Expertise

Topics:  Cancer Biology, Biophysics, Population Genetics, Computational Genomics, Machine Learning, Computational Biology, Artificial Intelligence, Algorithms, Phylogenetics

Industries: Research, Biotechnology

Russell Schwartz works broadly in computational biology and the use of algorithms, artificial intelligence, machine learning, and simulation in biomedical science. This has included work on problems in computational genomics, phylogenetics, population genetics, and biophysics. The largest area of his lab’s work in recent years has been cancer biology, with specific focus on clonal evolution in cancers and its role in disease progression. He is also active in bioinformatics education and improving quantitative and computational training in the biomedical field.

Media Experience

Pittsburgh’s AI-Powered Renaissance  — CMU News
"There is tremendous excitement about the new generation of AI tools and nowhere could their impact be greater than in improving human health. AI tools seem to hold great promise for personalized medicine but also warrant caution as we see what they do not do well and how much we do not yet understand about how they work and how they might be improved. The big leaps in AI we are seeing now are neither the beginning nor the end of the field. They were built on a foundation of decades of research into AI fundamentals and their application to real-world problems in human health and disease, areas in which Pittsburgh researchers have long been world leaders. And there is much more to be done to fully realize their potential."

Computer science professor Sorin Istrail wins award recognizing algorithms research  — The Brown Daily Herald
Through the paper and its surrounding work, Istrail and colleagues made use of one of the pillars of computer science in genomics — recognizing that a genome can be modeled as a computational artifact and that, in doing so, one is able to access a powerful set of tools for analyzing it, according to Russell Schwartz, co-author of the paper and head of the computational biology department at Carnegie Mellon University.