Meet Camilo González, Research Assistant

I’m Camilo González from Bogotá, Colombia, and I’m a Research Assistant at SEI-LA in the water group.

My role revolves around supporting research projects and activities in water resources management. I handle data collection and analysis, work with WEAP modelling and publish our results on open-access platforms.

A significant part of my work also involves developing methodologies that incorporate AI for analyzing both qualitative and quantitative information.

My decision to join SEI was driven by the organization’s impactful approach to research, which resonates both academically and socially.

It’s truly inspiring to see our projects being adopted by various institutions and entities, influencing decision-makers and eventually impacting society. This impact and the ongoing collaboration with communities on new projects is what motivates me the most.

In my work with water management, I specialize in constructing comprehensive WEAP models. This involves analyzing input data, calibrating models and developing future scenarios.

To enhance the utility of these models, I integrate them with programs like Excel, R or Python to optimize result visualization and provide a more efficient analytical framework. In terms of communicating results, I go beyond conventional reporting by presenting our modelling outcomes through interactive platforms, making it easier for decision-makers.

In addition to this, I incorporate AI algorithms to gain a deeper understanding of both qualitative and quantitative aspects of our water management projects.

From my perspective, AI has the potential to revolutionize water management and environmental research.

By leveraging AI technologies, we can enhance the efficiency and accuracy of data analysis, allowing us to understand complex water-related challenges better.

By processing large amounts of qualitative and quantitative data, identifying patterns and predicting future trends, AI enables quicker decision-making processes. It enhances modelling and simulation, further contributing to more effective water resource management strategies. It also facilitates the integration of diverse datasets, allowing for a holistic understanding of environmental issues.

Overall, AI presents opportunities to address water management challenges with innovative and data-driven solutions, fostering sustainability and resilience in the face of global environmental changes.

Professionally, I aspire to continue exploring, studying and learning from global trends related to water management methodologies under different economic, climatic, territorial and social conditions. I aim to apply this knowledge in various contexts, adding value through my expertise in model building, process optimization and result communication.

My goal is to make a significant impact through my work by creating inclusive spaces where diverse perspectives are openly shared and communicated. It’s not just about sharing knowledge and results, but also listening to the experiences and viewpoints of all project stakeholders, including those benefiting and those with similar global experiences.

By breaking down barriers like knowledge, language, culture and gender, these spaces foster collaboration, allowing for a common understanding of global issues. Ultimately, this collaborative approach leads to the development of more robust and informed decisions for the sustainable management of water and natural resources.