UA Little Rock professor selected for DeepLearn 2019

Dr. Xiaowei Xu. Photo by Ben Krain.

A University of Arkansas at Little Rock professor has been selected as one of the pioneers in the field of deep learning who will teach the subject during a prestigious international summer program in Warsaw, Poland, from July 22-26. 

Dr. Xiaowei Xu, UA Little Rock professor of information science, was chosen as a teacher for DeepLearn 2019, a research training event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. Renowned academics and industry pioneers will lecture and share their views with the audience.

Deep learning is a branch of artificial intelligence covering a spectrum of machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data over a broad range of fields, including neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, robotics, cybersecurity, and games.

Xu will teach introductory and advanced classes on “Multi-resolution Models for Learning Multilevel Abstract Representations of Text.” The class will cover new deep learning models that comes out of Dr. Xu’s own research in collaboration with his Ph.D. students.

“The new multi-resolution model can comprehend natural language text like human beings,” he said. “It is fundamental for many applications including question answering and virtual assistants such as Google Assistant, Apple Siri, and Amazon Alexa.”    

Xu earned a Bachelor of Science in mathematics from Nankai University, a Master of Science in computer science from the Chinese Academy of Science, and a Ph.D. in computer science from Ludwig-Mizimillians-Universität.

His research includes data mining, big data, and machine learning. In November, 2018 Xu and Tolgahan Cakaloglu, a doctoral candidate in computer science, received a $20,000 Google AI research grant for their research in artificial intelligence and machine learning for their project, “Contextual Advanced Text Representation via Improved Deep Language Model by Utilizing Side Information.”

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