Andrew received a BSc in control engineering from PUC-RIO and a BSc in general engineering from École Centrale de Marseille. He also holds a master's in Electrical Engineering with an emphasis on Operation Research, focusing on Power Systems and Energy markets. Some of his previous projects revolve around energy economic dispatch analysis and simulation, financial data classification and portfolio optimization. His main interests are optimization, decisions under uncertainty and machine learning.

Branwen did her PhD in Geophysics at Imperial College London, where she used an array o computational fluid dynamics models to research landslide-tsunami hazard. Along the way she explored uncertainty quantification and machine learning methods for natural hazard assessment. She is interested in building and using modelling tools to better understand the natural world and other complex systems.

Chris was formerly an Assistant Professor in Energy Informatics and Modelling at the University of Groningen. He received his PhD at the Delft University of Technology, and his work covers topics related to Energy, Sustainability, Linked Data, Machine Learning, Data Visualisation, and Agent-Based Modelling. Here are a few papers published by Chris: 1. Secondary Resources in the Bio-Based Economy: A Computer Assisted Survey of Value Pathways in Academic Literature 2. Electric vehicle charging in China’s power system: Energy, economic and environmental trade-offs and policy implications 3. The state of the states: Data-driven analysis of the US Clean Power Plan For the rest of Chris' published work, please refer to his Google Scholar profile.

James is a senior researcher at Invenia and a PhD student studying machine learning at the University of Cambridge in the Computational and Biological Learning Lab, under the supervision of Dr. Richard Turner. His interests include Bayesian optimisation, learning, approximate inference methods, and deep generative models. He previously completed a master’s in machine learning, speech, and language technology at the University of Cambridge under the supervision of Dr. Zoubin Ghahramani and a master’s of mathematics from the McGill University under Daniel Wise.

Josh is a former professor and honorary fellow of the University of Birmingham, and has previously held Marie Curie and David Phillips Fellowships at the Free University of Brussels and the University of Manchester, respectively. He is interested in developing robust algorithms for optimization, optimal control and decision making, particularly for problems involving multiple objectives, uncertainty, dynamical aspects (including interruptions), and human interaction. He is also interested in the ethical use of optimization and machine learning.

Miha, originally from Slovenia, is a theoretical physicist by training and holds an MSci degree from Imperial College London. After completing his Masters, he moved to the countryside to pursue a PhD at the University of Oxford where he analysed the data from the Large Hadron Collider at CERN searching for a rare decay of the Higgs boson. He likes python, boosted decision trees, and Federer's one-handed backhand.

Thomas is a graduate student in Energy Systems and Data Analytics at University College London and will be carrying out his research thesis in collaboration with Invenia Labs. He previously completed his undergraduate studies at Heriot-Watt University in Chemical Engineering, with a primary focus of biochemical process design. His research interests lie in the application of machine learning and data analytics to facilitate climate change mitigation and enhance the sustainability of energy systems, with particular passions for grid decarbonisation and power systems optimisation.