Artificial Intelligence (Natural Language Processing, Machine Learning, Vision)
Artificial intelligence (AI) is about making computing systems smarter, which is having a rapidly increasing positive impact on people's lives. Machines that are smart are able to infer useful information about the world from data, and effectively interact with the people they serve. Further, they are able to make predictions (e.g., is a medical condition likely to get worse?), and reason about intervention (e.g., will a particular drug be helpful in a particular case?).
Beyond the opportunity of working on problems with potential for substantive positive impact, research in AI is intellectually fascinating. We as humans understand a great deal about the world we live in, and the people we interact with, which enables us to thrive in a very complex environment. To what extent can we solve similar problems computationally? What are the representations and algorithms? These challenging questions make AI research rewarding and worthwhile beyond constructing useful applications.
At The University of Arizona, AI research spans inferring meaning from natural language texts (CLU lab led by Mihai Surdeanu), inferring explanatory statistical models from data in the context of computer vision and scientific data (IVILAB led by Kobus Barnard), and making visual representations smarter (Carlos Scheidegger). We collaborate with each other, others in the department, and many wonderful colleagues across campus and beyond. Our interdisciplinary projects touch on astronomy, cancer biology, cognitive psychology, geological engineering, plant sciences, linguistics, neuroscience, nursing, and social psychology.
Recently funded projects include a DARPA world modelers project on building systems to model global events and a UA accelerate for success grant on inferring facial communication from video data. We are also very active in the newly awarded NSF TRIPODS grant which is a collaboration between math, statistics, and computer science.