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Dr Xiaohui Chen

Dr Xiaohui Chen

  • Position: Associate Professor
  • Areas of expertise: Materials and Fluids, Machine Learning, Geotechnical Engineering, Multiphysics Modelling, Environmental Engineering, Water Science, Sustainable Agriculture and Food, Biodiversity.
  • Email: X.Chen@leeds.ac.uk
  • Phone: +44(0)113 343 0350
  • Location: 4.04 School of Civil Engineering
  • Website: Geomodelling and AI Group | Googlescholar

Profile

Dr Xiaohui Chen is an internationally recognised researcher in Artificial Intelligence for Civil and Environmental Engineering, pioneering the integration of Physics-Informed Machine Learning (PIML), Scientific Machine Learning and Multiphysics modelling to address complex engineering and environmental challenges. His research develops next-generation computational methodologies that combine physics, mathematics and artificial intelligence to deliver trustworthy prediction, optimisation and decision-making for infrastructure and environmental systems.

His research spans fluid dynamics, groundwater, geotechnics, environmental engineering, sustainable agriculture and climate resilience, with applications including intelligent infrastructure, water systems, tunnelling, carbon capture and storage, environmental pollution, nuclear waste disposal and digital agriculture. His pioneering research has established internationally recognised methodologies that are increasingly adopted across computational mechanics, geotechnical engineering, hydrology and environmental modelling.

Dr Chen is the Founder and Director of the Geomodelling and Artificial Intelligence Group, one of the University's leading research groups applying AI to engineering and environmental systems. The group currently comprises 2 postdoctoral researchers and 10 PhD researchers, and has secured over £3.7 million in competitive funding from UKRI, Horizon Europe, industry and international partners. Through close collaboration with world-leading universities, research institutes and industrial partners, the group develops cutting-edge AI technologies to enable resilient infrastructure, sustainable resource management and climate adaptation.

International and National Leadership

Dr Chen provides international and national leadership in Artificial Intelligence for Civil and Environmental Engineering, contributing to research strategy, policy, professional societies and scholarly publishing through several high-profile appointments:

  • Board Member, Agri-Food and Biosciences Institute (AFBI), appointed by the Northern Ireland Minister for the Department of Agriculture, Environment and Rural Affairs (DAERA), contributing to the strategic direction of AI, environmental science and sustainable agri-food research. (News)
  • DAFNI Fellow, UKRI Data & Analytics Facility for National Infrastructure, advancing AI-for-Science and digital twins for resilient national infrastructure. (News)
  • Task Force Leader for Physics-Informed Machine Learning, International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE) Technical Committee 309 (Machine Learning), leading international research collaboration and strategic development of Physics-Informed AI.
  • Deputy Editor-in-Chief, Geomechanics and Geoengineering: An International Journal (Taylor & Francis), leading the journal's strategic development and AI research portfolio.
  • UK Representative, ISSMGE Technical Committee 309 (Machine Learning).
  • UK Representative, ISSMGE Technical Committee 215 (Environmental Geotechnics).
  • Committee Member, British Standards Institution (BSI).
  • Editorial Board Member, Environmental Geotechnics (Institution of Civil Engineers).

Research Leadership & Impact

i) Pioneering Physics-Informed Artificial Intelligence for Engineering

Dr Chen has played a leading role in establishing Physics-Informed Machine Learning (PIML) as a new research direction within civil and environmental engineering. His pioneering work has advanced the integration of governing physical laws with artificial intelligence, enabling trustworthy, interpretable and computationally efficient models for complex engineering systems. His group’s contributions, including Loss-Attentional Physics-Informed Neural Networks (LA-PINN), have helped shape the second generation of physics-informed AI and are influencing research across computational mechanics, fluid dynamics, geotechnics, hydrology and environmental engineering.

ii) Building an International Research Community

Dr Chen has been instrumental in building the international research community in Physics-Informed Machine Learning. Through his leadership of the ISSMGE Task Force on Physics-Informed Machine Learning, he has established international collaborations, coordinated global research activities and promoted interdisciplinary knowledge exchange between engineering, applied mathematics and artificial intelligence. His leadership of the internationally collaborative Direction Paper on Physics-Informed Machine Learning in Geotechnical Engineering (2025) has helped define future research priorities and accelerate the adoption of trustworthy AI across engineering disciplines.

iii)Advancing Engineering Science through Authoritative Scholarship

Dr Chen has made significant contributions to the theoretical foundations of engineering through his research on coupled multiphysics processes and scientific machine learning. His UKRI-funded monograph, Multiphase Flows in Deformable Geomaterials: Chemo-Physical Mixture Coupling Theory and Non-Equilibrium Thermodynamics, provides one of the first comprehensive treatments of chemo-physical mixture coupling theory and non-equilibrium thermodynamics for porous media. He also championed the internationally recognised themed issue "Physical-Chemical Coupling in Environmental Geotechnics", bringing together leading international researchers to advance understanding of coupled multiphysics processes and helping to shape future research directions in geoenvironmental engineering.

Responsibilities

  • Deputy Director of Research and Innovation

Research interests

My research has garnered funding from prestigious research councils such as EPSRC, NERC, Horizon EU and CSC, as well as from international industry leaders across the UK, EU, and Asia. Below is a selected list of grants:

  • Horizon EU (UKPI): MARIE SKĊODOWSKA-CURIE ACTIONS Staff Exchanges (SE), Geotechnical Resilience through Intelligent Design. UK leads Physics-Informed Machine Learning
  • NERC (Co-I): iCASP Mini Project: Duration: 2023-2024. Description: Prioritising River Habitat improvements for biodiversity net gain using machine learning. Funding: One 6-month PDRA is funded.
  • EPSRC (PI): MSc Team Research Project: Duration: 2023-2024. Description: Flow behavior of and in bio-soils influenced by organic matter and mineralogy. Funding: Funded through EPSRC Centre for Doctoral Training in Fluid Dynamics (EP/S022732/1).
  • EPSRC (PI): Temperature-water-plant-soil Coupled Modeling for Biogeotechnics: Duration: 2022-2026. Description: Case studentship jointly funded by industry partner N2-Applied. Funding: EP/W524372/1.
  • H2020-EU (PI): BioGeoInterface: Duration: 2022-2024. Description: Grant agreement ID: 101031565. One Marie Curie Fellow was funded. Funding: Link to Project.
  • CSC (PI): Physics-Informed Deep Learning for Quick Prediction of Geo-infrastructure Response to Climate: Duration: 2022-2026.
  • NERC and Deltares Institute (PI): Using Deep Learning for Groundwater Prediction: Duration: 2021-2024 (NE/S007458/1).
  • Strabag Tunnelling (PI): THMC Coupled Modeling for Tunnelling: Duration: 2021-2023.
  • CSC (PI): Bio-inspired Penetrating and Burrowing Strategies: Duration: 2021-2024.
  • N8 Universities Agriculture Food Funds (PI): Real-Time Moisture and Temperature Modeling for Sustainable Agriculture Against Extreme Weather-Induced Pest Attack: Duration: 2021.
  • SUSTech + Leeds Funding (PI): AI for Surface and Groundwater Modeling: Duration: 2020-2024.
  • Kuwait Oil Company (PI): THMC Coupled Modeling for Carbon Capture and Storage: Duration: 2019-2024.
  • EPSRC IAA Phase 3 (Co-I): EP/R511717/1: Duration: 2018-2021.
  • Shell & CSC (PI): THMC Modelling for Shale Gas: Duration: 2019-2023.
  • Kuwait Oil Company (PI): Reactive Transport Modeling for Naturally Occurring Radionuclides: Duration: 2018-2022.
  • White Rose University Consortium (PI): Sustainable Agriculture: Biochemical-Physical-Biological Function of Sludge in Agricultural Soils (BIOSAS): Duration: 2016-2020.

Qualifications

  • PhD The University of Manchester, 2010
  • MSc Dalian University of Technology, 2007
  • BEng Dalian University of Technology, 2003

Professional memberships

  • Fellow of The Institution of Environmental Science
  • Chartered Environmentalist
  • Fellow of Higher Education Academy

Student education

I presently teach:

  • CIVE5162 (MSc Geotechnical Engineering) Constitutive Model and Numerical Analysis (Module Leader)
  • CIVE5574/5575 (MSc EEPM and Geotechnical Engineering) Groundwater Pollution and Contaminated Land (Module Leader)
  • CIVE3750 Individual Research Project
  • CIVE5755 Individual Research Project

Research groups and institutes

  • Water, Public Health and Environmental Engineering

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>