Kevin Ellis is an Assistant Professor in the Computer Science department at Cornell University. His research focuses on artificial intelligence, program synthesis, and the intersection of AI and cognitive science. The Ellis Lab explores how to build AI systems that learn and reason like humans, particularly in areas such as programming by example, world modeling, neural-symbolic integration, and few-shot learning. The group combines techniques from machine learning, program synthesis, probabilistic programming, and cognitive science to develop AI systems that can learn complex tasks from limited data and generalize across domains.
Our research aims to develop new foundations and technologies for modeling, abstraction, and reasoning in AI systems, focusing on the MARA project. MARA’s general goal is to build systems that actively discover abstract models of the world and reason with these models to carry out goals. Building these systems will demand advances in knowledge representation, abstraction, reasoning, active learning, and a first-principles rethinking of what it means to model the world.
The immediate mission of MARA is to solve the Abstract Reasoning Corpus (ARC) in a way that generalizes to other domains, with the broader mission of building systems capable of learning in an open, growing portfolio of domains using human-comparable amounts of data and interaction.
Fellows will have the opportunity to contribute to this ambitious project, working closely with a team of researchers at Basis and Cornell University. The research environment is both structured and adaptable, providing multiple avenues for scholarly contribution. As a fellow, your expertise can shape various aspects of the project, allowing for a balance of focused research, academic exploration, and software development.