Xiongye Xiao

Iโ€˜m Xiongye Xiao, currently a 5th year PhD candidate specializing in Electrical and Computer Engineering (ECE at USC). My research focuses on Network Science and Machine Learning, where I aim to develop advanced physical/mathematical/computational tools to decipher and learn the complex systems. My work primarily involves neural operators, complex network analysis, multimodal learning and generative modeling.

๐Ÿ“ƒ Journal Papers

Spanning network gels from nanoparticles and graph theoretical analysis of their structure and properties

Advanced Materials , 2022

Drew A. Vecchio, Mark D. Hammig, Xiongye Xiao, Anwesha Saha, Paul Bogdan, and Nicholas A. Kotov.

Unifying Structural Descriptors for Biological and Bioinspired Nanoscale Complexe

Nature Computational Science , 2022

Minjeong Cha, Emine Turali-Emre, Xiongye Xiao, Ji-Young Kim, Paul Bogdan, Scott VanEpps, Angela Violi, Nicholas A. Kotov.

Deciphering the generating rules and functionalities of complex networks

Nature Scientific Reports , 2021

Xiongye Xiao, Hanlong Chen, and Paul Bogdan

Generator based approach to analyze mutations in genomic datasets

Nature Scientific Reports , 2021

Siddharth Jainโ€ , Xiongye Xiaoโ€ , Paul Bogdan, and Jehoshua Bruck

A COVID-19 Rumor Dataset

Frontiers in Psychology , 2021

Mingxi Cheng, Songli Wang, Xiaofeng Yan, Tianqi Yang, Wenshuo Wang, Zehao Huang, Xiongye Xiao, Shahin Nazarian, and Paul Bogdan

Network science characteristics of brain-derived neuronal cultures deciphered from quantitative phase imaging data

Nature Scientific Reports , 2020

Chenzhong Yinโ€ , Xiongye Xiaoโ€ , Valeriu Balaban, Mikhail E. Kandel, Young Jae Lee, Gabriel Popescu, and Paul Bogdan

Biomorphic structural batteries for robotics

Science Robotics , 2020

Mingqiang Wang, Drew Vecchio, Chunyan Wang, Ahmet Emre, Xiongye Xiao, Zaixing Jiang, Paul Bogdan, Yudong Huang, and Nicholas A. Kotov

๐Ÿ“„ Conference Papers

Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations

International Conference on Learning Representations (ICLR), 2023

Xiongye Xiao, Defu Cao, Ruochen Yang, Gaurav Gupta, Gengshuo Liu, Chenzhong Yin, Radu Balan, Paul Bogdan

Non-Linear Operator Approximations for Initial Value Problems

International Conference on Learning Representations (ICLR), 2022

Gaurav Gupta, Xiongye Xiao, Radu Balan, and Paul Bogda

Multiwavelet-based operator learning for differential equations

dvances in Neural Information Processing Systems (NeurIPS), 2021 [Spotlight, top 2%]

Gaurav Gupta, Xiongye Xiao, Radu Balan, and Paul Bogda

๐Ÿ“– Book Chapter

AI and the Clinical Immunology/Immunoinformatics for COVID-19

Artificial Intelligence in Covid-19

Zikun Yang, Xiongye Xiao, and Paul Bogdan