Xiongxiao Xu

Ph.D. Student Department of Computer Science Illinois Institute of Technology Chicago, Illinois, United States E-mail: xxu85@hawk.iit.edu

About me

I am a second-year 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, including time-series forecasting and graph learning with their applications in HPC system and anomaly detection. Previously, I work on multi-armed bandits and its application in recommender system.

Research Interests

• Data Mining

• Machine Learning

• High-Performance Computing

Publications

1. Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu. "MetaGAD: Learning to Meta-Transfer for Few-shot Graph Anomaly Detection", arxiv, 2023. [arxiv]

2. 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]

3. 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), Short Paper, 2023. [pdf]

4. 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), Short Paper, 2023. [pdf] (Best Short Paper Award)

5. Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Yuan Hong, Kai Shu. "On Fair Classification with Mostly Private Sensitive Attributes", arxiv, 2022. [arxiv]

6. 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

• Best Short Paper Award, ACM SIGSIGM-PADS, 2023

• ACM SIGSIGM-PADS Student Travel Award, 2023

Talk

• Machine Learning Surrogate Models for the Parallel Discrete Event Simulation, Argonne National Laboratory, Lemont, IL, Aug. 30, 2023

Academic Services

Program Committee

• The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI’24)

Reviewer

• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)