AI Kevin Quinlan

Kevin has been nominated due to his enthusiasm and role in driving analytics in ESB which could have a long-term impact on the energy system and climate in Ireland. In the time since he joined ESB, Kevin has delivered numerous high value projects across the company, across a range of different technologies. The Deployment, Planning and Reporting tool he developed for the Smart Metering project is the primary tool to distribute areas for installers to operate in and to install almost 3 million smart meters across the country. This was awarded an ESB Innovation Award and Kevin was nominated as Star performer on the smart metering project, which at the time was the largest IT project in the UK and Ireland and second largest in Europe. In addition, Kevin has delivered a series of complex Tableau & Power BI dashboards across all ESB business units; Corporate Group, Networks, Generation & Trading and Enterprise Services functions. More complex data science solutions that Kevin has delivered include the multi-award-winning Smart IDM project in Networks in which he built a fully integrated enterprise application comprising of a computer vision application to automate the auditing of smart meter installations. Installers would take 4-5 images of the installation from different perspectives. These images are then fed into an Azure hosted computer vision model that would identify the type of meter, the cut-out type, if all the safety features were included and read the opening and closing reads of the meter. This project was nominated at the Analytics Institute Awards, at which Kevin also presented. This was awarded Best Use of RPA and Automation at the 2019 AI Awards and won an ESB Award in 2020.

Computer Vision is a particular passion of Kevin’s having won the Microsoft Image Processing OpenHack in 2018. Kevin is delivering further computer vision projects in ESB, such as the LV (Low Voltage) Mapping project, which is a model that “walks” through Google Street View to classify and identify utility poles and map the LV network in Ireland which is a regulatory requirement by the Commission for the Regulation of Utilities (CRU). The project allows ESB to not only complete a network that is currently less than 2% mapped, but also creates a store of pole images which can be used to detect for additional issues like leaning poles or damage.

He is also currently working on identifying domestic solar panels from satellite imagery to map the solar network in Ireland, which will support Networks’ planning of the solar integration to the Irish grid. Kevin is working alongside ESB Networks and their drone pilots to ensure footage meets GDPR requirements by blurring any discerning background imagery and allow technicians to store and review footage. Further AI models will then be developed to pinpoint vegetation encroachment, rust or damage to equipment and to create more accurate maps of the network. Kevin is also using computer vision to classify high voltage towers from satellite imagery to determine which towers are a risk to the public and require more security. Kevin has also delivered projects in the machine learning space, particularly for Energy Trading where he delivered a Gated Recurrent Unit (GRU) model for the forecasting of BSUoS price and other forecasting models for the Irish and UK energy markets. Kevin has also delivered Natural Language Processing (NLP) products to assess survey responses, filter CVs and analyse job specs.

Not only does Kevin promote AI and Data Science through the quality of his work, but he also understands that alone is not enough to bring the business along on the journey. In 2019 he established the Data Culture Committee (DCC) in ESB, which seeks to educate the business on the benefits of AI and Analytics, celebrates the work being done across analytics and promote self-serve analytics within the business. The committee organises several events each year, the highlight being Analytics Week, a weeklong celebration of the work completed by the analytics team plus having guest presentations by AI leaders from across the globe. In 2021, there were 8 presentations across the week, with a total of over 1000 attendees across all events. To promote self-serve analytics in the business, there were also competitions and dashboard clinics, where the business could bring dashboards which they had developed themselves to the analytics experts, including Kevin, for advice and guidance. Hackathons are also organised by the DCC, for both graduates and the wider business. In this way, non-analytics staff can learn the tools and techniques involved in developing analytical products and deliver a product that the business can use. Kevin hosts a monthly Analytics Lean Coffee session which is a structured, agenda-less meeting where analytics staff can discuss issues affecting their daily work and seek advice from their colleagues, which has become harder to procure since the move to hybrid working. These collaboration initiatives and events were highlighted as being key to the recent Team of the Year win by the ESB Analytics team at the 2022 Analytics Institute Awards.

Kevin also drives innovation within ESB, and regularly presents to the wider business on potential AI initiatives that could be implemented. He has also taken a leading role in the move to Azure cloud for machine learning activities and for driving agile development, including hosting regular analytics retro sessions and delivering knowledge sharing on new technologies. Kevin is a Safety Champion, LinkedIn Champion, was Chair of the CIO Comms Committee and part of the ESB Safe & Sound Leadership team, where he is working on making smart and hybrid working something that benefits both the individual and the company. Mentorship of younger staff members is also crucial for Kevin, and he is currently mentor to an undergraduate student and a graduate staff member.

Thus, Kevin has been nominated, not just for the quality of his work, but for also his enthusiasm and drive in establishing analytics within ESB and commitment to making ESB a digital utility.