Meet our Team
The MaaSlab is one of the leading research teams on new mobility services gathering cutting edge innovative knowledge and insights for use in mobility services design, transport planning, and policy. Researchers from different disciplines, such as transport modelling, data and computer sciences, mathematics, and economics merge their powers to deliver cutting edge research regarding the technology, the data, the business models and the demand management needed for the digital era in the transport sector.
Research and Academic Staff
Professor of Transport & Energy
Maria is the Head of MaaSLab. She is an expert in the MaaS concept. Her work mainly focuses on MaaS product design and pricing, demand and supply analysis, and business models. She has extensive experience in consumer choice modelling, big data handling, survey design and transport modeling. She is a Professor in Transport & Energy at UCL Energy Institute.
Lecturer in Transport Modelling and Machine Learning
His research focuses on modelling and simulation of transportation systems, including conventional and emerging transportation systems, demand modelling, and machine learning in transportation.
Research Fellow in Transport Modelling
Jishnu’s research focus on transport systems modeling with a focus on planning and operations of public transport and emerging mobility systems, their dynamics with users (demand-supply interactions with equilibrium models), crowd behavior modeling (wayfinding/route-choice and evacuation modeling), and the application of such models to make transport systems more efficient and sustainable.
Research Fellow in Transport Modelling
Position to be advertised soon
Energy Demand Modeller
Andreas is Professor of Energy and Transport, previously Director of Research at the Bartlett School of Environment, Energy and Resources, and a Visiting Professor at Stanford University. He is an expert in energy demand for transport.
Sridhar is a software developer. He has extensive experience in the urban mobility domain building mobility-related apps and handling big data. He has a software engineering background having worked in the industry for more than 12 years. He is a Research Assistant at UCL Energy Institute.
Kuba's expertise focuses on modelling demand for transport. His work centres around big data, new mobility services and sustainable transport. He has a background in economics and planning and is currently a Doctoral Researcher at UCL Energy Institute
Dimitris’ expertise focuses on modelling the dynamics of travel behaviour for demand forecasting within a new mobility services environment. His work is based on machine learning (ML) techniques, Markov decision processes (MDPs) and dynamic discrete choice models (DDCMs). He has an engineering background with plentiful experience on optimization modelling and is currently a Doctoral Researcher at UCL Energy Institute.
Transport Policy Analyst
Anne’s research centres around public policy development and standardization of implementation of new mobility services. Her background is in program management and functional solution architecture design for public transport technologies, working in the industry for over 15 years. She is a Doctoral Researcher at UCL Energy Institute.
Weijian’s expertise focuses on analysing travel behaviour developments and forecasting travel demand based on new mobility services. He has a background in transportation modelling and big data analysis and is currently a Doctoral Researcher at UCL Energy Institute.
Research and Business Development Manager
Dr Georgia Kouta is the Research and Enterprise/Business Development Manager of MaaSLab at the Energy Institute in UCL. Prior to joining MaaSLab, Dr Kouta has professional experience in Academia, Government and Private Companies. She is instrumental in bringing together academia, industry and government departments effectively, by facilitating and contributing to the development of stakeholder relations and collaborative networks. Georgia is skilled in Public Affairs, Communication, International Relations and Research Management.