Computational statistics harnesses the power of sophisticated numerical algorithms and high‐performance computing to solve complex inferential problems that are intractable by traditional analytical ...

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry ...

Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...

This course is designed for engineering graduate students who are interested in furthering their knowledge in advanced and emerging methods of engineering design, with the focus on computational ...

This course covers the ideas underlying statistical modelling in science through the lens of causal thinking. We cover the implementation of these ideas through Bayesian computational methods and ...

Researchers developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and how we treat them. Researchers at the University of ...

You'll learn to rigorously and creatively apply computational methods to social science research problems. You'll develop advanced skills in computational methods, research design, social scientific ...

Professor Ablowitz’s work centers around nonlinear waves, integrable systems, and physical applied mathematics — e.g., nonlinear optics and water waves and applications of complex analysis. Professor ...

Introduction to a wide range of computational techniques for engineering design. Modeling, simulation, optimization, design software, examples/projects with emphasis on computational techniques for ...