Dr Emmanouil Kakouris

Biography

Dr Emmanouil Kakouris is Assistant Professor in Civil Engineering in the School of Engineering at the University of Warwick.

He received his PhD from the University of Nottingham in 2019. His doctoral research project was on computational modelling of fracture in materials and structures. After his PhD, he continued in the University of Nottingham as a research associate for a collaborative research project with Schlumberger, to investigate the injection-induced vibrations due to hydraulic fracturing process.

He also holds a MEng in Civil Engineering (2012) and a MSc in Analysis and Design of Earthquake Resistant Structures (2014) from the National Technical University of Athens, Greece, where he graduated with distinction.

Following completing his PhD, he spent 4 years in the industry as a Research & Design Engineer at Roughan & O’Donovan (ROD) Consulting Engineers, Ireland, working on European and International research projects and large scale transport infrastructure commercial projects in Ireland and the UK.

He is also a peer reviewer for a number of top ranking research journals in his field such as Computer Methods in Applied Mechanics and Engineering (Elsevier), International Journal for Numerical Methods in Engineering (Wiley), Archives of Applied Mechanics (Springer) and Computational Methods in Structural Engineering (Frontiers).

He teaches modules in the subjects of civil engineering design. His research interests focus on computational science with an emphasis on computational mechanics and data science in engineering as well as the development of automated civil engineering systems.

Research Interests

• Computational mechanics
• Damage modelling in materials
• Multiscale modelling (computational homogenization)
• Artificial intelligence and machine learning methods
• Intelligent engineering systems
• Asset management
• Probabilistic evaluation of systems and their uncertain behaviour
• Resilience, vulnerability and risk assessment of critical infrastructure

Teaching Interests

Teaching for full time undergraduate students and Degree Apprentices.

• ES3G8 Integrated Project (Module Leader)

Selected Publications

• Connolly L., Bernardini I., Kakouris E.G., Kelly J., (2022), "Bridge and tunnel strikes by oversized vehicles", Technical note: World Road Association (PIARC).
• Triantafyllou S.P., Kakouris E.G., (2020), "A generalised phase‐field multi‐scale finite element method for brittle fracture", International Journal for Numerical Methods in Engineering, 121, pp. 1915-1945.
• Egger A., Pillai U., Agathos K., Kakouris E.G., Chatzi E.N., Aschroft I.A., Triantafyllou S.P. (2019), "Discrete and Phase Field Methods for Linear Elastic Fracture Mechanics: A Comparative Study and State-of-the-Art Review", Applied Sciences, 9(12), 2436.
• Kakouris E.G., Triantafyllou S.P. (2019), "Phase-field material point method for dynamic brittle fracture with isotropic and anisotropic surface energy", Computer Methods in Applied Mechanics and Engineering, 357, 112503.
• Kakouris E.G., Triantafyllou S.P. (2018), "Material point method for crack propagation in anisotropic media: a phase-field approach", Achieve of Applied Mechanics, 88(1-2), pp. 287-316.
• Kakouris E.G., Triantafyllou S.P. (2017), "Phase-field material point method for brittle fracture", International Journal for Numerical Methods in Engineering, 112, pp. 1750-1776.

Research Projects

• Probabilistic damage assessment of additively manufactured materials (P-DAM). Funded by Monash-Warwick Alliance; 2025.
• Artificial Intelligence driven multi-physics phase field fracture simulations for composites. Funded by EPSRC; 2024 - 2028.
• Artificial Intelligence driven multiscale material damage modelling. Funded by EPSRC; 2024 - 2028.
• Blending ultrasound data with physics-based models to predict damage in structural systems. Funded by EPSRC; 2023 - 2027.
• Infrastructure climate change risk considering interdependencies and cascading hazards (INFRALIC). Funded by Environmental Protection Agency (EPA) Ireland; 2022; €70,000.
• Bridge and tunnels strikes by oversized vehicles. Funded by World Road Association (PIARC); 2021; €40,000.
• Friction After Polishing (FAP)/ Network Safety Assessment. Funded by Transport Infrastructure Ireland (TII); 2020 - 2021; €50,000.
• Advanced options for authorities in light of Automation and Digitalisation Horizon 2040 (DIRIZON). Funded by European Conference of Directors of Roads (CEDR); 2018 - 2020; €500,000.
• Safety of Transport Infrastructure on the TEN-T Network (SAFE-10-T). Funded by European Commission (EC) under Horizon 2020; 2017 - 2020; €3,000,000.
• Predictive modelling of Injection-Induced vibrations due to Fracking (I²FRAC). Funded by Hermes Fellowship, University of Nottingham; 2018; £20,000.
• Hybrid multiscale methods for nonlinear dynamic processes. Funded by University of Nottingham; 2015 - 2018; £45,000.

Prospective Collaborators

I am always looking for high quality PhD students or collaborators to work on current or new research projects. Please directly contact if interested.

Please also check the PhD scholarships for 2025-26 entry:

1. Chancellor’s International Scholarships (CIS). Details in this link.
Deadline TBC.

2. China Scholarship Council (CSC). Details in this link.
Deadline TBC.

3. Monash Warwick Alliance Joint PhD Scholarships. Details in this link.
Deadline TBC.

4. Shanghai Jiao Tong University, SJTU- Warwick Joint PhD Scholarships. Details in this link.
Deadline TBC.

Vacancies

Looking to take the next step in your research journey? Our group is offering three exciting doctoral projects starting April 2026 or September 2026, tackling some of the biggest challenges in materials, mechanics, and infrastructure engineering.

Ph.D. position 1: Computational modelling of fracture in engineering materials

Qualification:
Doctor of Philosophy in Engineering (PhD)

Start date:
April 2026 or September 2026

Funding for:
4 years

Supervisor:
Dr Emmanouil Kakouris

Application deadline:
31st January 2026. Applications are reviewed continuously, and the post may close once a suitable candidate is identified, early submission is strongly encouraged.

Why choose this PhD?
Fracture - the way cracks initiate and grow - is at the heart of engineering safety, from aircraft fuselages and wind turbines to bridges and biomedical implants. Predicting fracture is a major challenge: cracks evolve in complex ways that traditional models often fail to capture. This PhD gives you the chance to develop advanced computational models of fracture, combining continuum mechanics, numerical methods, and high-performance computing to simulate failure under extreme loading conditions. The project aims to bridge the gap between physics-based theory and engineering applications, producing tools that can guide safer and more reliable design.

What you’ll gain

• 🚀 Deep knowledge of fracture mechanics and continuum theory.
• 💻 Strong programming skills (Python, Matlab) and software development practices.
• 🌍 Internationally competitive training at one of the UK’s top engineering schools.
• 🎓 💼 A strong research profile for future academic or industry careers.

Scholarship:
The award covers UK-rate tuition (£5,006/year) plus a tax-free stipend of £20,780/year for 4 years of full-time study. International candidates are welcome to apply.

Who should apply
You have (or expect to have) a First-class or 2:1 degree in engineering, applied mathematics, physical sciences, or computational sciences. Applicants should be motivated to explore fracture mechanics, numerical methods, and computational modelling. Experience with Finite Element Method, continuum mechanics, is advantageous but not essential - curiosity and commitment are what matter most.

How to apply:
Submit a formal application via Warwick:
https://warwick.ac.uk/fac/sci/eng/postgraduate/applypgr/

Application form 'Course search':
Department: School of Engineering
Academic Year: 2025/26
Type of Course: Postgraduate Research
Engineering (MPhil/PhD) (P-H1Q2)
In the application form funding section, enter: Source: EK-Computational mechanics

Ph.D. position 2: Use AI to understand how materials break

Qualification:
Doctor of Philosophy in Engineering (PhD)

Start date:
April 2026 or September 2026

Funding for:
4 years

Supervisor:
Dr Emmanouil Kakouris

Application deadline:
31st January 2026. Applications are reviewed continuously, and the post may close once a suitable candidate is identified, early submission is strongly encouraged.

Why choose this PhD?
Do you want to use artificial intelligence to tackle one of engineering’s toughest problems? This PhD lets you explore how and why materials fail and build next-generation models that predict fracture under real-world conditions. You’ll go beyond traditional methods, combining continuum mechanics with AI and cutting-edge computational tools to handle uncertainty and complexity in material behaviour.

What you’ll gain

• 🚀 Deep knowledge of fracture mechanics and continuum theory.
• 🤖 Hands-on experience with machine learning in engineering.
• 💻 Strong programming skills (Python, Matlab) and software development practices.
• 🌍 Internationally competitive training at one of the UK’s top engineering schools.
• 🎓 💼 A strong research profile for future academic or industry careers.

Scholarship:
The award covers UK-rate tuition (£5,006/year) plus a tax-free stipend of £20,780/year for 4 years of full-time study. International candidates are welcome to apply.

Who should apply
You have (or expect to have) a First-class or 2:1 degree in engineering, applied mathematics, physical sciences, or computational sciences. Motivation to work on computational modelling, simulation, and AI/ML in engineering is essential. Experience in fracture modelling, numerical methods, is a bonus - not a requirement. Curiosity and commitment matter most.

How to apply:
Submit a formal application via Warwick:
https://warwick.ac.uk/fac/sci/eng/postgraduate/applypgr/

Application form 'Course search':
Department: School of Engineering
Academic Year: 2025/26
Type of Course: Postgraduate Research
Engineering (MPhil/PhD) (P-H1Q2)
In the application form funding section, enter: Source: EK-AI mechanics

Ph.D. position 3: AI-driven decision-support for sustainable infrastructure

Qualification:
Doctor of Philosophy in Engineering (PhD)

Start date:
April 2026 or September 2026

Funding for:
4 years

Supervisor:
Dr Emmanouil Kakouris

Application deadline:
31st January 2026. Applications are reviewed continuously, and the post may close once a suitable candidate is identified, early submission is strongly encouraged.

Why choose this PhD?
How can AI help engineers make smarter, more sustainable decisions about infrastructure? In this PhD, you will develop AI-driven decision-support analytics to guide the life-cycle assessment of civil structures - from design, to operation, to end-of-life. The project addresses key global challenges: sustainability, resilience, and long-term performance of civil infrastructure. Using machine learning, probabilistic methods, and real-time data, you will create tools that help engineers, policymakers, and infrastructure managers balance structural safety, environmental impact, and cost. This is an opportunity to work at the intersection of civil engineering, artificial intelligence, and decision sciences, collaborating with experts at the University of Warwick and TU Delft (AiDAPT).

What you’ll gain

• 🧠 Expertise in decision-making theory and life-cycle assessment.
• 🔢 Skills in probabilistic modelling and managing uncertainty in engineering systems.
• 🤖 Hands-on experience applying machine learning to civil engineering problems.
• 💻 Strong programming and development skills (Python, MATLAB).
• 🌍 A unique research profile tackling global challenges in sustainability and resilience.

Scholarship:
Please note: admission does not automatically include funding. Applicants are encouraged to explore support options via the scholarships & funding.

Who should apply
This project is for you if you have (or expect to have) a First-class or 2:1 degree in engineering, applied mathematics, physical sciences, computational sciences. A strong interest in AI, machine learning, decision-making, and sustainable infrastructure is essential. Prior experience with probabilistic methods, life-cycle assessment, or structural analysis is beneficial but not required.

How to apply:
Submit a formal application via Warwick:
https://warwick.ac.uk/fac/sci/eng/postgraduate/applypgr/

Application form 'Course search':
Department: School of Engineering
Academic Year: 2025/26
Type of Course: Postgraduate Research
Engineering (MPhil/PhD) (P-H1Q2)
In the application form funding section, enter: Source: EK-Prescriptive analytics

Proposing your own project idea?

Curious about joining us or even proposing your own project idea? Explore Warwick’s postgraduate research options here:

https://warwick.ac.uk/fac/sci/eng/postgraduate/applypgr/

Questions?

Get in touch: Emmanouil.Kakouris@warwick.ac.uk