Research Support

My research group is generously supported by the following organizations.

1. Northeastern University start-up funding for early-career faculty.

2. National Science Foundation.

Research Topics and Related Papers

[Google Scholar]

1. Causal Discovery and Inference:

   • Papers: 13, 14 

2. Federated Learning:

   • Papers: 4, 5, 6, 10, 11, 12, 13, 14, 15

3. Additive Manufacturing:

   • Papers: 13

4. Material Discovery:

   • Papers: 11, 12

5. Gaussian Process: 

   • Papers: 1, 8, 10

6. Bayesian Optimization:

   • Papers: 2, 11, 12

7. Optimization of Deep Neural Network:

   • Papers: 7

8. Physics-informed Neural Network:

   • Paper: 9

9. Others (Joint Longitudinal-Survival Model, Parameter Calibration):

   • Papers: 1, 3, 15

Publications

* Students advised by Yue;

** Yue as the corresponding author. 

1. Yue, X., Kontar, R. (2020), "Joint Models for Event Prediction from Time Series and Survival Data." [link] [code]

   • Technometrics.

   • Finalists for the QCRE Best Student Paper Competition, Institute of Industrial and Systems Engineers (IISE), 2019. 

2.  Yue, X., Kontar, R. (2020), "Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout." [link]

   • International Conference on Artificial Intelligence and Statistics (AISTATS, 2020).

3. Liu B., Yue, X., Byon, E., Kontar, R. (2021), "Parameter Calibration in wake effect simulation model with Stochastic Gradient Descent and stratified sampling." [link]

   • Annals of Applied Statistics (AOS).

   • Finalists for the DAIS Best Student Paper Competition, IISE annual conference, 2021.

   • Finalists for the DAIS Best Paper Competition, IISE annual conference, 2021.

4. Kontar, R., Shi, N., Yue, X. et al. (2021), "The Internet of Federated Things (IoFT)." [link]

   • IEEE Access.

   • Featured IEEE Access article. [link] 

5. Yue, X., Nouiehed, M., Kontar, R. (2022), "GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning." [link]

   • INFORMS Journal on Data Science (IJDS).

   • Finalists for the QSR Best Paper Competition, INFORMS annual meeting, 2021.

   • One of the Most Read and Cited Articles in IJDS.

   • IJDS Best Paper Award, 2024.

6. Yue, X., Estrada Gómez, A. M., Kontar, R. (2022), "Federated Data Analytics: A Study on Linear Models." [link]

   • IISE Transactions. 

   • Featured Article in the December 2023 issue of the Industrial and Systems Engineering (ISE) Magazine.

7. Yue, X., Nouiehed, M., Kontar, R. (2023), "SALR: Sharpness-aware Learning Rates for Improved Generalization." [link]

   • IEEE Transactions on Neural Networks and Learning Systems (IEEE-TNNLS). Impact Factor: 14.255 (2022-2023)

8. Yue, X., Kontar, R. (2023), "An Alternative Gaussian Process Objective Based on the Rényi Divergence." [link] [code]

   • IISE Transactions. 

   • 2020 Richard C. Wilson Prize (The Best Student Paper Winner). 

   • Finalists for the INFORMS Virtual Workshop on Data Mining and Decision Analytics Best Paper Competition (Theoretical Section), 2020. 

9. Gnanasambandama, R, Shen, B, Chung, J, Yue,  X, and Kong, Z. (2023), "Self-scalable Tanh (Stan): Faster Convergence and Better Generalization in Physics-informed Neural Networks." [link]

   • IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI). Impact Factor: 24.314 (2022-2023)

   • Implemented, verified, and cited by NVIDIA [link].

   • Finalists (Winner) for the IISE QCRE/ProcessMiner Data Challenge Competition, IISE annual conference, 2022. 

   • Winner of the DMDA Workshop Best Poster Competition, INFORMS annual meeting, 2022.  

10. Yue, X., Kontar, R. (2024), "Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling." [link]

    • IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI). Impact Factor: 24.314 (2022-2023)

    • Finalists for the DM Best Student Paper Competition, INFORMS annual meeting, 2022.

    • Finalists for the JSM SPES+Q&P Student Paper Competition, Joint Statistical Meetings, 2023.

11. Liu, Y., Yue, X., Zhang, J., Zhai, Z., Moammeri, A., Edgar, K., Berahas, A., Kontar, R., Johnson, B. (2024), "Scalable Self-driving Accelerated Materials Discovery of Sustainable Polysaccharide-based Functional Composite Hydrogels by Autonomous Experimentation and Collaborative Learning." [link]

    • ACS Applied Materials & Interfaces.

12.  Yue,  X, Kontar, R, Berahas, AS, Liu, Y, Zhai, Z, Edgar, K, Johnson BN. (2025), "Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design." [link]

    • IEEE Transactions on Automation Science and Engineering (IEEE-TASE).

13. Xiao, X.*, Alharbi, K., Zhang, P., Qin, H., Yue, X. ** (2025), "Explainable Federated Bayesian Causal Inference and Its Applications in Advanced Manufacturing." [link]

    • Journal of Intelligent Manufacturing (JIMS).

14. Chen, J.*, Ma, Y., Yue, X.** (2025), "Temporal Causal Discovery in Dynamic Bayesian Networks Using Federated Learning." [link]

15. Jeong, C., Yue, X., Chung, S. (2025), "Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning." [link]

16. Xiao, X.*, Shen, B., Yue, X. ** (2025), "Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations." [link]

17. Chen, J.*, Zhao, M., Reisi, M., Yue, X.** (2025+), "Toward Temporal Causal Representation Learning with Tensor Decomposition." [link]

18. Yue, X.**, Xiao, X.*, Chen, J.*, and others, "TBA."

Software

1.  Yue, X., Hsu, C., Kang, J. (2019), "The brainKCCA Package: Building Region-level Functional Connectivity Network." [link]