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.
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
Aggregate results and short, non-identifying extracts from Warwick School of Engineering student surveys.
Reported for both ES1A1 and ES1A8.
Highest reported score across ES1A1 and ES1A8.
Reported for both ES1A1 and ES1A8.
2025–26 School of Engineering student surveys · 17 submitted responses across ES1A1 and ES1A8
“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.”
Feedback into action
Student feedback continues to shape the balance between mathematical depth, practice, assessment clarity, and pace.
People & collaborators
Students and collaborators connect stochastic modelling, engineering science, Earth systems, computer vision, and financial risk.
PhD Student
University of Warwick, United Kingdom
Stochastic modelling, geotechnical uncertainty, random fields, and probabilistic representations of spatially variable engineering systems.
PhD Student
University of Warwick, United Kingdom
Quantitative risk, pricing, and computational finance, with emphasis on uncertainty-aware valuation, tail events, and data-informed decisions.
PhD Student
University of Warwick, United Kingdom
Machine learning, computer vision, and geotechnical imaging for interpretable analysis of engineering materials, structures, and risk.
Visiting Research Associate
Nanchang University, China
Landslide dynamics, neural operators, and physics-informed modelling for rapid simulation, uncertainty propagation, and hazard-aware prediction.
Research Assistant
The Chinese University of Hong Kong, Hong Kong SAR, China
Image segmentation and AI-assisted geotechnical visual intelligence, linking material features, spatial patterns, and engineering interpretation.
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
Geotechnical modelling, uncertainty quantification, and risk analysis for complex ground behaviour, infrastructure resilience, and engineering decisions.
Visiting Research Associate
University of Warwick, United Kingdom
Collaborative research in engineering modelling, data-informed analysis, and uncertainty-aware computational methods for applied science.
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 ↗