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Caitlin is a Consultant within the Mathematical Modelling and Optimisation team. Caitlin joined decisionLab after completing her EngD thesis on modelling wave energy converters as part of the IDCORE program. Her initial master’s degree is in Aerospace and Aerothermal engineering from the University of Cambridge.

Chris heads up the data science team, working across the full spectrum of data science, from requirements gathering and data exploration, through to building production ready machine learning pipelines and innovative applications of reinforcement learning. Chris helps ensure we extract maximum value from data and build robust and reliable predictive models.

Christina is a senior data scientist with >2 years’ experience in designing & deploying custom production-ready Machine Learning (ML) solutions.

Damien is a DRL Engineer with a background in Mechatronics. His area of expertise is agent optimisation in environments with partial observability along with research into intrinsic motivation. He has significant international experience in the automotive industry and has lead development on projects on the forefront of Digital Transformation.

David co-founded decisionLab 2011 and is now a MD. Although the decision sciences landscape has evolved rapidly over this time, his mission remains the same: to help our clients grow their business through more effective decision making.

Dom Weldon is a Principal Software Engineer. Dom’s team works with data scientists and consultants to develop models and turn them into production ready tools.

Devika’s academic background includes degrees in physics and environmental modelling, which gave her a good understanding of fundamental modelling and optimisation principles. She has worked on a variety of interesting projects, including modelling river catchment hydrology,

Despoina is a consultant within the Mathematical Modelling & Optimisation team. She holds an M.Sc in Chemical Engineering from Imperial College London and has an extensive research experience in the area of investment modelling and supply chain optimisation for personalised medicinal products.

Ian oversees the running of the business and its strategic development. With a career in science and technology spanning 25 years and multiple sectors, he maintains his passion for creating innovative and exciting solutions that have an impact.

Kelvin is a consultant with an extensive background in Rail. He worked on major rail infrastructure projects as a system, track and simulation engineer.

Dr Kevis Pachos holds a Ph.D in Environmental Engineering with application to water resources management. His area of expertise is the implementation of adaptive modelling approaches for water resources planning given multiple uncertainties, used to optimise decisions such as how much to invest in water conservation and the construction of reservoirs, transfers, wastewater reuse and desalination plants.

Panagiotis is an experienced mathematical modeller, specialising in Machine Learning and Optimisation in order to solve operational problems in a variety of sectors, such as water, utilities, aerospace and others. He holds an M.Sc. in Operational Research & Business Analytics from Lancaster University.

Peter is a simulation modeler with a background in Mathematics. He has built agent-based, discrete event and system dynamics simulations for a wide range of industries, including: pharmaceutical, food and defence.

Polina wishes to identify as a cerebral social scientist one day and is now part of the Business Support Team at decisionLab. She is helping for the smooth running of our London office, and also contributes to some of the business development activities across departments.

Rachel is a highly experienced Senior HR Consultant, with extensive employment law knowledge, providing jargon free and commercial HR advice. Rachel prides herself on her ability to seek calmness in a storm, nipping problems in the bud before they become full blown nightmares. She listens carefully, rapidly understands issues and quickly follows up with clear analysis of situations with succinct options and routes to available solutions.

She is a decision and risk analyst, specialising in Multi-Criteria Decision Analysis (MCDA) and her expertise lies in supporting decision making with conflicting objectives and multiple stakeholders, and large and difficult to quantify uncertainties. Her work and research include projects to support policy making in a diversity of contexts and applications.

With background in agent-based modelling and analytics, Joy develops simulation models at Decision Lab. She is passionate about modelling human behaviour and processes, and has extensive experience in behaviour analytics and workplace simulation.