Assistant Professor of Chemical and Biological Engineering
University at Buffalo School of Engineering and Applied Sciences
Computational chemistry; molecular and materials modeling; cheminformatics; machine learning; big data; materials discovery and design
Johannes Hachmann’s research uses computational and data science approaches to accelerate the discovery and design of new chemical compounds, reactions, and materials.
His work combines techniques such as computational modeling of molecular structures and materials, virtual high-throughput screening, and machine learning to advance the ideas of accelerated discovery, rational design, and inverse engineering in the chemical and materials domain, and thus transform the process that leads to innovation.
In the past, this process often relied on lengthy and expensive trial-and-error searches. One focus area is the creation of novel materials and catalysts for renewable energy technologies and advanced electronics. Hachmann’s work thus aims to drive economic development, prosperity, and a rising standard of living.
Johannes Hachmann, PhD
Assistant Professor of Chemical and Biological Engineering, University at Buffalo School of Engineering and Applied Sciences
Core Faculty Member in the Computational and Data-Enabled Science and Engineering Program, University at Buffalo