Areas of expertise:
Computational Hydraulics (Two-Phase Transient Flows, Air Entrapment, Water Resources Planning); Digital Solutions (AI-Driven Solutions, Digital Twin); Engineering Education (Authentic Assessment)
I am an Assistant Professor in Hydraulics and Water Systems at the University of Leeds, where I lead undergraduate programmes and key MSc modules. I have published over 30 peer-reviewed papers, with 87% appearing in journals ranked in the top 25% by CiteScore. More than 50% of my work is in the top quartile of the most-cited papers worldwide. My work is driven by a commitment to advancing sustainable, resilient water infrastructure – both through cutting-edge research and by integrating real-world practice into student learning.
As the leader for three undergraduate programmes – Civil Engineering, Civil and Environmental Engineering, and Civil and Structural Engineering – I coordinate academic and support staff to ensure that modules, assessment strategies, and learning outcomes align with professional standards and the evolving needs of the industry. As module leader for key MSc modules, I am involved in two MSc programmes: Water, Sanitation and Health (WASH) and Environmental Engineering and Project Management (EEPM), in which I am privileged to work with a wide range of talented international students from around the world.
My educational background is entirely in civil engineering, with a BSc in Civil Engineering and an MSc in Civil Engineering, specialising in Hydraulic Structures. After completing my MSc, I worked in consulting firms for several years, gaining valuable industry insights that have enriched my research and teaching. I then returned to academia as a lecturer, gaining valuable experience teaching a wide range of civil engineering topics. I completed my PhD at Instituto Superior Técnico, University of Lisbon, where I specialised in pressure surge control in two-phase flows and novel compressed air energy storage systems (CAES). After pursuing my PhD and a postdoctoral position at the same university, I worked as a lecturer at the University of Suffolk before joining the University of Leeds in June 2022. Since then, I have worked on a diverse portfolio of research and educational projects with internal and external partners.
I am always keen to connect with researchers, engineers, students, practitioners, and policymakers interested in strengthening water infrastructure around the world.
My research encompasses three interconnected themes: computational hydraulics, digital solutions for water networks, and engineering education.
In computational hydraulics, I focus on complex two-phase transient flows, air-entrapment dynamics, and integrated water-resources planning. My past works have employed a wide range of CFD and 1D models to simulate air-water interactions and predict flow parameters, including pressure and velocity. I have developed extensive experimental studies investigating air dynamics inside air vessels and their effect on pressure surge mitigation within pipe systems to be used in numerical simulations. This has provided valuable insights into the energy-absorbing capabilities of air in air vessels, a topic that has significantly influenced my development of small scale compressed air energy storage (CAES) systems using the kinetic energy of transient flows. This concept, termed TI-CAES, is introduced in my publications. I am particularly passionate about the role of protective devices such as air valves and air vessels in safeguarding pipeline systems. The use of numerical models - including elastic, rigid, and computational fluid dynamics (CFD) approaches - fascinates me as it allows detailed exploration of gas-liquid interactions and transient phenomena.
In the area of digital solutions, I design AI-driven monitoring and predictive systems and develop digital twin frameworks for real-time decision support in water networks. My MSc research laid the foundation for this by incorporating optimisation algorithms, including genetic algorithms and artificial neural networks (ANNs), where ANNs supported by wavelet functions were used to accelerate optimisation processes. Building upon this, my current work applies AI predictive models to forecast contamination events in water resources and to predict complex transient flow conditions in pipe systems. These developments aim to be fully integrated into advanced digital twins capable of visualising and predicting rapid, destructive transient events, thereby enhancing operational resilience.
In engineering education, I focus on expanding authentic assessment models, such as iterative feed-forward feedback loops, and integrating immersive virtual reality (VR) technologies. These innovations aim to enhance student engagement, deepen learning, and improve educational outcomes. Through pedagogic research, I strive to identify and share best practices that enrich the student learning experience, revolutionising skill acquisition for future generations.
Ultimately, my research is driven by a commitment to sustainability, interdisciplinarity, technological innovation, and impactful education. With a background in bridging multiple disciplines - including fluid mechanics, artificial intelligence, data science, medicine, and pedagogic research - I am passionate about fostering cross-disciplinary collaborations that yield innovative solutions to complex engineering challenges. I believe that addressing the evolving demands of modern challenges requires an integrative approach.
Professional memberships
Institution of Civil Engineers (ICE)
American Society of Civil Engineers (ASCE)
International Association for Hydro-Environment Engineering and Research (IAHR)
Research groups and institutes
Water, Public Health and Environmental Engineering
Sustainable and resilient infrastructure
Cities, Infrastructure and Energy
Smart energy systems
Healthy buildings: air quality and airborne infection
Energy Leeds
Artificial Intelligence
<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>
