The Dennis Schieferdecker Lab

Schieferdecker Lab focuses on algorithm engineering for large-scale transportation and networked systems, with an emphasis on efficient route planning, alternative route generation, and robust navigation services. The group designs and analyzes algorithms that make modern navigation and mobility applications faster, more reliable, and more informative for users. In road networks, the lab develops methods to compute high-quality alternative routes beyond the single shortest path, using ideas like contraction hierarchies, via-node routing, and penalty-based techniques that iteratively modify edge costs to encourage diverse yet reasonable paths. It also studies robustness and feasibility in electric-vehicle routing, where uncertain energy consumption, charging behavior, and user risk preferences must be taken into account through constructs like starting charge maps and buffer maps. Beyond classical routing, the lab has contributed to distributed algorithms in sensor networks, including location-free boundary detection based solely on local connectivity information. Students joining the lab can expect to work at the interface of theory and practice: designing graph algorithms, proving properties, implementing and optimizing them in C++ for large real-world networks, and evaluating performance on continental-scale datasets. This environment is ideal if you enjoy graphs, algorithms, and making complex systems work efficiently in real applications.