Conference Agenda

Within the framework of the 2030 Agenda, sustainability has become a cross-cutting theme in engineering education, positioning international academic networks as key mechanisms for building capacity and promoting purposeful engineering. However, the literature shows that the lack of systematic diagnoses and empirical characterizations is a recurring limitation in these networks, restricting their strategic management and impact assessment. This knowledge gap is particularly relevant in engineering networks focused on sustainability, due to their interdisciplinary nature and regional scope. In this context, the Latin American and Caribbean Consortium of Engineering Institutions (LACCEI), through its Sustainability and Social Impact Committee, promoted the creation of a Research Network. The objective of this study is to empirically and systematically characterize the academics who comprise this network, identifying their profiles, research areas, collaboration patterns, and their alignment with the Sustainable Development Goals. This study employed a descriptive, cross-sectional design with a mixed-methods approach, integrating descriptive statistics, content analysis, and bibliometric analysis. The results demonstrate sustained growth in scientific output, presence across all 17 Sustainable Development Goals (SDGs)—with SDG 9 being the most prominent—alongside an interdisciplinary thematic structure, as well as persistent territorial gaps. It is concluded that the network exhibits an advanced level of academic consolidation and constitutes a replicable diagnostic baseline for academic networks in engineering and sustainability.

Dry tropical forests are highly sensitive ecosystems influenced by climate variability and regional warming trends, particularly those associated with ENSO. In northwestern Peru, a mosaic of watersheds is exposed to El Niño Costero precipitation pulses, which have increased in intensity and recurrence in recent decades. This makes it necessary to understand the relationship between these pulses and climate change, as well as their effects on ecosystems, in a sectorized manner. Meteorological variability, climate change, ENSO, and forest vigor were analyzed in the different watersheds of the Coto de Caza El Angolo from 1984 to 2025 to achieve this goal. Data from weather stations, ENSO measurements, and climate change measurements were processed to determine NDVI variation from Landsat images. The results revealed significant spatial heterogeneity, with higher NDVI values observed in the eastern watersheds (Tumbes and Chira) and arid conditions in the Pariñas watershed. Temporally, a sustained increase in NDVI was identified in all basins, exceeding 200% in the western basins (Fernández and Pariñas) due to greater wet year recurrence and reduced dry periods. The correlations indicate that the plant response is more closely related to minimum and average temperatures than to the El Niño-Southern Oscillation (ENSO) index. Intense ENSO events generate greening through hydrological pulses. Taken together, the results demonstrate that the ecohydrological response is heterogeneous and structurally differentiated by watersheds under a non-stationary climate regime. These findings provide empirical evidence of the importance of considering spatial heterogeneity when assessing ecosystems in the context of ENSO variability and regional warming.

A sustainable aqueduct is conceived as a comprehensive system that combines technical efficiency with social and environmental responsibility, ensuring equitable access to drinking water and the preservation of water resources for future generations. Under international standards, its design is based on optimizing water use through technologies that reduce losses, responsible management of water sources, and the implementation of conservation practices from the domestic to the agricultural sphere. Sustainability transcends the technical by promoting positive environmental impacts, community participation, and inclusive development, consolidating a water governance model based on innovation, equity, and resilience, aligned with global challenges of sustainability and environmental justice.
In this context, predictive artificial intelligence (AI) is presented as an effective resource for designing sustainable aqueduct systems in vulnerable urban environments. The case study is located in commune 5 of Valledupar, a municipality with 567,593 inhabitants and an aqueduct system that supplies 1,600 l/s daily, but with average losses of 52.65%. The system has five gate valves and three regulating tanks with a total capacity of 33,000 m³. The research used predictive modeling with EPANET 2.2 and Power BI AI Forecast, supported by ISO 24512 and RAS 0330 standards from 2017. The findings showed a simulated reduction of 18.83% in tank deficits and 35% in total losses, demonstrating operational stability, scalability, and low environmental impact. It is concluded that AI applied to water infrastructure strengthens replicable, efficient, and resilient models in Latin America, contributing to the fulfillment of SDGs 6 and 11 and consolidating prospects for urban sustainability.

This article presents the ATA System (Amazon Tambo Aldea) as a strategic regenerative platform designed to operate in high-biodiversity territories such as the Peruvian Amazon, applying LxC Engineering (Life per Carbon). This approach is grounded in the PCRC (Physicochemical Carbon Regeneration Cycle), which transforms captured CO₂ and solar energy into useful biomass, living energy, and social cohesion through thermodynamically and biologically quantifiable processes.

Using a modular intervention structure of 24 hectares per ATA unit, the model enables ecosystem restoration, job creation, and maximization of environmental, social, and economic returns without deforestation. The methodological architecture integrates the CUPA cycle (Calculate, Understand, Plan, Act), the 9SP canvas (Nine Strategic Pillars), the Value Chase (VC) adapted from QFD, and the ROP (Return of Operational Performance) indicator.

The system is validated at three levels:

• Technical: through indicators such as Marginal Consumption (CM), Marginal Benefit (BM), and ROP.
• Territorial: through projective simulations demonstrating scalability.
• Academic: with international recognition, including first place at IEOM 2023.

The ATA System demonstrates the feasibility of redesigning degraded territorial processes into sustainable regenerative models, enabling multicapital traceability, community participation, and measurable impact.