(142) Ph.D. 2018, Carnegie Mellon. Machine learning, artificial intelligence, nonparametric statistics, deep learning, statistical data mining, signal processing, graphical models, generative models, kernel methods, scalability, complex datasets, optimization, density estimation.
Contact258 Sitterson Hall
Junier Oliva is an assistant professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. Currently, he is looking to see what makes data tick and understanding data at an aggregate, holistic level. By using techniques ranging from modern deep learning architectures to nonparametric statistics, he is making strides in areas like high-dimensional density estimation and modeling; sequential modeling and RNNs; and learning over complex or structured data. Prior to completing his Ph.D. in machine learning at Carnegie Mellon University, he also received his B.S. and M.S. in computer science from Carnegie Mellon University. He also spent a year as a software engineer for Yahoo! and a summer as a machine learning intern at Uber ATG.