Haida Liang
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Professor at School of Science & Technology
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About
Haida Liang is a Professor at the School of Science & Technology at Nottingham Trent University, UK. His research focuses on ground-based remote sensing, machine learning applications in cultural heritage, and multimodal analysis techniques for art conservation. Recent publications highlight his work on non-invasive monitoring of historic buildings and innovative methods for analyzing wall paintings. His interdisciplinary approach combines physics and art to advance the understanding and preservation of cultural artifacts.
Recent Grants
Grant: Close
Culture and Trade through the Prism of Technical Art History - a study of Chinese export paintings
Open Date: 2013-02-01
Close Date: 2014-01-31
Grant: Close
Collaborative Doctoral 2010 Grant - Non-invasive methods for in situ assessing and monitoring the vulnerability of rock art monuments
Open Date: 2010-09-30
Close Date: 2014-07-30
Grant: Close
The Next Generation of Optical Coherence Tomography (OCT) for Art Conservation - in situ non-invasive imaging of subsurface microstructure of objects
Open Date: 2010-07-04
Close Date: 2013-12-31
Grant: Close
The nature of highly polarised radio sources
Open Date: 2009-06-08
Close Date: 2009-09-07
Grant: Close
Understanding complex structures: the conservation, display and interpretation of lace and natural objects
Open Date: 2009-02-01
Close Date:
Positions (1)
Haida Liang
Nottingham Trent University
4 months ago
This PhD project offers a unique opportunity to explore the making, degradation, and origin of historical parchments using advanced AI-aided, data-driven approaches. Parchments, made from treated animal skins, have served as the primary writing material in Europe and West Asia from the 4th to the 15th century, preserving invaluable records of civilisation. Understanding their origin, manufacturing processes, and degradation mechanisms is crucial for heritage conservation and manuscript dating. The research will focus on the identification of animal species (calf, sheep, goat) used in parchment production, leveraging biocodicology and both invasive (ZooMS, eZooMS) and non-invasive (reflectance spectroscopy, hyperspectral imaging, optical coherence tomography) analytical techniques. Machine learning and AI methods will be developed to enhance species identification and to disentangle complex multimodal imaging data, capturing information about animal origin, age, manufacturing differences, and degradation states. Students will work with a large collection of parchment manuscripts, employing non-invasive imaging to record statistical variations and train robust AI models. Comparative studies will be conducted on manuscripts from Belgium and British archives, representing different manufacturing traditions and exposure conditions. Reference proteomics analyses will be used for verification and calibration. The project is based in the Imaging and Sensing for Archaeology, Art history and Conservation (ISAAC) Lab at Nottingham Trent University and the Artificial Intelligence for Cultural Heritage (PHOENIX) collaborative research project at the University of Namur, Belgium. The studentship is jointly funded by both institutions, covering tuition fees and stipend, and the successful candidate will be registered at both universities. Applicants should have a background in physical sciences or bioinformatics, with a strong interest in heritage science, conservation, and archaeological science. The project welcomes candidates from diverse backgrounds and encourages applications from underrepresented communities. The research environment is inclusive and supportive, offering access to cutting-edge facilities and interdisciplinary expertise. Application deadline is June 15, 2026. For further information, visit the ISAAC Lab and PHOENIX project websites, or contact the supervisory team. Apply via the Nottingham Trent University applications page, ensuring you meet the eligibility criteria.
4 months ago
Articles (10)
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2025
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2024
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2021
Collaborators (2)
Lucas Goehring
Professor of Physics
University of Nottingham
Blythe McCarthy
Smithsonian Institution
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