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Graduate assistant positions (for Ph.D. students only) are available in my group. Please contact me directly if you are interested in any one of my research areas.
Tong Shu joined the School of Computing at Southern Illinois University Carbondale as an assistant professor in August 2020. Before that, she 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.
- Parallel Systems
- Scalable Deep Learning 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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- Ph.D. in Computer Science, New Jersey Institute of Technology, Newark, NJ, USA
- M.S. in Computer Science, University of Memphis, Memphis, TN, USA
- Thesis: Advance Bandwidth Scheduling for Energy Efficiency in High-performance Networks [ PDF | BibTex ]
- B.S. in Information Management and System, Peking University, Beijing, China
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My Google Scholar Profile
- Journal Articles
- I. Foster, M. Ainsworth, J. Bessac, F. Cappello, J. Choi, S. Di, Z. Di, A. M. Gok, H. Guo, K. A. Huck, C. Kelly, S. Klasky, K. K. van Dam, X. Liang, K. Mehta, M. Parashar, T. Peterka, L. Pouchard, T. Shu, O. Tugluk, H. van Dam, L. Wan, M. Wolf, J. M. Wozniak, W. Xu, I. Yakushin, S. Yoo, and T. Munson. Online Data Analysis and Reduction: An Important Co-design Motif for Extreme-scale Computers. SAGE International Journal of High Performance Computing Applications, Jun 2021. [ Preprint | BibTex ]
- T. Shu and C. Q. Wu. Energy-efficient Mapping of Large-scale Workflows under Deadline Constraints in Big Data Computing Systems. Elsevier Future Generation Computing Systems, vol. 110, pp. 515-530, Sep 2020. [ Preprint | BibTex ]
- J. M. Wozniak, M. Dorier, R. Ross, T. Shu, T. Kurc, L. Tang, N. Podhorszki, and M. Wolf. MPI Jobs within MPI Jobs: a Practical Way of Enabling Task-level Fault-tolerance in HPC Workflows. Elsevier Future Generation Computing Systems, vol. 101, pp. 576-589, Dec 2019. [ Preprint | BibTex ]
- T. Shu and C. Q. Wu. Bandwidth Scheduling for Energy-efficiency in High-performance Networks. IEEE Transactions on Communications, vol. 65, no. 8, pp. 3359-3373, Aug 2017. [ Preprint | BibTex ]
- T. Shu, M. Liu, A. Zhou, and Z. Li. A Fairness Optimization Algorithm of Variable Spectral Widths and Time-Slot Lengths in Wireless Mesh Networks. Chinese Journal of Computers, vol. 34, no. 1, pp. 65-75, Jan 2011. [ Preprint | BibTex ]
- T. Shu, M. Liu, and Z. Li. Performance Analysis of a Network-layer Soft Vertical Handoff Scheme without Packet Reordering. Chinese Journal of Computers, vol. 33, no. 1, pp. 23-35, Jan 2010. [ Preprint | BibTex ]
- Conference Papers
- T. Shu, Y. Guo, J. Wozniak, X. Ding, I. Foster, and T. Kurc. Bootstrapping In-Situ Workflow Auto-Tuning via Combining Performance Models of Component Applications. In Proc. of ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), article no. 28, pp. 1-15, St. Louis, MO, USA, Nov 14th-19th 2021. (Acceptance rate: 23.6% = 86/365) [ Preprint | BibTex ]
- T. Shu and C. Q. Wu. Performance Optimization of Hadoop Workflows in Public Clouds through Adaptive Task Partitioning. In Proc. of the 36th IEEE International Conference on Computer Communications (INFOCOM), pp. 2349-2357, Atlanta, GA, USA, May 1st-4th 2017. (Acceptance rate: 20.9%) [ Preprint | BibTex ]
- T. Shu and C. Q. Wu. Energy-efficient Dynamic Scheduling of Deadline-constrained MapReduce Workflows. In Proc. of the 13th IEEE International Conference on e-Science (eScience), pp. 393-402, Auckland, New Zealand, Oct 24th-27th 2017. (Acceptance rate: 36%) [ Preprint | BibTex ]
- T. Shu, C. Q. Wu, and D. Yun. Advance Bandwidth Reservation for Energy Efficiency in High-performance Networks. In Proc. of the 38th IEEE Conference on Local Computer Networks (LCN), pp. 541-548, Sydney, Australia, Oct 21st-24th 2013. (Acceptance rate: 26.4%) [ Preprint | BibTex ]
- T. Shu, M. Liu, Z. Li, and Q. Wu. Interference Pair-Based Distributed Spectrum Allocation in Wireless Mesh Networks with Frequency-Agile Radios. In Proc. of the 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pp. 82-90, Salt Lake City, UT, USA, Jun 27th-30th 2011. (Acceptance rate: 27.4%) [ Preprint | BibTex ]
- T. Shu, M. Liu, and Z. Li. Spectrum Allocation for Distributed Throughput Maximization under Secondary Interference Constraints in Wireless Mesh Networks. In Proc. of the 20th IEEE International Conference on Computer Communications and Networks (ICCCN), 6 pages, Maui, HI, USA, Jul 31st-Aug 4th 2011. (Acceptance rate: 29.6%) [ Preprint | BibTex ]
- A. Zhou, M. Liu, T. Shu, Y. Song, and Z. Li. Exploiting the Full Potential of Multi-AP Diversity in Centralized WLANs through Back-pressure Scheduling. In Proc. of the 36th IEEE Conference on Local Computer Networks (LCN), pp. 505-513, Bonn, Germany, Oct 4th-7th 2011. (Acceptance rate: 29.3%) [ Preprint | BibTex ]
- T. Shu, M. Liu, Z. Li, and A. Zhou. A Diagnosis-Based Soft Vertical Handoff Mechanism for TCP Performance Improvement. In Proc. of the 19th IEEE International Conference on Computer Communications and Networks (ICCCN), 6 pages, Zurich, Switzerland, Aug 2nd-5th 2010. (Acceptance rate: 33.9%) [ Preprint | BibTex ]
- T. Shu, M. Liu, Z. Li, and A. Zhou. Joint Variable Width Spectrum Allocation and Link Scheduling for Wireless Mesh Networks. In Proc. of IEEE International Conference on Communications (ICC), 5 pages, Cape Town, South Africa, May 23rd-27th 2010. (Acceptance rate: 39.5%) [ Preprint | BibTex ]
- T. Shu, M. Liu, and Z. Li. A Performance Evaluation Model for RSS-based Vertical Handoff Algorithms. In Proc. of the 14th IEEE Symposium on Computers and Communications (ISCC), pp. 271-276, Sousse, Tunisia, Jul 5th-8th 2009. (Acceptance rate: 35.9%) [ Preprint | BibTex ]
- Workshop Papers, Short Papers, and Posters
- T. Shu, Y. Guo, J. Wozniak, X. Ding, I. Foster, and T. Kurc. POSTER: In-situ Workflow Auto-tuning through Combining Component Models. In Proc. of 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 467-468, Virtual Event, Seoul, South Korea, Feb 27th-Mar 3rd, 2021. [ Preprint | BibTex ]
- J. Wozniak, P. E. Davis, T. Shu, J. Ozik, N. Collier, I. Foster, T. Brettin, and R. Stevens. Scaling Deep Learning for Cancer with Advanced Workflow Storage Integration. In Proc. of the 4th Workshop on Machine Learning in HPC Environments in conjunction with ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), pp. 114-123, Dallas, TX, USA, Nov 11th-12th 2018. [ Preprint | BibTex ]
- T. Shu and C. Q. Wu. Energy-efficient Mapping of Big Data Workflows under Deadline Constraints. In Proc. of the 11th Workshop on Workflows in Support of Large-Scale Science (WORKS) in conjunction with ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), pp. 34-43, Salt Lake City, UT, USA, Nov 14th 2016. (Acceptance rate: 29.4%) [ Preprint | BibTex ]
- T. Shu, M. Liu, Z. Li, and K. Zheng. Network-layer Soft Vertical Handoff Schemes without Packet Reordering (short paper). In Proc. of the 34th IEEE Conference on Local Computer Networks (LCN), pp. 285-288, Zurich, Switzerland, Oct 20th-23rd 2009. [ Preprint | BibTex ]
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- Pending proposals
- NSF CRII: OAC: Adaptive Auto-Tuning for Online Scientific Workflows, $175,000, 05/01/2022-04/30/2024, PI
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Assistant professor, School of Computing, Southern Illinois University Carbondale (Aug 2020 - Present)
- Courses for undergraduates
- CS311 Theory and Implementation of Programming Languages (Spring 2021, Fall 2021)
- Courses for seniors and graduates
- CS485 Computer Graphics and Visualization (Fall 2020, Fall 2021)
- Course for master and Ph.D. students
- CS520 Parallel and Distributed Computing (Spring 2022)
Teaching assistant, Department of Computer Science, University of Memphis (Sep 2012 - Apr 2014)
- Courses for seniors and graduates
- COMP4030/6030 Design and Analysis of Algorithms (Spring 2014)
- COMP4040/6040 Programming Languages (Fall 2012, Spring 2014)
- COMP4302/6302 Web Services and the Internet (Spring 2013)
- COMP4601/6601 Models of Computation (Fall 2013)
- Course for master and Ph.D. students
- COMP7125/8125 Computer Forensics (Fall 2013)
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- High-performance Computing with Machine Learning Techniques
Postdoctoral Appointee, at Data Science and Learning/Mathematics and Computer Science Division, Argonne National Laboratory (Oct 2017 - Aug 2020)
- US Department of Energy: ECP CODAR: Co-design center for Online Data Analysis and Reduction at the exascale
- Design machine learning-based auto-tuning algorithms to optimize configurations of in-situ workflows;
- Develop an HPC application auto-tuner in Swift/T and Python with Keras and Tensorflow;
- Implement source code of Swift/T, parallel programming language for high-performance dataflow computing.
- US Department of Energy: ECP CANDLE: CANcer Distributed Learning Environment
- Big Data Processing and Transfer
- Research Assistant, at Big Data Lab, New Jersey Institute of Technology (Aug 2015 - Sep 2017)
US National Science Foundation: An Integrated Approach to Performance Modeling and Optimization of Big-data Scientific Workflows
- Explored the performance bottleneck of Hadoop/YARN and Spark;
- Designed algorithms to minimize the makespan and energy consumption of MapReduce workflows;
- Implemented the proposed algorithms in Hadoop/YARN, Oozie, and Spark.
- Research Assistant, at High-performance Networking and Computing Group, University of Memphis (Sep 2012 - Apr 2014)
US Department of Energy: Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments
- Designed bandwidth scheduling algorithms to minimize the energy consumption of big data transfer;
- Implemented the large-scale simulation in C++.
- Computational Healthcare and Natural Language Processing
Research Assistant, at the Institute of Intelligent Systems, University of Memphis (May 2014 - Apr 2015)
- FedEx Institute of Technology: Technical Research in Alzheimer's Care
- Implemented a prototype tutoring application in Java on Android 4.3 on Google Nexus 7" tablet;
- Implemented a RESTful Web API server in C# for storing data from tablets to a MongoDB database.
- Institute of Education Sciences: DeepTutor: An Intelligent Tutoring System Based on Deep Language and Discourse Processing and Advanced Tutoring Strategies
- Explored a semantic similarity toolkit in Java for assessing the semantic similarity between two texts;
- Processed natural language by adding annotations according to a set of guidelines.
- Wireless Networking and Mobile Computing
Research Assistant, at the Institute of Computing Technology, Chinese Academy of Sciences (Sep 2005 - Jul 2011)
- Spectrum allocation algorithms in wireless mesh networks with frequency-agile radios
- Vertical handoff in heterogeneous wireless networks
- Multimedia terminals to support mobile IPv6
- Technologies for the integration of WLANs and WWANs and service demonstration
- A multimedia session service system to support mobility / roaming
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- Conferences and Workshops
- Technical program committee member for
- ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) 2022
- The 16th Workshop on Workflows in Support of Large-Scale Science (WORKS) in conjunction with ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC) 2021
- IEEE International Conference on Distributed Computing Systems (ICDCS) 2020
- IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC) 2020
- IARIA International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM) 2019
- The 14th International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems (SRMPDS) in conjunction with International Conference on Parallel Processing (ICPP) 2018
- IEEE Global Telecommunications Conference (GLOBECOM) 2013
- IEEE Wireless Communications and Networking Conference (WCNC) 2010, 2011, 2012, and 2013
- IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) 2012
- Reviewer for
- IEEE International Conference on Communications (ICC) 2019
- IEEE International Conference on Computing, Networking and Communications (ICNC) 2019
- IEEE International Conference on Big Data (BigData) 2018
- IEEE International Congress on Big Data (Big Data Congress) 2018
- IEEE International Conference on Distributed Computing Systems (ICDCS) 2017
- Journals
- Reviewer for
- IEEE Transactions on Parallel and Distributed Systems in 2020 and 2021
- Wiley Networks in 2021
- IEEE Transactions on Industrial Informatics in 2020
- IEEE Transactions on Cloud Computing in 2019
- Wiley Concurrency and Computation: Practice and Experience in 2019 and 2021
- Hindawi Scientific Programming in 2019
- IEEE Transactions on Big Data in 2017 and 2018
- Elsevier Journal of Parallel and Distributed Computing in 2018
- PLOS PLOS One in 2018
- Hindawi Journal of Engineering in 2018
- SAGE International Journal of Distributed Sensor Networks in 2011, 2012, and 2018
- Books
- Reviewer
- Programming Massively Parallel Processors at Elsevier in 2021
- Computer Science at Springer in 2018
- Proposals
- Panelist/ad-hoc reviewer for US National Science Foundation (NSF) Small Business Innovation Research (SBIR) Program in 2019
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- Ph.D. students
- Turja Kundu (from Fall 2021, B.S. in computer science and engineering from Bangladesh University of Engineering and Technology)
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