Mathematical Modeling & Scientific Computation
We live in an era of unprecedented data generation, producing massive datasets that can be unwieldy, difficult to manage, and challenging to comprehend. At Yale Engineering, our expertise in computational and scientific modeling is transforming this complex data frontier into critical insights and real-world applications.
By developing sophisticated algorithms and harnessing scientific computation, we are simulating complex scenarios with high reliability and efficiency, advancing the fields of engineering, medicine, and science.
In biomedical sciences, we are an active part of the genomic revolution, developing high-throughput search engines and simulating biological cells to better understand diseases and develop targeted therapies. Our researchers are also modeling cardiovascular systems to predict heart disease and optimize medical device design.
Our chemical engineers and materials scientists are analyzing complex data to study physical and chemical transformations of matter, revealing the impacts of climate change on human health and the environment.
We're also applying computational modeling to improve the algorithms underlying large language models and AI systems. Recognizing the challenges of interpreting messy real-world data, our researchers critically examine the theoretical foundations of widely used algorithms. In computer science, we're advancing animation through innovative mathematical modeling, digitally creating tightly coiled, afro-textured hair to provide accurate ethnic representation where it did not exist.
Our robotics researchers are employing advanced computational methods to develop socially engaging and collaborative robots for educational and therapeutic support, enhancing our understanding of human behavior and human-robot interaction.
From microscopic cellular simulations to macroscopic climate models, Yale Engineering researchers are leveraging computational and scientific modeling to make a real-world impact and benefit society.