To tackle the scientific challenges proposed by landscape dynamics and cooperation processes, I have developed a research methodology based on field work and companion modelling (ComMod) combined with the formalisation of the observed processes and agents based models.
This approach offers the possibility to understand : spatial, social, cultural and / or economic conditions that take place on territories, and to provide prospective scenarios.
These methods have been applied in various contexts: steep slope vineyards landscapes (2011), water resource management cooperation (2015), vegetation cover in dry climate (2017). The established research networks are still active through sustained collaborations and activities.

My technical expertise grew and evolved through investment in several workgroups: MAPS Team (Modelling Applied to Space Phenomena), OSGeo (president of the OSGeo’s French chapter between 2013 and 2016, member of the OSGeo-international chapter since 2015), various initiatives around modelling, exploration and sensibility analysis of spatial patterns behaviours, and more generally in Free Software communities.

Dr. Lilian Alessa, University of Idaho President’s Professor of Resilient Landscapes in the Landscape Architecture program, is also Co-Director of the University of Idaho Center for Resilient Communities. She conducts extensive research on human adaptation to environmental change through resilient design at landscape scales. Much of her work is funded by the National Science Foundation, including projects awarded the Arctic Observing Network, Intersections of Food, Energy and Water Systems (INFEWS) and the Dynamics of Coupled Natural Human Systems programs. Canadian-born and raised, Alessa received her degrees from the University of British Columbia. She also uses her expertise in social-ecological and technological systems science to develop ways to improve domestic resource security for community well-being, particularly through the incorporation of place-based knowledge. Her work through the Department of Homeland Security’s Center of Excellence, the Arctic Domain Awareness Center, involves developing social-technological methods to monitor and respond to critical environmental changes. Lil is a member of the National Science Foundation’s Advisory Committee for Environmental Research and Education and is on the Science, Technology and Education Advisory Committee for the National Ecological Observing Network (NEON). Professor Alessa also teaches a university landscape architecture capstone course: Resilient Landscapes with Professor Andrew Kliskey. Professor Alessa’s collaborative grant activity with Professor Andrew Kliskey, since coming to the university in 2013, exceeds 7 million USD to date. She has authored over a 100 publications and reports and has led the development of 2 federal climate resilience toolbox assessments, the Arctic Water Resources Vulnerability Index (AWRVI) and the Arctic Adaptation Exchange Portal (AAEP).

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}).