Hi! I’m Diego Malagrida Gonzalez, a third-year Computer Engineering student at the University of the Balearic Islands (UIB), currently specializing in Artificial Intelligence and Computing.
At Gemminis
Alongside my degree, I work at Gemminis on computer vision and geospatial data for urban infrastructure. My work includes fine-tuning models, proposing and testing ideas, and developing tools that connect model predictions with real imagery and maps.
On the computer vision side, I work on models for road and sidewalk defects, from preparing training data to fine-tuning and examining where predictions fail. I also build and improve the tools we use to evaluate those predictions and feed corrections back into the data. This work brings together model development, experiments and the software needed to make them useful to the team.
On the geospatial side, I develop GPS correction workflows and tools for reviewing trajectories against sidewalk maps and recorded video. That includes QGIS editing tools and ways to keep manual corrections traceable. I enjoy taking a problem from an initial idea through implementation, then checking what actually works on the data.
Background
My journey into tech did not start in a typical way. When I began my degree, I had never written a line of code, and I was not even sure Computer Engineering was the right path for me. I knew I wanted to challenge myself and build a meaningful future. Through consistent work, curiosity, and support from great friends, I discovered how exciting this field is and ended up genuinely loving it.
A major part of that growth came from projects that pushed me beyond my comfort zone. One of the most important was developing a full Pac-Man style game in MC68000 assembly, working close to the hardware: input, graphics, collisions, scoring, and ghost behavior. Another key project was building a complete file management system in Linux using C, which strengthened my operating systems knowledge and my appreciation for structured low-level code.
Right now I am especially focused on Artificial Intelligence, particularly deep learning. I read papers, explore new models and test ideas in practice, connecting what I study with the problems I work on.