I am an applied AI engineer and research professional focused on building reliable machine learning systems, particularly in computer vision and modern language-based architectures (LLMs, RAG, and agents).
Over the past years, I have worked on projects that combine deep learning with pragmatic system design-covering model development and evaluation, data strategy (including synthetic data when appropriate), and deployment constraints such as latency, resource usage, and maintainability.
I typically work across the full lifecycle: defining the problem and KPIs, designing modular pipelines, training and validating models, and operationalizing them with reproducible environments and experiment tracking.
My current research areas of interest are timeseries modeling, computer vision and language systems (LLMs). I also have a background in algebra and cryptography since I did some work in Criptografia i Grafs (CiG) research group in Universitat de Lleida.
Publications
Peer-reviewed journal articles
Velasquez-Camacho, L., van Doorn, N., Preisler, H., Etxegarai, M., Alas, O., Gonzalez Castro, J. M., & de-Miguel, S. ( 2025). Monitoring temporal changes in large urban street trees using remote sensing and deep learning. PLOS ONE, 20( 6), e0326562. doi: 10.1371/journal.pone.0326562
Alàs, O., & Sebé, F. (2024). Privacy-Preserving Electricity Trading for Connected Microgrids. Applied Sciences, 14(4), 1458. doi: 10.3390/app14041458
Thesis / academic work
Alàs Cercós, O. (2023). Generative deep learning based models for cloud removal satellite imagery (Master’s thesis / Treball Final de Màster, Universitat de Lleida – EPS; public defense dated 27 Sep 2023)
Alàs Cercós, O. (2021). Implementació d’un sistema criptogràfic per l’enviament del consum elèctric en sistemes de comptadors intel·ligents (Treball Final de Grau, Grau en Enginyeria Informàtica, Universitat de Lleida – Escola Politècnica Superior; presented July 2021; supervisor: Francesc Sebé Feixas).