Assistant Professor - Lane Department of Computer Science and Electrical Engineering
Sicilia’s research studies how Large Language Models and other AI systems can reason effectively when information is uncertain or goals are unclear. His work combines statistical learning theory with computational linguistics to understand how communication functions as part of the reasoning process in AI systems. He applies these ideas to human-AI collaboration, agentic AI systems, and multimodal AI systems in domains such as healthcare, scientific discovery, and education.
His expertise has been recognized with multiple paper and reviewer awards from top computational linguistics and machine learning venues, including ACL venues, AISTATS, and UAI. Sicilia’s research has also been applied in nationally deployed AI systems through collaboration with industry labs, such as Amazon Alexa.
Education
Ph.D., Computer Science, Northeastern University, 2025.
B.S., Mathematics, University of Pittsburgh, 2019.