The Auton Lab
Developing Artificial Intelligence for practical solutions of real world problems
Research Focus Areas
The Auton Lab is interested in the underlying computer science, mathmatics, statistics and AI of detection and exploitation of patterns in data
Key People
The Auton Lab is directed by Artur Dubrawski, Jeff Schneider, and Barnabas Poczos but many people contribute to its success.
Founding Faculty
Andrew Moore Head of AI, Google
- Interested in building probabilistic models efficiently and in developing data structures that make machine learning very scalable and fast.
Core Faculty
Artur Dubrawski Research Professor, CMU School of Computer Science
- Interested in researching new machine learning algorithms and data structures to facilitate probabilistic modeling, predictive analysis, interactive exploration, and understanding of data.
Core Faculty
Barnabas Poczos Associate Professor, CMU School of Computer Science
- His research interests lie in the theoretical questions of statistics and their applications to machine learning, computer vision, astronomy, and bioinformatics.
Core Faculty
Jeff Schneider Research Professor, CMU School of Computer Science
- His research is in learning, optimization, data mining, scheduling, robotics, and intelligent control. Additional areas include navigation, manipulation, vision, and other types of sensing.
Upcoming Events and News
News
The University of Pittsburgh School of Medicine and Carnegie Mellon University each have been awarded four-year contracts totaling more than $7.2 million from the U.S. Department of Defense to create an autonomous trauma care system that fits in a backpack and can treat and stabilize soldiers injured in remote locations. - Learn More
Congrats to the Traffic Jam team at CMU and Marinus Analytics! Our counter-human-trafficking work in the media: "It is not about the data, it is really about the people" - WQED Just a Minute
Events
2nd Annual HackAuton
TBD, 2019
Newell Simon Hall
The Auton Lab hackAuton is an annual outreach event focused on celebrating the positive impact AI can have on real-world problems. Students with diverse skills and interests spend a weekend working on one of several challenge problems. While there is an opportunity to compete for top prizes, we set ourselves apart from other hack-a-thons by focusing on the shared experience of all participants. We archive the efforts of students through hosting their code on Github, storing recordings of their final presentations online, and publishing a write up of their efforts to be included in an event proceedings. This way, all participants walk away with an online reference to their hard work which can help all participants build their resume as they go on to become leaders in their respective fields. Learn More