The Peter Sanders Lab

Peter Sanders’s lab focuses on algorithm engineering and the design of highly efficient data structures and algorithms for large-scale problems, with strong emphasis on practice-oriented theory. The group works on shortest-path and route-planning algorithms for road networks, graph partitioning and clustering, parallel and distributed data structures such as priority queues and relaxed concurrent queues, and compact representations like bit-vector rank/select and minimal perfect hashing. Research topics include scalable graph-partitioning methods for multi-level and tera-scale networks, fast and low-space hash structures, concurrent and multi-queue designs for high-throughput systems, and algorithmic optimizations for bioinformatics and large-dataset workloads. A distinctive feature of the lab is the tight coupling between rigorous theoretical analysis and engineered implementations that must perform well on real hardware and massive inputs. Students joining the group can expect to work on the boundary between theory and systems, using C++, low-level optimizations, and parallel programming, and preparing for careers in algorithms, database systems, high-performance computing, and algorithm-driven software engineering.