Assistant Professor · University of Warwick
Model uncertainty. Interpret evidence. Design decisions.
I develop AI-informed stochastic models for uncertain physical, environmental, energy, and financial systems—turning sparse and complex data into interpretable, decision-ready risk insight.
01Modelrandomness as structureX(s,t,ω)
02Interpretevidence through inferencep(θ | 𝒟)
03Designdecisions under riskd* = arg min 𝔼[L]
Three connected research branches
Across probability, stochastic processes, inverse problems, scientific machine learning, and decision analysis, the programme asks one question: how can mathematical structure turn incomplete evidence into reliable action?
01
Stochastic systems
Learning spatial and temporal variability from sparse observations, simulations, and prior knowledge—then carrying that uncertainty through to system-level risk.
02
Visual intelligence
Extracting risk-relevant structure from images and physical processes, linking perception models with mechanics for explainable hazard intelligence.
03
Decision intelligence
Developing models for pricing, tail events, and risk transfer where market uncertainty, physical exposure, and strategic decisions interact.
Selected projects
A selection of research projects and collaborations.
Loughborough University · i-Risk PhD project selected (2027/28)
Co-supervisor (20%) · Led by Dr Peng Liu, Loughborough University
Selected on 4 November 2026. The project combines extreme value learning, random fields and copulas to study landslide tail risk under a changing climate.
Warwick IAS · Interdisciplinary Research Development Award (2026)
Co-Investigator · With Dr Kaihua Qin (PI) and Prof Jiahua Xu (UCL)
Integrates computer security, stochastic modelling and financial economics to assess systemic risk and cascading failures in decentralised finance.
Fudan–Warwick Joint Seed Fund
Co-Investigator · With Dr Feng Mao (Warwick) and Prof Jian Pu (Fudan)
Combines deep learning and stochastic random fields to address spatial uncertainty in subsurface characterisation.
Shanghai Jiao Tong University–Warwick Joint Seed Fund
In collaboration with Prof Lulu Zhang (Shanghai Jiao Tong University)
Combines machine learning and probabilistic reliability analysis to improve landslide risk assessment under geological and geotechnical uncertainty.
European Commission Horizon 2020 · MSCA-RISE (2020–2026)
Participating Researcher
Contributed stochastic modelling, spatial heterogeneity and uncertainty quantification to interdisciplinary environmental and subsurface research.
Warwick IAS · Early Career Fellowship (2021–2022)
Fellowship Holder
Supported independent research development in computational geomechanics, stochastic modelling and uncertainty quantification for geohazard risk.
Welsh Government · Coal Tip Safety Taskforce (2022)
Researcher and Policy Advisor
Applied computational geomechanics and landslide risk modelling to support coal tip safety assessment and policy in Wales.
Research in practice
The work spans fundamental methods, engineering applications, policy-facing risk, and new financial mechanisms for uncertainty.
View full Warwick profile ↗Recognised through the UK Global Talent route.
Contributed to the Welsh Government Coal Tips Safety Taskforce.
Corresponding member of ISSMGE Technical Committee 309.
Engineering Mathematics, applied modelling, and student research supervision.
Teaching & supervision
I teach engineering mathematics and supervise projects across uncertainty modelling, AI for engineering, risk analysis, and computational decision-making.
Evidence of teaching
Teaching satisfaction in Engineering Mathematics, from Warwick School of Engineering student surveys.
2025/26 survey snapshot
ES1A1 and ES1A8
ES1A1
ES1A1 and ES1A8
| Academic year | ES1A1 | ES1A8 |
|---|---|---|
| 2024/25 | 4.6/5 · n=5 | 4.2/5 · n=17 |
| 2025/26 | 4.3/5 · n=8 | 4.3/5 · n=9 |
36/39 positive satisfaction answers across four surveys (92%).
Source: Warwick School of Engineering student surveys, 2024/25–2025/26. Positive means Agree or Strongly Agree; n is the number of answers to this item. Small samples.
In students’ words
“Derek teaches an example and then allows the class to engage… providing support where required.”
“Brilliant notes… and clear structure. Derek is brilliant with being consistent in every lesson’s delivery.”
“Derek did a great job lecturing this, engaging and made sure everyone was following.”
People & collaborators
Students and collaborators connect stochastic modelling, engineering science, Earth systems, computer vision, and financial risk.
PhD Researcher
University of Warwick, United Kingdom
Conditional neural processes and ACF-constrained random-field reconstruction from sparse observations.
PhD Researcher
University of Warwick, United Kingdom
Brownian motion and non-stationary stochastic processes for multiscale modelling and extreme-event risk.
PhD Researcher
University of Warwick, United Kingdom
Brownian motion and stochastic modelling for probabilistic forecasting and risk-aware sequential decisions.
PhD Researcher
University of Warwick, United Kingdom
Exploring image-based models for porous-media flow and particle transport.
Visiting Research Associate
Nanchang University, China
Diffusion models and physics-informed neural operators for rainfall-induced slope responses.
Research Assistant
The Chinese University of Hong Kong, Hong Kong SAR, China
Image segmentation and engineering AI, with nuclear-graphite applications under exploration.
Former Visiting Student · Marie Skłodowska-Curie Fellow
University of Liverpool, United Kingdom
GeoAI, stochastic modelling, and uncertainty-aware simulation for spatially variable ground conditions and data-informed geotechnical analysis.
Applied AI Research Fellow
University of Warwick, United Kingdom
Machine learning, computer vision, and image analysis for engineering inspection, scientific imaging, and interpretable pattern recognition.
Associate Professor · Visiting Scholar & Collaborator
Guizhou University, China
Backfill-material permeability and geotechnical experiments under uncertainty.
Visiting Research Associate
University of Warwick, United Kingdom
Rainfall infiltration, internal erosion, and slope stability, with a focus on model validation.
Open opportunities
I welcome thoughtful enquiries from prospective PhD students, visiting scholars, and collaborators whose interests connect with the three research branches.
Email Derek →Contact
For research collaboration, student enquiries, policy work, or interdisciplinary projects, the best place to begin is a short email.
Derek.Ma.1@warwick.ac.uk