Me
Xiaoda Wang (王晓达)
CS Ph.D. Student @ Emory

About

I am a second-year Computer Science Ph.D. student at Emory University, fortunately advised by Prof. Carl Yang. I also collaborate closely with Prof. Yizhou Sun and Prof. Wei Wang at UCLA. I obtained my B.S. degree in Computer Science from Sichuan University, where I was honored to be advised by Prof. Mingjie Tang.

My research focuses on LLM reasoning, time-series foundation models and generative models for healthcare applications.

I am looking for summer 2026 industry research internship opportunities. Feel free to reach out if there is a good fit!

Education

Ph.D.           Sep. 2024 - Present
                     Emory University, Atlanta, GA, U.S.
                     Ph.D. student in Computer Science
                     Advisor: Prof. Carl Yang
B.S.              Sep. 2020 - Jun. 2024
                     Sichuan University (SCU), Chengdu, China.
                     B.S. in Computer Science
                     Advisor: Prof. Mingjie Tang
IIRP              Jan. 2023 - Feb. 2023
                     University of Cambridge, Cambridge, United Kingdom.
                     Innovation and Interdisciplinary Research Programme (IIRP)
                     Thesis Project: Financial Fraud Detection using Graph Neural Networks

News

  • Our paper SE-Diff on Diffusion Models is now available on arXiv!
  • Our paper ECG-MOE on ECG foundation models has been accepted by NeurIPS 2025 TS4H. See you in San Diego!
  • Our paper CNODE on Conditional neural ODEs has been accepted by BIBM 2025!
  • Our survey on Graph ODEs and Beyond has been accepted by KDD 2025!
  • Our paper EnECG on ECG foundation models has been accepted by AMIA 2025.
  • Our paper Couler has been accepted by ICDE 2024.

Selected Publications and Manuscripts (Full List: here)

Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generation
Xiaoda Wang, Kaiqiao Han, Yuhao Xu, Xiao Luo, Yizhou Sun, Wei Wang, Carl Yang
[ Paper]
Preprint, 2025
ECG-MoE: Mixture-of-Expert Electrocardiogram Foundation Model
Yuhao Xu, Xiaoda Wang, Yi Wu, Wei Jin, Xiao Hu, Carl Yang
[ Paper]
NeurIPS 2025 Workshop on Learning from Time Series for Health (TS4H)
Conditional Neural ODE for Longitudinal Parkinson's Disease Progression Forecasting
Xiaoda Wang, Yuji Zhao, Kaiqiao Han, Xiao Luo, Sanne van Rooij, Jennifer Stevens, Lifang He, Liang Zhan, Yizhou Sun, Wei Wang, Carl Yang
[ Paper] [ Poster] [ Abstract version]
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025
Abstract version at the Organization for Human Brain Mapping (OHBM), 2025
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks
Zewen Liu*, Xiaoda Wang*, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin (* equal contribution)
[ Paper] [ Website]
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
EnECG: Efficient Ensemble Learning for Electrocardiogram Multi-task Foundation Model
Yuhao Xu, Xiaoda Wang, Jiaying Lu, Sirui Ding, Defu Cao, Huaxiu Yao, Yan Liu, Xiao Hu, Carl Yang
[ Paper]
American Medical Informatics Association (AMIA) Annual Summit, 2025
BadDet: Blockchain Fraud Detection with Dynamic Address-Transaction Graph Convolutional Networks
Xiaoda Wang, Zhaoyi Liu, Tengda Guo, Zhiyuan Cheng, Carl Yang, Mingjie Tang
In submission, 2025
Couler: Unified Machine Learning Workflow Optimization in Cloud
Xiaoda Wang, Yuan Tang, Tengda Guo, Bo Sang, Jingji Wu, Jian Sha, Ke Zhang, Jiang Qian, Mingjie Tang
[ Paper] [ Github] [ Project Website]
IEEE International Conference on Data Engineering (ICDE), 2024
BGEK: External Knowledge-Enhanced Graph Convolutional Networks for Rumor Detection in Online Social Networks
Xiaoda Wang, Chenxiang Luo, Tengda Guo, Zhangrui Liu, Jiongyan Zhang, Haizhou Wang
[ Paper] [ Code]
International Conference on Artificial Neural Networks (ICANN), 2023
A Metadata-Aware Detection Model for Fake Restaurant Reviews Based on Multimodal Fusion
Yifei Jian, Xinyu Chen, Xiaoda Wang, Ying Liu, Xingshu Chen, Xiao Lan, Wenxian Wang, Haizhou Wang
[ Paper]
Neural Computing and Applications, 2025

Selected Honors & Awards

Teaching

Academic Services

Conference Reviewer: ICLR 2026; NeurIPS 2025; ICML 2025; AMIA 2025; KDD 2025, 2024; WWW 2025; SIGIR 2025; IJCAI 2025; AAAI 2025.
Journal Reviewer: PKDD 2025; ACM Health 2025; TNNLS 2025, 2024.

Miscellaneous

I love F1, driving, hiking, traveling, and photography.
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