Collective intelligence focuses on the ways in which technology can enhance teamwork by enabling groups of people to arrive at insights that escape the experts. Research in the School of Computing focuses on the intersection between collective intelligence and machine learning, specifically in the context of humans and AI working together as a team. The work combines unique and often creative insights that different configurations of human-machine teams can arrive at even in domains where the problems are too complex for the AI alone to solve.
Dr. Nathan McNeese, Assistant Professor of Human-Centered Computing and Director of the Team Research and Analytics in Computational Environments (TRACE) Research Group, can count another Human-Centered Computing Ph.D. graduate from his group, Dr. Lorenzo Barberis Canonico.
Dr. Lorenzo Canonico studies how to apply the “Wisdom of Crowds” to many open problems in bioinformatics. He is starting a post-doc at the Department of Biomedical Data Science at Stanford University where he will be applying the methods he learned at Clemson to the problem of integrating human intelligence and artificial intelligence to the analysis of genomes, clinical diagnostics, and computational biochemistry.
