Brendan Juba

Brendan Juba is an Associate Professor at Washington University in St. Louis, affiliated with the School of Engineering and the Department of Computer Science and Engineering. He is also associated with the Division of Computational & Data Sciences and the Machine Learning & Artificial Intelligence group.

Brendan earned his PhD from MIT in 2010 under Madhu Sudan, followed by a postdoctoral fellowship at Harvard University with Leslie Valiant until 2014. He was also jointly affiliated with CSAIL and the Center for Science of Information through 2012. His PhD thesis, Universal Semantic Communication, was published by Springer.

Research Interests

His work focuses on theoretical approaches to artificial intelligence, particularly algorithms for integrated learning and reasoning (e.g., common sense reasoning), and computational complexity. He has also explored communication protocols without standards and the science of information in contexts like data mining and logical reasoning. His research spans the intersection of machine learning, formal logic, and algorithmic efficiency.

Scientific Awards & Collaborations

While specific awards are not listed, his work has been supported by the NSF Big Data Analytics REU site grant (IIS-1560191) and collaborations with researchers like Loizos Michael and Manuel Blum. He has presented tutorials at AAAI-18 and seminars at institutions like the Center for Computational Intractability and the IAS CSDM seminar.

Teaching & Supervision

He has taught courses such as CSE 347 (Analysis of Algorithms), CSE 513T (Theory of AI & Machine Learning), and CSE 519T (Advanced Machine Learning). His supervision includes PhD students like Golnoosh Dehghanpoor and Zihao Deng, as well as Masters students (e.g., Roger Iyengar, Phoebe Chua).