Malik Lechekhab
I'm a PhD student in High Performance Computing at the Advanced Computing Laboratory, Università della Svizzera italiana. I hold a master’s degree in Finance from HEC, University of Lausanne. My research interests include graph theory, anomaly detection, and computational finance. In my free time, I enjoy all mountain sports, from hiking to paragliding.
Session
We present GraphLab.jl, a Julia package designed to facilitate the study, experimentation, and research of graph partitioning. GraphLab.jl provides a framework for exploring the principles and trade-offs of partitioning algorithms through hands-on tools. It implements a growing set of methods—including coordinate, inertial, and spectral bisection, random spheres, space-filling curves, and nested dissection—with support for recursive partitioning. The package includes routines for generating adjacency matrices, computing partition quality metrics, benchmarking problems, and visualizing partitioned graphs. GraphLab.jl enables integration with external graph partitioning software, thus allowing users to compare additional methods and results in a unified environment. Our work aims to introduce Julia's capabilities to learners and researchers engaging in graph theory and related partitioning problems.