In a nutshell, tell us about what you do
I work as a Lecturer in Analytics of Infrastructure Systems at UCL’s Faculty of Engineering Science. I’m also currently heading up a research project focused on developing dynamic digital twins of interconnected energy and transport networks, as part of an ongoing collaboration between the Turing and Accenture.
Can you tell us about that collaboration, and how your research fits into it?
So, the Turing has launched a five-year strategic partnership with Accenture. The aim is to collaborate on research in, and real-world application of, data science, analytics and AI, with a focus on delivering tangible business and societal value. A key pillar of the partnership involves conducting joint research. As part of this, the Turing issued an open call for new research projects in mid-2021. I applied and was lucky enough to have my project chosen for sponsorship.
Can you share more about what your project will be exploring?
We’ll be looking at how new technologies (specifically electric vehicles [EVs]) and lifestyle patterns (including a rise in homeworking) will impact energy and transport demand in cities. To do this, we plan to develop dynamic digital twins of existing and planned energy and transport infrastructure. The digital twins will also include real-time monitoring of transport and energy network conditions and demand, plus agent-based simulations of transportation and domestic energy usage.
How do dynamic digital twins differ from your average digital twin?
A conventional digital twin is an accurate digital representation of something that exists in the real world: in this case, transport and energy infrastructure networks. Our dynamic digital twins add three new dimensions to that: 1) the behaviour of the individuals who interact with infrastructure networks; 2) the interactions between flows (of people, goods, energy, data, etc.) in a system; and 3) the physical response of infrastructure to loads and hazards.
Incorporating these dynamic dimensions makes it possible to investigate complex counterfactual scenarios with our digital twins. So, we can make more human-centric predictions about how infrastructure networks will respond to both planned and unplanned changes. And, because of this, we can use the dynamic digital twins as a policy planning tool rather than just an infrastructure management tool.
What kinds of planning do you hope to support with your research?
The key application is to help energy and transport network operators understand how EV penetration rates and flexible working policies impact demand for their services. With this, they can perform better long-term strategic planning, network management, and sustainability and resilience analysis.
Beyond that, there are all kinds of potential planning and analytical applications. Our research could help EV charging station operators decide where to deploy new charging points. Government could use it to test different scenarios around their plans to transition to an emissions-free vehicle fleet by 2050. It could also help inform future public transportation investments, flexible working policies, and electricity pricing strategies.
What’s been a career highlight so far?
I think my proudest moment was when one of my fellow researchers on this project, Gael Lederrey, was awarded his PhD earlier this year. I was a co-director of his thesis and he passed his viva just after I started my current position as a lecturer at UCL, which makes this transition extra special. I'm really excited to enter this new phase of being able to lead and supervise research.
And finally, when not working what can you be found doing?
I moved to London a few months ago from Lausanne in Switzerland (where I was working as a postdoc at EPFL) so a lot of my free time has been taken up by the move. I enjoy keeping active – I did a lot of outdoor activities in Switzerland and am hoping to get back into playing rugby now I am back in London. I’ve also started high diving at my local pool, which is a good adrenaline rush!