Tabea Sonnenschein is a Researcher at Utrecht University , affiliated with the Faculty of Geosciences and Human Geography and Spatial Planning . She is also a PhD Candidate in the Department of Population Health Sciences under the Faculty of Veterinary Medicine . Her work bridges environmental science, urban planning, and public health through advanced computational modeling. Coordinated EU-funded EXPANSE (Horizon 2020) and EXPOSOME-NL (NWO) projects. Research Associate at the MRC Epidemiology Unit at University of Cambridge, contributing to DARe Hub and UBD Policy initiatives. Research Interests Air Pollution and Health: Modeling health impacts of urban pollutants. Agent-Based Simulation: Developing tools like GenSynthPop and CellAutDisp . Urban Sustainability: Assessing interventions for resilient, low-emission cities. Recent Publications highlight her work on urban exposome, synthetic population modeling, and subway expansion impacts. She contributes to journals like Environmental Modeling and Software , Autonomous Agents and Multi-Agent Systems , and Semantic Web .
Günter Schneckenreither is a researcher affiliated with the Computational Statistics research area at Technische Universität Wien (TU Wien). His work spans interdisciplinary applications of computational methodologies to epidemiology, public health, and biomedical modeling, with a focus on agent-based simulations and cellular automata. Research Interests: Heterogeneity in disease transmission, age-dependent SIR models, synthetic data generation for pandemics, and fractional diffusion processes in structured populations. Publications: Recent research includes epidemiological modeling of SARS-CoV-2 immunization levels, melanocytic proliferation simulations, and comparative studies of epidemic modeling frameworks. Projects: Active participant in ARGESIM benchmark studies, integrating cellular automata and differential equations for epidemic simulations. Methodologies: Specializes in dynamic causal modeling, fractal topological structures, and multiplex social network analysis.
Dr. Georges Kesserwani is a Senior Lecturer in Water Engineering at the School of Mechanical, Aerospace and Civil Engineering , University of Sheffield. His work bridges flood risk modeling , hydrodynamic simulations , and agent-based modeling to advance automated flood mapping and forecasting. He holds an EPSRC Early Career Fellowship (2018–2024) and has organized international workshops on flood modeling. Research Interests: He develops computational methods to integrate fluid mechanics , uncertainty quantification , and human behavior in flood scenarios. Current projects include GPU-accelerated flood models Agent-based evacuation dynamics Multiwavelet terrain filtering Two-way pedestrian-floodwater interaction Scientific Contributions: His publications reveal trends in Hybrid numerical-data-driven flood simulation Uncertainty propagation in multi-hazard environments Agent-based modeling of urban evacuation Experimental validation of flow-structure interactions Awards: ASCE’s 2024 Best Reviewer Award EPSRC Early Career Fellowship DAAD Visiting Fellowship (2013–2014) Teaching & Leadership: Dr. Kesserwani teaches hydraulics , hydrology , and computer modeling to water engineering students. He leads the Water - Environmental Fluid Mechanics research group and co-organized the 2024 Advances in Flood Modelling workshop.
Professor Charisma Choudhury is a Chair in Behaviour Modelling at the Institute for Transport Studies, University of Leeds. She leads the Choice Modelling Research Group and serves as Deputy Director of the interdisciplinary Choice Modelling Centre. Her expertise spans travel behaviour modelling, discrete choice analysis, and big data applications in transportation systems, particularly in the Global South. Her research focuses on integrating data science, ubiquitous computing, and choice modelling techniques using innovative data sources like mobile phone records, smart cards, and physiological sensors. She has collaborated extensively with Southeast Asian institutions, including projects with Indonesian students and prior traffic microsimulation work in Malaysia. She holds a PhD and MSc from MIT, where her pioneering driving behaviour models were incorporated into commercial tools like AIMSUN and VISSIM. Interests: Behaviour Modelling, Big Data, Developing Countries, Traffic Microsimulation Leadership: Choice Modelling Research Group, Deputy-Director of Choice Modelling Centre Collaborations: Beijing Jiaotong University, Alan Turing Institute Scientific accolades include the Gordon Newell Best Dissertation Prize, Faculty for Future Award, and UKRI Future Leader Fellowship. She supervises PhD students and has previously mentored researchers in Bangladesh, India, and Malaysia, with projects ranging from ride-hailing energy impacts (INFUZE) to agent-based simulations (NEXUS, TOZCA).
Joshua M. Epstein is Professor of Epidemiology at New York University, with affiliations in the Courant Institute of Mathematical Sciences and the Wolff Family Department of Politics. He is founding Director of the NYU Agent-Based Modeling Laboratory and External Faculty Fellow at the Santa Fe Institute. Since 2025, he has also been a member of the External Faculty at the Complexity Science Hub. His work bridges computational modeling, social science, and public health. BA, Amherst College Ph.D., Massachusetts Institute of Technology (MIT) Epstein is a pioneer in agent-based modeling , focusing on generative social science, complex systems, and nonlinear dynamics. His research explores how macro-level social phenomena emerge from micro-level individual behaviors. Key domains include infectious disease spread, financial contagion, obesity diffusion, and social innovation. He emphasizes computational approaches to understanding societal mechanisms and policy implications. His recent publications reflect a consistent focus on generative modeling , complex adaptive systems , and interdisciplinary simulation . Themes across his work include emergence, contagion (biological and social), cognitive foundations of behavior, and the limits of prediction in social systems. His modeling spans epidemiology, economics, and cognitive science, demonstrating the versatility of agent-based methods. Notable scientific awards include: NIH Director’s Pioneer Award Honorary Doctorate of Science from Amherst College Epstein has led major research initiatives, including the Johns Hopkins Center for Advanced Modeling and the NYU Agent-Based Modeling Laboratory. He has advised numerous research projects and secured significant grants supporting computational social science. His books, such as Growing Artificial Societies and Agent_Zero , have shaped the field. Future work continues to explore neurocognitive agents and real-world policy applications. He leads the NYU Agent-Based Modeling Laboratory, a hub for developing and applying agent-based models to pressing societal challenges. The lab fosters interdisciplinary collaboration across public health, political science, economics, and computer science.
Tiziana Assenza is an Associate Professor of Economics at the Toulouse School of Economics , affiliated with Toulouse 1 Capitole University. Her research bridges theoretical models and observed economic behavior through experimental and computational methods. Current focus areas: Monetary policy communication, economics of disinformation, and household decision-making under uncertainty. Teaches Ph.D.-level Behavioral Macroeconomics and Agent-based Modeling courses at TSE and other European institutions. Her work explores how heterogeneous expectations shape macroeconomic outcomes, using lab and online experiments. Recent projects analyze fake news impacts on business cycles and cognitive load during crises. Contact: tiziana.assenza@tse-fr.eu
Andreas Pollak is an Associate Professor and Graduate Supervisor in Economics at the University of Saskatchewan's College of Arts and Science. His research focuses on macroeconomic dynamics, quantitative methodologies, and labor market policies. He investigates how unemployment insurance systems impact business cycles and human capital development, while also exploring the relationship between R&D investment and economic growth. Research interests include: Macroeconomic modeling of unemployment Quantitative analysis of labor markets Impact of employment insurance on skill retention R&D-driven economic convergence His publications demonstrate consistent focus on labor economics and growth theory, utilizing advanced econometric techniques to analyze policy impacts across diverse economic contexts. Recent work examines technological innovation's role in sustainable development. Dr. Pollak actively supervises graduate students in economics and contributes to departmental leadership through his graduate supervision role.
Dr. Gudrun Wallentin serves as Associate Professor for Geoinformatics and Ecology at the Department of Geoinformatics (Z_GIS) within the Faculty of Natural and Life Sciences at the University of Salzburg. She is Program Director of the UNIGIS distance learning programs and heads the Research Group "Spatial Simulation". Her academic work bridges ecological theory with advanced spatial modeling techniques. Dr. Wallentin's research focuses on spatial simulation in ecology , individual-based modeling , and complex systems . Her work integrates geographical information science with ecological modeling to understand spatial patterns and processes in natural and urban environments. She has developed innovative approaches to model ecological dynamics, animal behavior, and urban transportation systems using agent-based and hybrid modeling frameworks. Analysis of her publication record from 2008-2017 reveals consistent research themes centered on spatial modeling approaches applied to ecological and urban systems. Her work demonstrates a progression from ecological modeling (particularly alpine tree line dynamics and invasive species) toward urban applications (especially bicycle traffic and safety), while maintaining a strong methodological focus on individual-based and agent-based modeling techniques. The interdisciplinary nature of her work spans ecology, computer science, transportation engineering, and geography. Dr. Wallentin actively contributes to the academic community through service roles including Guest Editor for the ISEM 2019 special issue in "Ecological Modelling" and membership on program committees for major conferences such as AGILE, AGIT, and GI_Forum. As Program Director for UNIGIS, she oversees distance learning programs in Geographical Information Science and Systems, and supervises master's theses across multiple programs including Geography, Applied Geoinformatics, and Ecology. Her teaching portfolio includes courses on Spatial Simulation, Modeling Geographical Systems, and GIS applications in ecological research. She leads the "Spatial Simulation" research group, which focuses on developing and applying individual-based modeling approaches to complex spatial systems, with particular applications in ecological dynamics and urban transportation networks.
Nick Malleson is a Professor of Spatial Science and Cluster Leader of the Institute for Spatial Data Science (ISDS) at the School of Geography, University of Leeds. His research integrates computer science, statistics, and machine learning to address social issues with strong geographical dimensions. Research Interests: His primary focus lies in agent-based modelling (ABM), geographical information science (GISc), and urban simulation. He applies these techniques to domains such as criminal justice, urban mobility, public health, and environmental policy. His work emphasizes data-driven simulation and the integration of novel 'big data' sources. Recent Research Trends: His recent publications and projects reveal a strong trajectory in enhancing ABMs with real-time data assimilation, integrating large language models (LLMs) for spatial reasoning, and applying simulation to urban health and sustainability. Projects like DUST and SURF exemplify his focus on dynamic, realistic urban simulations for policy impact. Royal Geographical Society (RGS) Gill Memorial Award ERC Starting Grant (€1.5M) – DUST ESRC Future Research Leaders Grant (£312k) – SURF Supervision & Grants: Malleson supervises postgraduate researchers and leads major interdisciplinary grants involving collaboration with police, local government (e.g., Leeds City Council), and other universities. His work often involves co-production of knowledge and the development of tools for policy evaluation. He leads research strands in the Consumer Data Research Centre and the N8 Policing Research Partnership. Labs & Teams: He is central to the Institute for Spatial Data Science (ISDS) at Leeds and leads the SURF and DUST research teams. His GitHub presence indicates active software development for urban analytics and crime modelling.
Mike Bithell is a Researcher in the Department of Geography at the University of Cambridge. His work focuses on numerical modeling of spatially distributed systems, including fluid flow, atmospheric physics, climate-ecosystem interactions, and socio-economic processes. Member of the Climate and Environmental Dynamics group Member of the Biogeography and Biogeomorphology group Recent projects address agent-based modeling applications in rangeland health, disease transmission, global ecosystems, and scree dynamics. His publications highlight interdisciplinary collaborations in computational simulation and environmental science, with a methodological emphasis on agent-based modeling and geospatial analysis.
Dr. Ali Parsa is a Research Fellow specializing in Food Systems Modelling at the University of Southampton. Previously affiliated with Coventry University's Centre for Agroecology, Water, and Resilience (CAWR), he develops integrated models combining system dynamics, agent-based, and microsimulation approaches to analyze environmental and socio-economic impacts in agri-food systems. Key research themes: Circular economies Methodologies: System dynamics modeling Policy focus: Sustainable food waste management Geographic scope: Urban systems His recent publications explore food waste hierarchies, nexus approaches, and synthetic population modeling for agricultural policy analysis. Current work evaluates environmental land management schemes through computational models. Scientific recognition includes: Prestigious Chevening Scholarship recipient Founder of award-winning NGO Rainbow Social and Cultural Organisation Ali's research bridges computational modeling with policy development for sustainable development initiatives targeting youth engagement and agricultural resilience.
Dr Wendy J Harrison is Associate Professor in Biostatistics at the University of Leeds’ School of Medicine, based in the Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) and the Specialist Science Education Department. Since arriving as Lecturer in 2007 she has led quantitative teaching across MBChB and postgraduate programmes, and now directs the Health Informatics with Data Science MSc launched in 2022. Education & Qualifications PhD Latent Variable Modelling for Complex Observational Health Data (part-time, awarded 2017) PGCLTHE – Postgraduate Certificate in Learning and Teaching in Higher Education (2011) MSc Medical Statistics, University of Leicester BSc(Hons) Combined Studies Mathematics / Physics Research Interests Her methodological work focuses on causal inference techniques—especially directed acyclic graphs (DAGs), multilevel and latent-class / latent-variable modelling—for analysing complex observational health data. Applied domains include obesity, cancer epidemiology and paediatric cardiology. She uses insights from this research to embed contemporary quantitative methods into undergraduate and postgraduate medical education. Publications Snapshot Across 15 recent papers (2008-2021) three cross-cutting themes emerge: development and teaching of DAG-based causal inference tools, evaluation of multilevel latent-class methodologies via simulation and real data, and collaborative epidemiological studies in cancer, cardiology and perinatal health. These outputs underline a commitment to both advancing and disseminating robust statistical practice. Professional Memberships Fellow of the Royal Statistical Society (GradStat) Fellow of the Higher Education Academy (FHEA) Leadership & Administration She currently serves as Programme Lead for Postgraduate Programmes in Health Informatics with Data Science, Admissions Lead for all postgraduate programmes in her department, and Chair of the Postgraduate Special Circumstances Committee.
Dr. C. Anna Spurlock is a Researcher at the University of California at Berkeley , working within the Sustainable Energy and Environmental Systems Department at Lawrence Berkeley National Laboratory. As a Deputy Department Head and head of the Berkeley Lab Sustainable Transportation Initiative, she leads projects like the DOE-funded BEAM CORE and the Geo-Economic Multi-Modal Systems (GEMS) Model. Her work bridges behavioral economics with advanced data science to analyze consumer decision-making in transportation and energy efficiency policy. Education: PhD in Agricultural and Resource Economics, University of California at Berkeley (2013) MS in Agricultural and Resource Economics, University of California at Berkeley (2009) BA in Anthropology, University of California at Santa Cruz (2002) Research interests span transportation equity , machine learning for mobility modeling , and energy justice frameworks . Her publications focus on autonomous vehicles, fleet turnover, and the intersection of life events with mobility patterns. Articles address topics like probe vehicle data analysis , CO2 emissions reduction , and gender disparities in transportation . Scientific Awards: 2021 Spot: Team Workforce Development Award 2018 Director’s Award for Exceptional Achievement: Diversity 2017 Early Career Development LDRD Award 2017 CUCSA Kevin McCauley Memorial Outstanding Staff Award She has advised research teams on projects such as the WholeTraveler initiative under DOE SMART Mobility and founded the Behavior Analytics research initiative at LBNL. Her work includes collaborations with DOE programs , data-driven policy evaluation , and advocacy for diversity and inclusion in academic institutions.
Professor Taha Hossein Rashidi is a leading expert in Transport Engineering at the School of Civil and Environmental Engineering, University of New South Wales (UNSW), and a member of the Research Centre for Integrated Transport Innovation (rCITI). His work bridges disciplines like economics, statistics, urban design, and sustainability to advance smart-city solutions. Education : PhD, University of Illinois, Chicago (2011); MS Civil Engineering, Sharif University of Technology (2005); BS Civil Engineering, Sharif University of Technology (2003). His research focuses on travel behaviour analysis, activity-based travel demand modelling, integrated land use and transportation models, and autonomous driving technologies. He leads the rCITI Travel Behaviour Modelling Team, which includes 3 Post-docs, 7 PhD, and 3 MSc students. Recent work explores shared autonomous vehicles, social media data integration for transport models, and dynamic ride-sharing systems. His publications span topics like pedestrian demand modeling, residential relocation dynamics, and pandemic-related travel restrictions. Scientific Awards Fred Burggraf Award (TRB, 2008) Dwight Eisenhower Fellow (2008) ASCE Freeman Fellowship (2009) NSERC PDF Award (2012) Industrial RAND Fellowship (2012) Vice Chancellor’s Award for Teaching Excellence (2015, Team) Award for Engineering Education Engagement (2015, Team) Outstanding Paper (TRB Analytics Contest, 2017) He has secured over $1.2 million in research funding since 2007, including ARC DECRA and Linkage Grants. His teaching includes courses on geometric design, urban transport modeling, and transport econometrics.
Ridhi Kashyap is an Associate Professor of Social Demography at the University of Oxford and a Professorial Fellow at Nuffield College. She is based at the Leverhulme Centre for Demographic Science where she co-leads the Digital and Computational Science strand. Her work bridges traditional demographic methods with computational approaches and digital data sources to address pressing population issues. Her research interests span multiple areas of demography including population health, gender inequality, family dynamics, migration, and the impacts of digital technologies on demographic outcomes. She has made significant contributions to understanding the demographic manifestations of son preference, the relationship between educational expansion and marriage patterns, and the social and demographic impacts of the COVID-19 pandemic. Her methodological interests focus on computational approaches such as agent-based models, microsimulation, and machine learning, as well as leveraging new data streams from digital trace data. Analysis of her recent publications reveals a strong thematic focus on the intersection of digital technology and demographic processes. Her work consistently examines how digital technologies impact population health, gender equality, migration patterns, and social inequalities. A significant portion of her recent research addresses pandemic-related mortality and health outcomes, while maintaining her longstanding interest in gender disparities within demographic processes. Her methodological approach increasingly incorporates computational techniques and novel data sources like social media to address demographic questions. Ridhi Kashyap actively contributes to the field through her leadership in the Leverhulme Centre for Demographic Science and her work on platforms like digitalgendergaps.org, which uses social media and survey data to monitor global digital gender inequalities related to Sustainable Development Goals. Her research has important implications for policy in areas of gender equality, digital inclusion, and population health.
