Dr David Li

Senior Lecturer

Biomedical Engineering

Personal statement

David Li is a senior lecturer in optoelectronics at the Department of Biomedical Engineering. He received his PhD in electrical engineering from the National Taiwan University. He then joined the Industrial Technology Research Institute (ITRI), Taiwan, as an 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, digital signal processing, mixed-signal integrated circuits, fluorescence-based sensing systems, and artificial intelligence. He has been working with researchers within the UK and overseas, such as the Netherlands, Switzerland, Belgium, Germany, France, China, the USA, and Taiwan.

Please also check https://scholar.google.co.uk/citations?hl=en&user=UFE7FyIAAAAJ.

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 for 2021:

1. 4-year PhD studentship funded by STMicroelectronics


2. 3-year PhD studentships in time-resolved spectroscopy/imaging and machine-learning techniques for biomedical applications expected to start from 1st October 2021.

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


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

China Scholarship Council: http://en.csc.edu.cn/ (for students in China) 

Commonwealth Scholarships: http://cscuk.dfid.gov.uk 

EU Marie Sklodowska-Curie Fellowships: http://ec.europa.eu/research/mariecurieactions/

Newton Fellowships: http://www.newtonfellowships.org 

Royal Society Newton Mobility Grant: https://royalsociety.org/grants-schemes-awards/grants/newton-mobility-grants/ 

Royal Academy of Engineering Newton Mobility Grant: http://www.raeng.org.uk/grants-and-prizes/international-research-and-collaborations/newton-fund-programmes/newton-research-collaboration-programme


Dynamic non-line-of-sight imaging system based on the optimization of point spread functions
Pei Chengquan, Zhang Anke, Deng Yue, Xu Feihu, Wu Jiamin, Li David U-Lei, Qiao Hui, Fang Lu, Dai Qionghai
Optics Express (2021)
Multichannel time-to-digital converters with automatic calibration in Xilinx Zynq-7000 SoC devices
Wang Yu, Xie Wujun, Chen Haochang, Li David Day-Uei
IEEE Transactions on Industrial Electronics (2021)
Combining time of flight and photometric stereo imaging for 3D reconstruction of discontinuous scenes
Le Francois Emma, Griffiths Alexander D, McKendry Jonathan J D, Chen Haochang, Li David Day-Uei, Henderson Robert K, Herrnsdorf Johannes, Dawson Martin D, Strain Michael J
Optics Letters Vol 46, pp. 3612-3615 (2021)
One-dimensional deep learning architecture for fast fluorescence lifetime imaging
Xiao Dong, Chen Yu, Li David Day-Uei
IEEE Journal of Selected Topics in Quantum Electronics Vol 27 (2021)
Non-fusion time-resolved depth image reconstruction using a highly efficient neural network architecture
Zang Zhenya, Xiao Dong, Li David
Optics Express Vol 29, pp. 19278-19291 (2021)
Histogram clustering for rapid time-domain fluorescence lifetime image analysis
Li Yahui, Sapermsap Natakorn, Yu Jun, Tian Jinshou, Chen Yu, Li David Day-Uei
Biomedical Optics Express (2021)

More publications


SPRINT: A SuPer-Resolution time-resolved ImagiNg and specTroscopy facility for rapid biomolecular analysis
Li, David (Principal Investigator) Chamberlain, Luke (Co-investigator) Chen, Yu (Co-investigator) Cunningham, Margaret Rose (Co-investigator) Gould, Gwyn (Co-investigator) Hoskisson, Paul (Co-investigator) McConnell, Gail (Co-investigator) Rattray, Zahra (Co-investigator) Van de Linde, Sebastian (Co-investigator)
01-Jan-2021 - 30-Jan-2022
Time-resolved imaging and spectroscopy systems for life science applications
Li, David (Principal Investigator) Jiao, Ziao (Researcher)
01-Jan-2020 - 31-Jan-2023
High-precision time conversion and TCSPC systems for time-resolved optical spectroscopy and imaging
Li, David (Principal Investigator) Wang, Yu (Researcher)
01-Jan-2020 - 30-Jan-2023
Applications of multichannel high-precision time-resolved spectroscopy
Li, David (Principal Investigator) Wang, Quan (Researcher)
01-Jan-2020 - 30-Jan-2023
Smart Hardware-embedded Data Processors for Rapid 3D Ranging & Imaging
Li, David (Principal Investigator) Zang, Zhenya (Researcher) Yang, Erfu (Co-investigator)
01-Jan-2019 - 31-Jan-2022
Stand-off, SPAD-enhanced Ultra-Violet Raman Spectroscopy
Kelly, Ellis (Researcher) Stothard, David (Principal Investigator) Li, David (Principal Investigator)
The detection of substances at range is extremely important to a number of industrial production and safety processes. Raman is a potent optical technique by which the nature of a substance can be ascertained, but to date has been limited to contact / short-range stand of operation due to the weakness of the Raman scattering effect. In this programme, we will develop and evaluate different stand-off Raman spectrometers to solve different industrial, medical and safety issues in sectors such as the Nuclear industry, mining, healthcare and pharma production. Crucially, we will use UV excitation sources to maximise the intensity of the Raman scatter, and use single photon detectors which not only confer exquisite sensitivity, but whose temporal response allows fluorescence-suppression techniques to be brought to bear on such systems. Whilst many of these techniques have been demonstrated individually, we will integrate them into a single system refined for deployment in the envisaged end-user scenario; such an endeavour would represent a highly timely, novel and disruptive achievement. Our use of single-photon detectors also plays strongly into the UK Quantum Technologies agenda, and will result in a timely and highly innovative early industrial application of these devices.
01-Jan-2019 - 30-Jan-2023

More projects


Biomedical Engineering
Wolfson Building

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