Dr Ningrong Lei PhD, MSc, BEng, FHEA
Associate Professor in Systems Engineering, Course leader for MSc Advanced Engineering and Management
- Department of Engineering and Mathematics
- Advanced Wellbeing Research Centre
- Industry and Innovation Research Institute
Summary
Dr Ningrong Lei is an associate professor in systems engineering and course leader for MSc Advanced Engineering and Management. She holds a PhD in Industrial Engineering and Management from Nanyang Technological University, Singapore. Ningrong's 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.
About
Ningrong joined Sheffield Hallam University as a lecturer in 2016, achieving promotion to senior lecturer and associate professor in 2019 and 2023 respectively. Prior to joining Hallam, Ningrong was a visiting scholar at Georgia Institute of Technology, USA. She worked as a researcher at Centre of Innovation at Ngee Ann Polytechnic, Singapore. Before that, she was a lecturer at Wuhan Institute of Technology, China, where she led the industrial training program of surface mount technology in collaboration with Foxconn Technology Group.
Ningrong's 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 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, she 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, she 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/.
Ningrong acts as a mentor within the Advance Wellbeing Research Centre (AWRC) Accelerator program—an esteemed R&D initiative. Through this role, she provide invaluable support and mentorship to pre-revenue and early-stage health and wellbeing companies, not only fostering their growth but also enriching her own professional development and networking endeavours.
Teaching
Department of Engineering and Mathematics
College of Business, Technology and Engineering
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:
MSc Advanced Engineering and Management
BEng/MEng (Hons) Mechanical Engineering
BEng/MEng (Hons) Electrical and Electronic Engineering
Modules taught:
Systems engineering (level 6, module leader)
Systems Engineering and Systems Thinking (level 7)
Mechatronics (level 5)
Design evaluation technology (level 5)
Group project (level 7)
Research
- Principal Investigator(PI), A real time sleep apnoea detection service in the home environment. £133,000, SHU GTA PhD project, 2024-2027.
- PI, Heart rate variability biofeedback in long COVID rehabilitation. £6,000, SHU department research fund, 2023-2024.
- PI, A mental health monitoring service to prevent depression. £68,000, PhD scholarship project-Lybia Government, 2022-2026.
- PI, Sleep Apnoea Detection with Smart Internet of Things Technology. £65,000, PhD scholarship project-Lybia Government, 2019-2023.
- Consultant, AWRC accelerator. £8,250, 2023.
- Early career research and innovation fellowship, A multi-disease detection service platform
based on deep learning and internet of things. £5,000, SHU, 2022.
- Entrepreneurial Lead, an atrial fibrillation detection service for stroke prevention. £ 60,000, Innovate UK. 2021-2022.
- Co-I, the stroke risk monitoring service. Grant: £ 40,000, Grow MedTech, 2019-2021.
- Co-I, Stroke Risk Monitoring Service. Research England, £5,000. 2019.
- Founding member, transformative artificial intelligence applications research cluster. £1,550, CKIP SHU, 2019.
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.
https://www.scci.org.uk/news/sheffield-hallam-awarded-30k-to-further-develop-stroke-prevention-service/
https://www.setsquared.co.uk/meet-the-trailblazing-female-innovators-who-are-shaping-our-future/.
Publications
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, 456-460. 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.
Media
Lei, N. (2022). Ebers Health - Real time atrial fibrillation detection to prevent stroke.
Presentations
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).
Scientific advisory board - Design Conferences from 2018 to 2022.
Postgraduate supervision
- Jude Okorie (as Director of Studies)
- Marim Altaleb (as Director of Studies)
- Ragab Barika (as Director of Studies)
- Jiacheng Chen (as Co-supervisor)
- Samina Komal (as Co-supervisor)