Luigi Nardi is WASP-AI assistant professor in Machine Learning at Lund University and researcher at Stanford University. His current research focuses on multi-objective black-box optimization and its use in a variety of applications, including computer vision, robotics, database management and hardware design. Nardi's research has garnered significant industry interest. His work on Bayesian optimization and AI benchmarks was adopted by industry leaders such as NVIDIA, ARM, Intel, Microsoft and IBM. Prior to his current positions, Luigi was a permanent researcher at the financial firm Murex S.A.S., France, leading the high-performance analytics effort, and a postdoctoral researcher at Imperial College London where he worked on the learning-based optimization of low-power high-performance computer vision systems. Luigi received his Ph.D. in Computer Science from Université Pierre et Marie Curie (UPMC) in Paris and both his master and undergrad from La Sapienza University in Rome.