Xiongxiao Xu
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Ph.D. Student |
About me
I am currently interning at Argonne National Laboratory, Illinois. Feel free to talk to me if you happen to be there. I am a Ph.D. student in the Department of Computer Science at Illinois Institute of Technology since Spring 2022, advised by Dr. Kai Shu. I received the B.S. degree in Computer Science from the Chongqing University in 2020, advised by Dr. Hong Xie. My research interests generally lie in data mining and machine learning, and their applications in high-performance computing. Previously, I work on multi-armed bandits and its application in recommender system.
Research Interests
Data Mining
Machine Learning
High-Performance Computing
Publications
Yueqing Liang, Liangwei Yang, Chen Wang, Xiongxiao Xu, Philip S. Yu, Kai Shu. "Taxonomy-Guided Zero-Shot Recommendations with LLMs", arxiv, 2024. [arxiv]
Xiongxiao Xu, Yueqing Liang, Baixiang Huang, Zhiling Lan, Kai Shu. "Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting", arxiv, 2024. [arxiv][Code]
Xiongxiao Xu, Kevin A. Brown, Tanwi Mallick, Xin Wang, Elkin Cruz-Camacho, Robert B. Ross, Christopher D. Carothers, Zhiling Lan, Kai Shu. "Surrogate Modeling for HPC Application Iteration Times Forecasting with Network Features", Proceedings of The ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), 2024. [pdf]
Elkin Cruz-Camacho, Kevin A. Brown, Xin Wang, Xiongxiao Xu, Kai Shu, Zhiling Lan, Robert B. Ross and Christopher D. Carothers. "Hybrid PDES Simulation of HPC Networks using Zombie Packets.", ACM Transactions on Modeling and Computer Simulation (TOMACS), 2024. (Recommend Publication with Minor Revisions)
Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu. "MetaGAD: Learning to Meta-Transfer for Few-shot Graph Anomaly Detection", arxiv, 2023. [arxiv]
Xiongxiao Xu. "Exploring Machine Learning Models with Spatial-Temporal Information for Interconnect Network Traffic Forecasting", Proceedings of The ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), PhD Colloquium, 2023. [pdf]
Xiongxiao Xu, Xin Wang, Elkin Cruz-Camacho, Christopher D. Carothers, Kevin A. Brown, Robert B. Ross, Zhiling Lan, Kai Shu. "Machine Learning for Interconnect Network Traffic Forecasting: Investigation and Exploitation.", Proceedings of The ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), 2023. [pdf]
Elkin Cruz-Camacho, Kevin A. Brown, Xin Wang, Xiongxiao Xu, Kai Shu, Zhiling Lan, Robert B. Ross, Christopher D. Carothers. "Hybrid PDES Simulation of HPC Networks using Zombie Packets.", Proceedings of The ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), 2023. [pdf] (Best Short Paper Award)
Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Yuan Hong, Kai Shu. "On Fair Classification with Mostly Private Sensitive Attributes", arxiv, 2022. [arxiv]
Xiongxiao Xu, Hong Xie, John C.S. Lui. "Generalized Contextual Bandits With Latent Features: Algorithms and Applications", IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2021. [pdf][Supplementary]
Awards
Starr-Fieldhouse Research Fellowship Award, 2024
Best Short Paper Award, ACM SIGSIGM-PADS, 2023
ACM SIGSIGM-PADS Student Travel Award, 2023, 2024
Internship
Argonne National Laboratory, Illinois, Summer, 2024
Talk
Machine Learning Surrogate Models for the Parallel Discrete Event Simulation, Argonne National Laboratory, Illinois, Aug. 30, 2023
Academic Services
Program Committee
The AAAI Conference on Artificial Intelligence (AAAI’24, AAAI'25)
The International Conference on Database Systems for Advanced Applications (DASFAA’24)
Reviewer
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)