Franz Stoll

Franz is a 5th-year Ph.D. candidate at Purdue University, dedicated to bridging the gap between academic research and real-world industry challenges. He has worked with Amazon as a Research Scientist and Applied Scientist intern, applying cutting-edge research to optimize operations across fulfillment centers, sort centers, and air hub facilities. His work focuses on logistics challenges such as package sortation, containerization, and labor-intensive tasks. Currently, his research focuses on applying hybrid modeling techniques that integrate AI, explainable AI (XAI), and resource cross-training with optimization methods to leverage historical industry data. His work accelerates learning curves and enables faster, more dynamic decision-making. He also holds a pending patent for an integrated system deployed across 1,900+ Amazon warehouses, reinforcing his commitment to scalable, high-impact research.