<?xml version="1.0" encoding="UTF-8"?><item href="/people/tong-shu.html" dsn="people"><first_name>Tong</first_name><last_name>Shu</last_name><prefixes/><pronouns/><post_nominals/><title-1>Assistant Professor</title-1><title-2/><title-3/><title-4/><department>Computer Science and Engineering</department><expertise>Artificial Intelligence and Data Engineering,Computational Systems and Sciences</expertise><type>Full-Time Faculty</type><email>Tong.Shu@unt.edu</email><phone/><image><img src="/people/images/tong_shu.jpg" alt="Tong Shu"/></image><office>Discovery Park F277</office><address/><office-hours>Office Hours:<br/>Mon 4:45 - 5:45 pm<br/>Wed 4:45 - 5:45 pm</office-hours><types><type>Full-Time Faculty</type></types><departments><department>Computer Science and Engineering</department></departments><expertise-list><expertise>Artificial Intelligence and Data Engineering</expertise><expertise>Computational Systems and Sciences</expertise></expertise-list><main-content>Faculty Info | Website |
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Education


Ph.D. in Computer Science, New Jersey Institute of Technology
M.S. in Computer Science, University of Memphis, Memphis
B.S. in Information Management and System, Peking University




Biography

Tong Shu joined the Department of Computer Science and Engineering at the University of North Texas as an assistant professor in August 2022. Before that, she was an assistant professor in the School of Computing at Southern Illinois University Carbondale from August 2020 to August 2022, and worked as a postdoctoral appointee under the supervision of Dr. Justin M. Wozniak and Prof. Ian T. Foster in Data Science and Learning/Mathematics and Computer Science Division at Argonne National Laboratory from October 2017 to August 2020.



Research


Parallel Systems

Resource-Aware Neural Architecture Search Systems
Parallel Programming Language for High-performance Dataflow Computing
Scientific Workflow Optimization


Machine/Deep Learning

Neural Architecture Search
Empirical Model-based Auto-tuning


Data Science

In-situ Workflows
Big Data Processing


Distributed Systems

Energy Efficiency
Cloud Computing
Bandwidth Scheduling in Software-defined Networks
Resource Allocation and Mobile Computing in Wireless Networks






 
 


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