me
Pau Martínez Rios
FIB-UPC
Master Student
me
Pau Martínez Rios
FIB-UPC
Master Student
I am a Computer Engineering student at the Universitat Politècnica de Catalunya (UPC - BarcelonaTech), specializing in Computation. Currently, I am working on my Bachelor’s Thesis, entitled “Exploring Graph Partitioning for Optimal Graph Neural Networks”. My research focuses on analyzing how graph partitioning methods affect the performance and efficiency of Graph Neural Networks (GNNs) on large-scale datasets.

I am a Computer Engineering student at the Universitat Politècnica de Catalunya (UPC - BarcelonaTech), currently completing my studies in the specialization of Computation. The final stage of my academic path is the Bachelor’s Thesis, a project that I consider not only a requirement to graduate, but also an extraordinary opportunity to integrate and apply the knowledge and competences I have been developing during these years of study.

This thesis gives me the chance to bring all these skills together and put them into practice in a real, complex, and challenging problem. I believe this experience will be decisive in shaping both my academic and professional future, and I am very enthusiastic about taking on this challenge.

With the continuous support and guidance of Sergi Abdal and Axel Washington, I feel well-prepared, motivated, and confident to conduct rigorous research and deliver meaningful results.

The project is entitled “Exploring Graph Partitioning for Optimal Graph Neural Networks”. Its main goal is to analyze how different graph partitioning strategies can impact the performance and efficiency of Graph Neural Networks (GNNs), particularly when applied to large-scale graph datasets.

I am a Computer Engineering student at the Universitat Politècnica de Catalunya (UPC - BarcelonaTech), specializing in Computation. Currently, I am working on my Bachelor’s Thesis, entitled “Exploring Graph Partitioning for Optimal Graph Neural Networks”. My research focuses on analyzing how graph partitioning methods affect the performance and efficiency of Graph Neural Networks (GNNs) on large-scale datasets.

I am a Computer Engineering student at the Universitat Politècnica de Catalunya (UPC - BarcelonaTech), currently completing my studies in the specialization of Computation. The final stage of my academic path is the Bachelor’s Thesis, a project that I consider not only a requirement to graduate, but also an extraordinary opportunity to integrate and apply the knowledge and competences I have been developing during these years of study.

This thesis gives me the chance to bring all these skills together and put them into practice in a real, complex, and challenging problem. I believe this experience will be decisive in shaping both my academic and professional future, and I am very enthusiastic about taking on this challenge.

With the continuous support and guidance of Sergi Abdal and Axel Washington, I feel well-prepared, motivated, and confident to conduct rigorous research and deliver meaningful results.

The project is entitled “Exploring Graph Partitioning for Optimal Graph Neural Networks”. Its main goal is to analyze how different graph partitioning strategies can impact the performance and efficiency of Graph Neural Networks (GNNs), particularly when applied to large-scale graph datasets.