The Collaborative Research at the Intersection of Statistics and Engineering (CRSE) Program aims to provide supplementary mentorship to engineering Ph.D. students whose research involves the analysis of high-dimensional data, as well as to statistics Ph.D. students developing statistical methods applicable to engineering. The CRSE Workshop will include two main components: Lectures on state-of-the-art methods in high-dimensional data analysis by distinguished experts, and Research Sessions in which Ph.D. students will present their projects, followed by discussions and feedback from participating experts and peers. In addition, a Program Director from the National Science Foundation (NSF) will share insights on funding opportunities and resources available to Ph.D. students and academic researchers.
The objectives of the workshop are to:
· Advance collaboration between statisticians and engineers.
· Provide training and feedback opportunities for Ph.D. students.
· Facilitate discussions on high-dimensional data analysis and its applications.
The workshop theme includes, but is not limited to, the following areas:
Statistical topics
· High-Dimensional Time Series Analysis
· Functional Data Analysis
· Regularization and Sparse Modeling
· Bayesian High-Dimensional Modeling
· Dimensionality Reduction and Embedding Techniques
· Conformal Prediction and Uncertainty Quantification
· Physics-Informed Machine Learning
Engineering applications
· Transportation Data Analysis
· Environmental Modeling
· Infrastructure Demand Forecasting
· Advanced Manufacturing and Process Control
· Energy Demand and Supply Modeling
· Autonomous and Robotics Systems
· Biomedical Signal Analysis
Ph.D. students are invited to apply to participate in the workshop. Details on eligibility and the application process can be found here.