Hector Orengo Romeu
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- Position: COMPUTATIONAL HUMANITIES GROUP LEADER
- Computational Social Sciences and Humanities Laboratory - Computational Humanities
- email: hector [dot] orengo [at] bsc [dot] es
- Tel: 000000000
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Biography
Hèctor A. Orengo is an ICREA Research Professor at the Barcelona Supercomputing Center. He obtained his PhD from the Rovira i Virgili University in 2010 and, since then, he has developed research at the GEOLAB (UMR 6042) in France, the Universities of Nottingham, Sheffield and Cambridge in the UK, and the Catalan Institute of Classical Archaeology in Spain. His research has focused on long-term human-environment interactions and the development of computational methods to address archaeological problems.
Research
Hèctor’s research has mainly focused on the analysis of human-landscape dynamics in Mediterranean environments and beyond. He has developed extensive research on computational archaeology that includes, but is not restricted to, GIS and remote sensing techniques, field survey, and site detection methods. He is currently working on the application of machine learning to archaeological research using cloud computing and big data sources (mostly multisource multitemporal satellite data, drone imagery and lidar).
He currently works on the following research lines:
1. Large-scale analysis of global patterns of human habitation over space and time using remote sensing methods, geospatial analyses and machine learning. His work is providing important insights into the development and fall of ancient civilisations that cover very large areas and display complex organisational patterns resulting by a combination of human agency, cultural and environmental factors. The use of massive datasets have been key in allowing discerning patterns that are invisible otherwise.
2. Development of automatisation methods that can significantly boost archaeology's interpretative potential. By automatising technical tasks Hector is seeking to: a) increase the scale of analysis to achieve quantitatively solid interpretations while b) reducing the time and effort necessary for the development of these tasks. Hector's and his team work on automatization not only includes large-scale detection and monitoring of archaeological sites but is also unlocking sources with unique potential for the analysis of human settlement and landscape use. These include the automated identification of material culture in drone imagery, the extraction of human-made landscape features from large-scale historical map series, the automated identification of complex multi-cell phytoliths in microscope slides, and the identification of ancient agricultural regimes using the 3D analysis of seeds’ shape. Hector's long-term partners in these projects include the Computer Vision Centre (CERCA-UAB) and The McDonald Institute for Archaeological Research (University of Cambridge).
3. Modelling and analysis of pre-industrial transcontinental movement. Hector's team together with colleagues at Cambridge is currently working on the development of new methods for the analysis of large-scale movement. These are significantly more complex to model than regional scale transport as they need to take into account different environmental scenarios and seasonal factors. Besides other algorithmic innovations, his approach to this task includes the use multiple and seasonality-sensitive cost factors, convolutions to manage proximity-based costs, and probability surfaces that allow the investigation of alternative routes. This research aims to understand connectivity at large scale and how it influenced the origin and distribution of urban centres in the Ancient World.