AutoGluon: Empowering (Multimodal) AutoML for the Next 10 Million Users

Lecture / Panel
Open to the Public

Geometric abstract image of brain

Part of the Special ECE Seminar Series 

Modern Artificial Intelligence


AutoGluon: Empowering (Multimodal) AutoML for the Next 10 Million Users


Alex Smola, VP & Distinguished Scientist at Amazon Web Services


Automated machine learning (AutoML) offers the promise of translating raw data into accurate predictions without the need for significant human effort, expertise, and manual experimentation. AutoGluon is a state-of-the-art and easy-to-use toolkit that empowers multimodal AutoML. Different from most AutoML systems that focus on solving tabular tasks containing categorical and numerical features, we consider supervised learning tasks on various types of data including tabular features, text, image, time series, as well as their combinations.


Alex Smola studied physics in Munich at the University of Technology, Munich and computer science at the University of Technology in Berlin. He received a PhD in 1998.  After that, he joined the Australian National University and National ICT Australia (now part of Data61 at CSIRO) where he worked until 2008 as full professor and group leader. From 2008 to 2012 he worked at Yahoo! Research and moved to google in 2012. From 2013-17 he was full professor at Carnegie Mellon University's Machine Learning Department. Alex co-founded Marianas Labs in 2015. Since 2016 he works as VP/Distinguished Scientist at Amazon Web Services to help build AI and ML tools for everyone. His work includes Kernel Methods, Bayesian Nonparametrics, Distributed Optimization and Systems, and Deep Learning. He has published over 250 papers and five books.