


I am an associate professor in systems engineering. My research focuses on leveraging systems engineering methodologies to create accessible and scalable multi-disease detection and monitoring services based on artificial intelligence and wearable technology. 



I hold a PhD in Industrial Engineering and Management from Nanyang Technological University, Singapore. Prior to joining Hallam, I was a visiting scholar at Georgia Institute of Technology, USA. I also worked as a researcher at Centre of Innovation at Ngee Ann Polytechnic, Singapore. Before that, I was a lecturer at Wuhan Institute of Technology, China, where I led the industrial training program of surface mount technology in collaboration with Foxconn Technology Group.

In 2016, I became part of the Sheffield Hallam University faculty as a lecturer, achieving promotion to senior lecturer and associate professor in 2019 and 2023 respectively. My vision is to develop a scalable and sustainable service platform for multi-disease detection and monitoring. This aspiration has driven the creation of technologies that harness wearable devices and Artificial Intelligence (AI) for the detection of atrial fibrillation (AF) and sleep apnoea. These technological innovations hold promising potential to improve AF and sleep apnoea detection allowing earlier treatment with the attendant downstream benefits of reduced morbidity.
To validate these technologies, I spearheaded two clinical studies, undertaken in collaboration with esteemed clinical and industry partners. Clinical evidence showed that both AF and sleep apnoea can be detected based on cardiac electrical activity in the home environment. To further advance these technologies towards commercialization, I successfully secured Innovate UK funding. Please see press coverage: https://www.scci.org.uk/news/sheffield-hallam-awarded-30k-to-further-develop-stroke-prevention-service/ and https://www.setsquared.co.uk/meet-the-trailblazing-female-innovators-who-are-shaping-our-future/.

As a guest editor for the Journal of Applied Science and AI-based automated recognition and detection in healthcare, I actively contribute to the advancement and quality of research in these fields. My designation as an expert reviewer for the National Institute for Health and Care Research programme further underlines the recognition of my expertise and contributions. Since 2021, I have also assumed the role of mentor within the Advance Wellbeing Research Centre (AWRC) Accelerator program—an esteemed R&D initiative. Through this role, I provide invaluable support and mentorship to pre-revenue and early-stage health and wellbeing companies, not only fostering their growth but also enriching my own professional development and networking endeavours.


Department of Engineering and Mathematics

College of Business, Technology and Engineering

Subject areas: Systems engineering; Digital health
Group: Materials and Engineering Research Institute, Industry and Innovation Research Institute, Advanced Wellbeing Research Centre


Courses taught:
- BEng/MEng (Hons) Mechanical Engineering
- MSc Advanced Engineering and Management

Modules taught:
- Systems engineering
- Mechatronics


My current research interests include data-driven product and service design, modular service design, and Internet of Things for data-driven additive manufacturing. I am the founding member of the 'Transformative artificial intelligence applications research cluster'. 

I am the Co-investigator for the following funded projects: 

  • The stroke risk monitoring service, funded by Grow MedTech Proof of Feasibility funding. 
  • The stroke risk monitoring service, funded by Grow MedTech Proof of Market funding.

1. 2023. AWRC Accelerator project.
2. 2023. Long COVID rehabilitation monitoring based on wearable technology and artificial intelligence.
3. 2021-2022 An atrial fibrillation detection service for stroke prevention. Funded by Innovate UK.
4. 2019-2022. A stroke risk monitoring service. Funded by Grow MedTech.



Journal articles

Barika, R., Elphick, H., Lei, N., Razaghi, H., & Faust, O. (2022). Environmental benefits of sleep apnoea detection in the home environment. Processes, 10 (9). http://doi.org/10.3390/pr10091739

Faust, O., Kareem, M., & Lei, N. (2021). Atrial fibrillation detection service validation tool. Software Impacts, 10. http://doi.org/10.1016/j.simpa.2021.100117

Paszkiel, S., Rojek, R., Lei, N., & Castro, M.A. (2021). Review of solutions for the application of example of machine learning methods for motor imagery in correlation with brain-computer interfaces. Przeglad Elektrotechniczny, 97 (11), 111-116. http://doi.org/10.15199/48.2021.11.20

Kareem, M., Lei, N., Ali, A., Ciaccio, E.J., Acharya, U.R., & Faust, O. (2021). A review of patient-led data acquisition for atrial fibrillation detection to prevent stroke. Biomedical Signal Processing and Control, 69, 102818. http://doi.org/10.1016/j.bspc.2021.102818

Paszkiel, S., Rojek, R., Lei, N., & Castro, M.A. (2021). A Pilot Study of Game Design in the Unity Environment as an Example of the Use of Neurogaming on the Basis of Brain–Computer Interface Technology to Improve Concentration. NeuroSci, 2 (2), 109-119. http://doi.org/10.3390/neurosci2020007

Lei, N., Kareem, M., Moon, S.K., Ciaccio, E.J., Acharya, U.R., & Faust, O. (2021). Hybrid Decision Support to Monitor Atrial Fibrillation for Stroke Prevention. International Journal of Environmental Research and Public Health, 18 (2), 813. http://doi.org/10.3390/ijerph18020813

Faust, O., Lei, N., Chew, E., Ciaccio, E.J., & Acharya, U.R. (2020). A Smart Service Platform for Cost Efficient Cardiac Health Monitoring. International Journal of Environmental Research and Public Health, 17 (17), e6313. http://doi.org/10.3390/ijerph17176313

Lei, N., Yao, X., Moon, S.K., & Bi, G. (2016). An additive manufacturing process model for product family design. Journal of Engineering Design, 27 (11), 751-767. http://doi.org/10.1080/09544828.2016.1228101

Lei, N., & Moon, S.K. (2015). A decision support system for market-driven product positioning and design. Decision Support Systems, 69, 82-91. http://doi.org/10.1016/j.dss.2014.11.010

Lei, N., LU, P., & Liu, Z.-.M. (2009). Effect of magnetic fluid grinding parameters on grinding efficiency and grinding mechanism of steel balls. Machinery Design & Manufacture, 241.

Lei, N., & Liu, Z.-.M. (2005). Engineering Experimental Long Distance Supervisory Control System Based on Web. Journal of WUT Information and Management Engineering, 27, 28-31.

Conference papers

Chen, J., Alboul, L., & Lei, N. (2022). Simulation of fire fighter swarm robotics in MATLAB and robot e-puck2 development. UKRAS22 Conference "Robotics for Unconstrained Environments" Proceedings, 30-31. http://doi.org/10.31256/ei2ak4a

Lei, N., Faust, O., Rosen, D.W., & Sherkat, N. (2018). Uncovering design topics by visualizing and interpreting keyword data. The proceeding of 15th international design conference, 57-68. http://doi.org/10.21278/idc.2018.0370

Lei, N., Moon, S.K., & Rosen, D. (2015). Redefining product family design for additive manufacturing, iced [abstract only]. In Weber, C., Husung, S., Cantamessa, M., Cascini, G., Marjanovic, D., Graziosi, S., ... Venkataraman, S. (Eds.) 20th International Conference on Engineering Design (ICED15), Milan, Italy, 27 July 2015 - 30 July 2015. The Design Society

Lei, N., Moon, S.K., & Bi, G. (2014). Additive manufacturing and topology optimization to support product family design. High Value Manufacturing: Advanced Research in Virtual and Rapid Prototyping - Proceedings of the 6th International Conference on Advanced Research and Rapid Prototyping, VR@P 2013, 505-510.

Chen, G.X., Kwee, T.J., Lei, N.R., Tan, K.P., Choo, Y.S., & Hong, M.H. (2010). Underwater laser cleaning for marine and offshore applications. International Congress on Applications of Lasers & Electro-Optics. http://doi.org/10.2351/1.5062066

Kwee, T.J., Chen, G.X., Lei, N., Tan, K.P., Choo, Y.S., & Hong, M.H. (2010). Surface preparation for shipbuilding using pulsed high-power fibre laser. International Congress on Applications of Lasers & Electro-Optics, 451-455. http://doi.org/10.2351/1.5062065

Book chapters

Lei, N., & Moon, S.K. (2014). Decision support system design for data-driven management. In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASME: http://doi.org/10.1115/DETC2014-34871

Lei, N., Moon, S.K., & Bi, G. (2014). An Additive Manufacturing resource process model for product family design. In Proceedings of the 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE: http://doi.org/10.1109/IEEM.2013.6962485

Lei, N., & Moon, S.K. (2013). A decision support system for market segment driven product design. In Lindemann, U., Venkataraman, S., Kim, Y.S., Lee, S.W., Papalambros, P., & Chen, W. (Eds.) Proceedings of the 19th International Conference on Engineering Design (ICED13), Design for Harmonies. (pp. 177-186). Design Society: https://www.designsociety.org/publication/34655/A+decision+support+system+for+market+segment+driven+product+design

Theses / Dissertations

Lei, N. (2016). Data-driven project family design for additive manufacturing. (Doctoral thesis). Supervised by Moon, S.K.


Lei, N. (2022). Ebers Health - Real time atrial fibrillation detection to prevent stroke.


Lei, N. (2021). Heart health monitoring service platform. Presented at: Materials and Engineering Research Symposium (MERI) research symposium, Online, 2021

Lei, N., Yao, X., Ki Moon, S., & Bi, G. (2014). Resource-Driven Product Family Design in Additive Manufacturing. Presented at: 1st International Conference on Progress in Additive Manufacturing (Pro-AM 2014), Nanyang Technological University, Singapore, 2014

Other activities

Guest editor - MDPI special issue on AI-based automated recognition and detection in healthcare.
Guest editor - Applied Science special issue on Advance in Technology of Brain-Computer Interface.
Review editor - Biomedical Signal Processing, Frontiers.
Grant funding reviewer -National Institute for Health and Care Research (NIHR).

Postgraduate supervision

Innovate UK; Sheffield Teaching Hospital; Sheffield Children's Hospital; EPSRC South Yorkshire Digital Health Hub

- Marim Altaleb (as Director of Studies)
- Ragab Barika (as Director of Studies)
- Jiacheng Chen (as Co-supervisor)
- Samina Komal (as Co-supervisor)

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