Iban Profile Picture

Iban Berganzo Besga

Title/Position
Senior research engineer
Barcelona Super Computer

A recent post-doc of the RLEA and a continued advisor for RLEA projects, Iban is now a senior research engineer in computational archaeology at the Barcelona Supercomputing Center (BSC). His work focuses on utilizing different lines of AI research for computational archaeology including computer
vision (CV), natural language processing (NLP) and high-performance computing (HPC). 

Publications

Berganzo-Besga, I., Orengo, H., Canela, J., & Belarte, M. (2022). Potential of Multitemporal Lidar for the Detection of Subtle Archaeological Features under Perennial Dense Forest. Land, 11, 1964. https://doi.org/10.3390/land11111964

Berganzo-Besga, I., Orengo, H., Lumbreras, F., Alam, A., Campbell, R., Gerrits, P., Gregorio de Souza, J., Khan, A., Suárez-Moreno, M., Tomaney, J., Roberts, R., & Petrie, C. (2023). Curriculum learning-based strategy for low-density archaeological mound detection from historical maps in India and Pakistan. Scientific Reports, 13, 11257. https://doi.org/10.1038/s41598-023-38190-x

Berganzo-Besga, I., Orengo, H., Lumbreras, F., Aliende, P., & Ramsey, M. (2022). Automated Detection and Classification of Multi-Cell Phytoliths Using Deep Learning-Based Algorithms. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4115214

Berganzo-Besga, I., Orengo, H., Lumbreras, F., Carrero-Pazos, M., Fonte, J., & Vilas-Estévez, B. (2021). Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia. Remote Sensing, 13, 4181. https://doi.org/10.3390/rs13204181

Orengo, H., Berganzo-Besga, I., Landauer, J., Aliende, P., Tres-Martínez, S., & Garcia-Molsosa, A. (2021). New developments in drone-based automated surface survey: Towards a functional and effective survey system. Archaeological Prospection, 28, 1–8. https://doi.org/10.1002/arp.1822

Research

Deep Learning; Phytoliths

Other

Specialization
Computational Archaeology
Machine Learning
Remote Sensing