I am a computational archaeologist with a strong background in humanities and social sciences, specialising in simulating socioecological systems from the past.

My main concern has been to tackle meaningful theoretical questions about human behaviour and social institutions and their role in the biosphere, as documented by history and archaeology. My research focuses specifically on how social behaviour reflects long-term historical processes, especially those concerning food systems in past small-scale societies. Among the aspects investigated are competition for land use between sedentary farmers and mobile herders (Angourakis et al. 2014; 2017), cooperation for food storage (Angourakis et al. 2015), origins of agriculture and domestication of plants (Angourakis et al. 2022), the sustainability of subsistence strategies and resilience to climate change (Angourakis et al. 2020, 2022). He has also been actively involved in advancing data science applications in archaeology, such as multivariate statistics on archaeometric data (Angourakis et al. 2018) and the use of computer vision and machine learning to photographs of human remains (Graham et al. 2020).

As a side, but not less important interest, I had the opportunity to learn about video game development and engage with professionals in Creative Industries. In one collaborative initiative, I was able to combine my know-how in both video games and simulation models (\href{https://doi.org/10.1007/978-3-030-92843-8_15}{Szczepanska et al. 2022}).

Lu Ping is a dedicated researcher in interdisciplinary fields including artificial intelligence (AI), digital economy, technological innovation, and industrial economics. Currently serving as an Associate Research Fellow at the China Academy of Information and Communications Technology (CAICT), Lu Ping focuses on examining the impacts of digital technologies (e.g., AI, big data, and IoT) on economic growth, industrial ecosystems, policy formulation, and societal ethics through multidimensional data modeling and empirical research.
Representative Academic Contributions:
1. AI Development and Societal Implications
A Brief History of Artificial Intelligence Development in China (2017): Explored the technological evolution and policy-driven pathways of China’s AI industry.
Ethical Dilemmas Faced by AI Algorithms (2018): Analyzed ethical challenges such as algorithmic bias and data privacy, proposing governance frameworks.
A Brief History of the Evolution of Smart Hardware in China (2018): Systematically reviewed the technological iterations and market dynamics of China’s smart hardware sector.
2.Technological Innovation and Industrial Economics
An Empirical Analysis of Technological Innovation Driving Growth in Internet Companies: Evidence from A-Share Listed Internet Firms in Shanghai and Shenzhen (2019).
Research on Competitiveness Measurement of Frontier Emerging Industries Based on Data Envelopment Analysis (DEA) Models (2019).
3.Digital Economy and Market Behavior
Correlation Analysis of Crowdfunding Behavior and Funding Performance for Internet Products: A Bayesian Approach Based on JD.com Crowdfunding Data (2018): Uncovered nonlinear relationships between user participation and project success rates using crowdfunding platform data.
Analyzing the Effects of Developer and User Behavior on Mobile App Downloads (2019): Built predictive models for app market performance based on user behavior data.
4.Policy Simulation
General Equilibrium Analysis of Beijing’s Water Supply and Consumption Policies: A Computable General Equilibrium (CGE) Model-Based Approach (2015).
Impact Analysis of EU Food Safety Standards on China’s Food Industry: A Dynamic Global Trade Analysis Project (GTAP) Model-Based Study (2015).
Academic Contributions:
Pioneered interdisciplinary paradigms in industrial economics research by integrating perspectives from econometrics, data science, and sociology. Published high-impact research in AI ethics, digital economy policies, and resource-environmental economics, providing decision-making references for academia and policymakers.

Furkan Gürsoy received the BS in Management Information Systems from Boğaziçi University, Turkey, and the MS in Data Science from İstanbul Şehir University, Turkey. He is currently a PhD Candidate at Boğaziçi University. He previously worked as an IS/IT Consultant and a Machine Learning Engineer with the industry for several years. He held a Visiting Researcher Position with IMT Atlantique, France, in 2020. His research interests include complex networks, machine learning, simulation, and broad data science.

I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.

I graduated Bachelor and Master studies at the University of Warsaw, obtaining the diploma in biology at College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences (MISMaP). After graduation I worked as a freelancer in data science and statistics, then worked for 2 years as a data scientist in an IT startup and now I am working as a statistician in The Polish National Information Processing Institute (OPI PIB) in a group analysing condition of science and higher education in Poland. My interests: agent based modelling, evolutionary ecology, statistics, data science, sociology of science.

Peter Gerbrands is a Post-Doctoral Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure for FIRMBACKBONE. He teaches data science courses: “Applied Data Analysis and Visualization” and “Introduction to R”. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In Fall 2023, he is a Visiting Research Scholar at SUNY Binghamton in NY.

Prof. Christian E. Vincenot is by nature an interdisciplinary researcher with broad scientific interests. He majored in Computer Science / Embedded Systems (i.e. IoT) at the Université Louis Pasteur (Strasbourg, France) while working professionally in the field of Computer Networking and Security. He then switched the focus of his work towards Computational Modelling, writing his doctoral dissertation on Hybrid Modelling in Ecology, and was awarded a PhD in Social Informatics by Kyoto University in 2011 under a scholarship by the Japanese Ministry of Research. He subsequently started a parallel line of research in Conservation Biology (esp. human-bat conflicts) under a postdoctoral fellowship of the Japanese Society for the Promotion of Science (JSPS) (2012-2014). This led him to create the Island Bat Research Group (www.batresearch.net), which he is still coordinating to this date. In 2014, he was appointed as the tenured Assistant Professor of the Biosphere Informatics Laboratory at Kyoto University. He also been occupying editorial roles for the journals PLOS ONE, Frontiers in Environmental Science, and Biology. In 2020, he created Ariana Technologies (www.ariana-tech.com), a start-up operating in the field of Data Science/Simulation and IoT for crisis management.

He is a member of IEEE, a computer scientist, an Information Technologist, and a Research Lab Head at the Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda. My research broadly integrates and focuses on developing principled computationally and statistically efficient models and algorithms for various machine learning problems in Smart Agriculture, Ecological Informatics, Computer Vision, Applied AI, Cybersecurity and Privacy, and Smart Cities. I attained a Bachelor in Information Technology at the Faculty of Science & Computing, Ndejje University, Kampala, Uganda; a Master in Information Technology Engineering (Computer and Communication Networks); and PhD in Computer Science Universiti Brunei Darussalam, Brunei. He has received additional training from, among others, the National Institutes of Health, US Department of Health and Human Services, and the Bloomberg School of Public Health, USA. Hundreds of scholarly publications, including those in prestigious peer-reviewed journal articles, numerous IEEE International, non-IEEE Conference proceedings, book chapters, and books have been published. Reviewer/editorial support of over twelve (Scopus, Compendex (Elsevier Engineering Index), and WoS International Journals, including Expert Systems With Applications, Scientific Reports and Computers and Electronics in Agriculture. I served in several capacities, including being departmental support for Mathematics for Data Science, Advanced Topics in Computing, and Advanced Algorithms. Prior to this, I served as a community data officer at Pace-Uganda, a research associate at TechnoServe, a research assistant at PSI-Uganda, a research lead at the Socio-economic Data Centre (SEDC-Uganda) and ag. managing director at Asmaah Charity Organisation.

About me
Name: Dr. Julia Kasmire
Position: Post-doctoral Research Fellow
Where: UK Data Services and Cathie Marsh Institute at the University of Manchester.
Short Bio
2004 - BA in Linguistics from the University of California in Santa Cruz, including college honours, departmental honours and one year of study at the University of Barcelona.
2008 - MSc in the Evolution of Language and Cognition from the University of Edinburgh, with a thesis on the effects of various common simulated population features used when modelling language learning agents.
2015 - PhD from Faculty of Technology, Policy and Management at the Delft University of Technology under the supervision of Prof. dr. ig. Margot Wijnen, Prof. dr. ig. Gerard P.J. Dijkema, and Dr. ig. Igor Nikolic. My PhD thesis and propositions can be found online, as are my publications and PhD research projects (most of which addressed how to study transitions to sustainability in the Dutch horticultural sector from a computational social science and complex adaptive systems perspective).
Additional Resources
Many of the NetLogo models I that built or used can be found here on my CoMSES/OpenABM pages.
My ResearchGate profile and my Academia.org profile provide additional context and outputs of my work, including some data sets, analytical resources and research skills endorsements.
My LinkedIn profile contains additional insights into my education and experience as well as skills and knowledge endorsements.
I try to use Twitter to share what is happening with my research and to keep abreast of interesting discussions on complexity, chaos, artificial intelligence, evolution and some other research topics of interest.
You can find my SCOPUS profile and my ORCID profile as well.