Working to connect artificial intelligence with chemical sciences, Olexandr Isayev's research focuses on solving fundamental chemical problems with machine learning, molecular modeling and quantum mechanics. his lab works at the interface of theoretical chemistry, pharmaceutical sciences and computer science, working in such areas as theoretical and computational chemistry, machine learning, cheminformatics, drug discovery, computer-aided molecular design and materials informatics.
Areas of Expertise (2)
Future of Science
Jackson State University: Ph.D., Theoretical Chemistry
Dnepropetrovsk National University: M.S., Chemistry
Media Appearances (4)
AI-Based ‘Artificial Chemist’ Directs Automated Lab to Create Better MRI Contrast Agents
Artificial-intelligence algorithm developed on XSEDE-allocated systems promises better MRI agents with unprecedented speed of discovery
ALCC Program Awards Computing Time on ALCF’s Theta Supercomputer to 24 projects
The U.S. Department of Energy’s (DOE) Advanced Scientific Computing Research (ASCR) Leadership Computing Challenge (ALCC) has awarded 24 projects a total of 5.74 million node hours at the Argonne Leadership Computing Facility (ALCF) to pursue challenging, high-risk, high-payoff simulations.
Chemical Discovery for Industry, Medical with Carnegie Mellon’s Neural Network Tool
For industrial and medical companies, a central question in modern chemistry is how to identify and synthesize molecules to create useful applications. Even with high performance computing, the research is expensive both in terms of cost and computer time required for the simulations. The good news is that artificial intelligence (AI) and machine learning (ML) are revolutionizing chemical research and creating tools that can be used in a typical enterprise setting.
AI identifies drug candidate in weeks
Chemical & Engineering News
The artificial intelligence start-up Insilico Medicine has used machine learning to find credible drug candidates in a matter of weeks (Nature Biotechnology 2019, DOI: 10.1038/s41587-019-0224-x). Experts say it’s an important demonstration of what machine learning can do in drug discovery, but it isn’t a revolution.