Regular biography
Amir Barati Farimani is the Russell V. Trader Associate Professor in the Department of Mechanical Engineering at Carnegie Mellon University. His research focuses on applying machine learning, data science, and molecular dynamics simulations to health and bio-engineering problems. The Mechanical and Artificial Intelligence laboratory (MAIL) at CMU is a multidisciplinary group that integrates mechanical engineering with computer science, bio-engineering, physics, materials, and chemical engineering. The lab aims to develop data-driven models that incorporate physics into learning algorithms to improve predictive accuracy in mechanical systems. His work includes using multi-scale simulations to generate data and applying these techniques to areas such as additive manufacturing, bioengineering, and energy systems.
Scholar-generated biography
Amir Barati Farimani is a Russell V. Trader Associate Professor at Carnegie Mellon University, specializing in computational systems, multi-scale modeling, biophysics, and deep learning. His research focuses on integrating machine learning with physical models to advance scientific discovery and engineering applications. He explores topics such as molecular contrastive learning, physics-informed diffusion models, and the use of graph neural networks for molecular representation. His work also includes the development of deep learning frameworks for materials science, such as MOFormer and TransPolymer, and applications in biophysics, including DNA base detection and biofluid barriers. His research bridges computational methods with experimental insights to address challenges in energy, materials, and biological systems.