The field of graph and hypergraph algorithms is rapidly advancing, with a focus on developing efficient and scalable solutions for complex problems. Recent research has explored new approaches to disentangling hyperedges, subhypergraph counting, and hyperedge prediction, leading to improved performance and accuracy in various applications. Notably, innovative uses of category theory and parameterized complexity have enabled the development of more effective algorithms for tasks such as diameter computation and VC-dimension calculation. Furthermore, advancements in logic-based algorithmic meta-theorems have led to single exponential FPT time and polynomial space solutions for problems like treedepth. Some noteworthy papers in this area include: Truly Subquadratic Time Algorithms for Diameter and Related Problems in Graphs of Bounded VC-dimension, which presents a new framework for computing diameter in graphs with bounded VC-dimension. HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search, which proposes a novel search-based algorithm for hyperedge prediction that efficiently evaluates unconstrained candidate sets.