Research Themes
YAMTL — A model-to-model transformation engine whose transformations are defined with an internal DSL of Xtend. Main strengths: interoperability with Java, expressiveness, and performance. Supports incremental execution. yamtl.github.io
EMF-Syncer — Facilitates the adoption of Model-Driven Engineering techniques and EMF-supported tooling in JVM programs. emf-syncer.github.io/
MDE-subtyping — A tool that infers whether two metamodel specifications (EMF metamodel + OCL constraints) are compatible, enabling safe reuse of model management operations. mde-subtyping.github.io/web
FMA-ATL — An executable formalization of a large excerpt of the model transformation language ATL in Maude, using EMF and ATL as front-end languages. fma-atl.github.io
Funded opportunities — For those looking for research-oriented opportunities in model-driven engineering, AI/ML, and healthcare. arturboronat.github.io/funded-opportunities
Grants and Projects
Personalised Space Technology Exercise Platform (P-STEP) Funder: European Space Agency (ESA) · Role: Informatics lead · 2021–2023 · Award: £2M (whole project)
P-STEP is an eHealth service platform to deliver and monitor personalised exercise advice to patients living with long term health conditions. The platform provides warnings and guidance based on environmental conditions and location (from GNSS and EO sources) to modify recommended exercises and reduce risk. Through AI and optimally designed user interfaces, it promotes adherence to advice. The platform targets long-term respiratory and cardiac conditions, identified as clinical priorities in the NHS 10-year plan. Project page
P-STEP CCN1: iOS & Wearables Extension Funder: European Space Agency (ESA) · Role: Informatics lead (WP3000) · Nov 2024–Oct 2025 · Award: EUR 467,528 (ESA contribution; total project cost EUR 935,054)
Contract Change Notice 1 extends the P-STEP platform to iOS via Kotlin Multiplatform (KMP) and adds wearables integration (Terra API) for Apple Watch, Fitbit, Garmin, and Google Fit. The extension addresses a commercialisation barrier identified during pilot activities: 39% of prospective participants were excluded due to iOS-only access. Backend hardening, security, and data aggregation updates are also in scope. Project page
An AI-powered DSML for Data Discovery for Rare Diseases Funder: EPSRC network MDE-Net · Role: PI · Jun–Dec 2022 · Award: £4,950
Design of a domain-specific modelling language (DSML) and development of a proof-of-concept no-code development platform for rare disease medical researchers. Applies MDE productivity tools and AI-enabled optimization techniques. Project page
MDENet: The expert network for Model-Driven Engineering Funder: Engineering and Physical Sciences Research Council (EPSRC) · Role: Founding member · 2022–2023
The EPSRC network MDENet brings together research and practice in Model-Driven Engineering (MDE) in the UK and internationally, generating research collaborations, producing MDE training material, and increasing awareness of MDE in the software industry. mde-network.com