Chenlu Shi

Chenlu Shi is an Assistant Professor in the Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT). Their research focuses on design of experiments, statistical modeling, and combinatorial design, with an emphasis on orthogonal arrays, factorial design optimization, and model robustness. Key contributions include work on space-filling criteria, generalized resolution in nonregular designs, and subdata selection strategies for big data.

Research interests span topics such as optimal design theory, Hadamard matrices, and efficient experimental setups. Notable projects include developing projection space-filling criteria, analyzing Paley’s Hadamard matrices for design construction, and exploring model-robust subdata selection methods.

Articles highlight advancements in statistical design efficiency, with trends toward optimizing experimental setups for high-dimensional spaces and improving robustness against model misspecification. No scientific awards are explicitly mentioned in the provided texts. Advising and grant information is not available here.