The University of Alberta’s Faculty of Science is pleased to announce the inaugural recipient of the AltaML Professorship in Natural Language Processing, Lili Mou.
Mou joins the Department of Computing Science as an assistant professor, following graduate studies at Peking University and a postdoctoral fellowship at the University of Waterloo.
AltaML is an Alberta-based machine learning company, co-founded by UAlberta alumni Cory and Nicole Janssen. Their work is focused on building applications powered by applied machine learning to drive innovation in industry. Late last year, the company established the AltaML Professorship in Natural Language Processing in the Faculty of Science.
“Entrepreneurs and industry alike have a massive opportunity because of the world-class talent at UAlberta. These professors are the draw to bring the best and brightest from around the world to Edmonton,” said Cory Janssen, AltaML’s CEO. “The spirit of this agreement is to create additional opportunities for research collaboration through industry involvement. We believe the end result will be real commercial enterprises built on applied AI that will keep jobs—and thus graduates—here in Alberta.”
Natural language processing, a subset of artificial intelligence that explores interactions between computers and human languages, is viewed as a powerful way to turn the mass amounts of data being created in today’s technology-driven society into knowledge, furthering the innovation of all industries and contributing to continued economic diversification in Alberta and Canada.
At the forefront of this cutting-edge research area is Mou. In his work, Mou’s ultimate goal is to build an artificial intelligence system that can interact with humans through language. This means creating a system that can understand a person’s natural way of speaking and respond in kind.
Learn more about Mou’s upcoming work at UAlberta.
Tell us about your research program in the area of natural language processing.
My research mission is to build an intelligent system that can understand and interact with humans via natural language, involving both text understanding and text generation. Towards this long-term goal, I am focusing on fundamental problems in machine learning (especially deep learning) methods applied to natural language processing. My work has been successfully applied to various natural language processing tasks, including information extraction, sentiment analysis, semantic parsing, syntactic parsing, dialogue systems, paraphrase generation, grammatical error correction, and many others.
What inspired you to enter this field?
My research started from software engineering and program analysis when I was a PhD student at the Software Engineering Institute at Peking University in Beijing, China. At that time, we were one of the earliest groups applying deep learning to program source code, and I proposed a tree-based convolutional neural network (TBCNN) to analyze the parse tree of a program. I found my TBCNN model worked for natural language parse trees as well, so I started to do natural language processing (NLP) research. I found NLP research very interesting, as it is one of the core problems of artificial intelligence.
Tell us about your teaching.
I teach CMPUT 651 Deep Learning for NLP and CMPUT 466 Introduction to Machine Learning.
I believe courses are essential steps to cutting-edge research. I hope my courses not only build a solid foundation of knowledge and skills, but also point to the frontier of research.
Welcome, Professor Mou.