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Dr David Li

Senior Lecturer

Strathclyde Institute of Pharmacy and Biomedical Sciences

Personal statement

David Li is a senior lecturer in photonics/electronics. He received his PhD in electrical engineering from the National Taiwan University. He then joined the Industrial Technology Research Institute (ITRI), Taiwan, as a R&D engineer working on 1.25-12.5Gbps optical communication chipsets and wireless communication IP, knowledge transfer, and international joint projects with the Carnegie Mellon University, Pittsburgh, USA.

From 2007 to 2011, he worked at the Institute for Integrated Micro and Nano Systems, University of Edinburgh, on the European projects "MEGAFRAME" and "METOXIA" for CMOS single-photon avalanche diode (SPAD) based fluorescence lifetime imaging microscopy (FLIM) cameras and analogue front-end circuits. He has invented several hardware-embedded imaging processors which resulted in the first video-rate FLIM imaging on CMOS SPAD arrays.

From January 2014, he joined the Centre for Biophotonics, SIPBS, after his first lecturing position in biomedical engineering and embedded systems at the School of Engineering and Informatics, University of Sussex (where he led a research team working on industry-funded projects).

His current research interests include CMOS imaging and sensor systems, embedded systems and GPU computing, digital signal processing, mixed-signal integrated circuits, fluorescence based sensing systems, electrical impedance sensing systems, forward models of electrical impedance tomography, finite-element/finite-difference and numerical modelling. He has been working with researchers within the UK and from oversea such as Netherlands, Switzerland, Belgium, Germany, France, China, USA, and Taiwan.

Please also check:

David would be delighted to collaborate with colleagues or hear from potential PhD candidates interested in exploring any aspect of imaging/sensing and embedded systems research. 


Available Studentships:

David has secured a 3 year PhD studentship on 3D ranging, and we would expect to start the project as soon as possible.  

He has also secured a 4 year PhD studentship on smart single-photon sensing systems; we expect the project to start from October 2018. 

Candidates interested in these projects could send CVs to him for further discussions.  


Other funding opportunities for post-graduate students, postdoc researchers and visiting scholars:

China Scholarship Council: (for students in China)

Commonwealth Scholaraships:

EU Marie Sklodowska-Curie Fellowships:

Newton Fellowships:

Royal Society Newton Mobility Grant:

Royal Academy of Engineering Newton Mobility Grant: 




Multi-frame blind deconvolution of atmospheric turbulence degraded images with mixed noise models
Yang Afeng, Jiang Xue, Li David
Electronics Letters, (2017)
A survey of the state-of-the-art techniques for cognitive impairment detection in the elderly
Fei Zixiang, Yang Erfu, Li David, Butler Stephen, Ijomah Winifred, Mackin Neil
Advanced Computational Methods in Life System Modeling and Simulation - International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, ProceedingsCommunications in Computer and Information Science Vol 761, pp. 143-161, (2017)
Estimating fluorescence lifetimes using extended Kalman filter
Gao Kai, Li David
Electronics Letters Vol 53, pp. 1027-1028, (2017)
A computational method for two-dimensional quantitative analysis of standing wave images of red blood cells
Scrimgeour Ross, Tinning Peter William, Li David, McConnell Gail
Microscience Microscopy Congress 2017, (2017)
A low nonlinearity, missing-code free time-to-digital converter based on 28nm FPGAs with embedded bin-width calibrations
Chen Haochang, Zhang Yongliang, Li David Day-Uei
IEEE Transactions on Instrumentation and Measurement Vol 66, pp. 1912 - 1921, (2017)
Comment on 'A novel method for fast and robust estimation of fluorescence decay dynamics using constrained least-square deconvolution with Laguerre expansion'
Zhang Yongliang, Li David Day-Uei
Physics in Medicine and Biology Vol 62, pp. 1632-1636, (2017)

more publications


Development of Imaging Technologies for 3D Visualisation of Cancer Invasion (EPSRC OPTIMA)
Li, David (Principal Investigator) Hallas-Potts, Amelia May (Researcher)
Period 01-Oct-2016 - 30-Sep-2020
UK Quantum Technology Hub in Quantum Enhanced Imaging (Quantic) / R140296-202
Birch, David (Principal Investigator) Chen, Yu (Co-investigator) Li, David (Co-investigator)
Period 01-Oct-2014 - 30-Sep-2019
UK Quantum Technology Hub in Quantum Enhanced Imaging (Quantic) / R140296-106
Birch, David (Principal Investigator) Chen, Yu (Co-investigator) Li, David (Co-investigator)
Period 01-Oct-2014 - 30-Sep-2019
Big Data-Driven Distributed Microseismic Monitoring Method for Hydrofracturing Oil Exploration
Yang, Erfu (Principal Investigator) Li, David (Co-investigator) Post, Mark (Co-investigator)
Period 01-Apr-2017 - 31-Mar-2019
Investigation of a Smart and Low-Cost Autonomous System for Early Detection and Monitoring of Mild Cognitive Impairment in the Elderly
Yang, Erfu (Principal Investigator) Li, David (Co-investigator) Ijomah, Winifred (Co-investigator) Fei, Zixiang (Post Grad Student)
As the number of the elderly people increase, there is an urgent need for the development of advanced assistative technology to ensure their mobility and independent living by early detection and monitoring of the MCI in the low-income community. The main objectives of this project are described as follows: Scientific: (1) To develop novel algorithms for facial recognition and body movement analyses to early detect and monitor the MCI condition in the elderly. (2) To propose a smart tool that can compute the attentional focus of the elderly and determine communication counterparts. (3) To investigate a decision making tool to manage and integrate all the sensory resources of the mobile devices for efficiently executing multiple tasks. Long-term: (1) To improve the performance and scalability of the developed system for the purpose of collective care in the low-income community. (2) To widen the scope of the applicability of the developed system. (3) To lay the foundation for improving the interaction between the elderly and other assistive healthcare device/systems in different environments and chronic conditions. (4) To associate healthcare applications with smart cities, robotics and autonomous systems, signal processing, computer vision and machine learning communities.
Period 01-Oct-2016 - 30-Sep-2019
Big Data-Driven Distributed Microseismic Monitoring Method for Hydrofracturing Oil Exploration
Yang, Erfu (Principal Investigator) Post, Mark (Co-investigator) Li, David (Co-investigator)
This joint-project aims to address the fundamental research challenge related to the development of Big Data-driven distributed microseismic monitoring method for hydrofracturing oil exporation. This research challenge is related to microseismic image information processing and utilization, i.e., how to quickly and efficiently extract and analyze the information of interest for oil detection, tracking its distribution/storage from distributed data/images acquired by a huge number of sensors deployed across the oil field, through either fixed locations or autonomous vehicles platforms, such as unmanned ground vehicle (UGV). To address this challenge faced by the O&G industry, this joint project is focusing on novel Big Data-driven solutions which can integrate distributed data filtering, intelligent analytics and machine learning techniques to offer unique benefits in terms of its ability to bring in data from multiple and distributed sensing sources and provide a full suite of descriptive, predictive and prescriptive analytics.
Period 01-Apr-2017 - 31-Mar-2019

more projects


Strathclyde Institute of Pharmacy and Biomedical Sciences
Hamnett Wing John Arbuthnott Building

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