Articulate the need for computational approaches, such as Markov chain Monte Carlo (MCMC) algorithms, to Bayesian inference. Implement various MCMC algorithms to find posterior distributions, ...

Recent advancements in high-throughput sequencing technologies have enabled researchers to harness valuable omics data, paving the way for precision medicine. This approach aims to enhance diagnosis ...

Computational statistics combines mathematical theory, algorithm design and high-performance computing to extract insight from data. It spans simulation-based inference (for example, bootstrap and ...

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 ...

Data science is a broad, rapidly developing field that combines statistics and mathematics, artificial intelligence, machine learning and programming, for the extraction and structuring of knowledge ...

A computational method for finding transition states in chemical reactions, greatly reducing computational costs with high reliability, has been devised. Compared to the most widely used existing ...