2026

Choi, Y., S. W. Cheung, Y. Kim, P.-H. Tsai, A. N. Diaz, I. Zanardi, S. W. Chung, D. M. Copeland, C. Kendrick, W. Anderson, X. He, T. Iliescu, and M. Heinkenschloss. 2026. "Rigor Over Hype: What Foundation Model Should Mean in Computational Science." Computing in Science & Engineering.

Dey, A., and Y. R. Gel. 2026. “Integrating Statistical Data Depth and Topological Methods for Anomaly Detection in Weighted Dynamic Networks.” Technometrics. https://doi.org/10.1080/00401706.2026.2643214.

Iliakis, E., W. G. Y Tan, L. Wu, J. Drgona, and R. D. Braatz. 2026. “Polynomial Parametric Koopman Operators for Stochastic MPC.” arXiv preprint https://arxiv.org/pdf/2604.00935

Jnini, A., E. Kiyani, K. Shukla, J. F. Urbán, N. Ahmadi Daryakenari, J. Müller, M. Zeinhofer, and G.E. Karniadakis. 2026. “Curvature-aware optimization for high-accuracy physics-informed neural networks.” arXiv preprint. https://doi.10.48550/arXiv.2604.05230.

Larsson, A., M. Kim, C. Vales, S. Adriaenssens, D. M. Copeland, Y. Choi, and S. W. Cheung. 2026. "Hyper-reduction methods for accelerating nonlinear finite element simulations: open-source implementation and reproducible benchmarks." arXiv preprint arXiv:2602.23551.

Liu, S., L. Wu, D. Zhang, J. Drgona, and C. Belta. 2026. “Koopman-Based Linear MPC for Safe Control using Control Barrier Functions.” https://arxiv.org/pdf/2603.21070

Liu, S., P. Chen, Y. Lee, and J. Darbon. 2026. “Algorithms and differential game representations for exploring nonconvex Pareto fronts in high dimensions.” arXiv preprint. https://doi.10.48550/arXiv.2602.11515.

Liu, Y., K. Wang, C. Yang, Y. R. Gel, and Y. Chen. 2026. “TEN-DM: Topology-Enhanced Diffusion Model for Spatio-Temporal Event Prediction.” Proceedings of The International Conference on Learning Representations (ICLR).

Park, J. S. R., A. H. Hashim, S. W. Cheung, Y. Choi, and Y. Shin. 2026. "WGFINNs: Weak formulation-based GENERIC formalism informed neural networks." arXiv preprint arXiv:2604.02601.

Southworth, B. S., S. Jiang, D. McBride, E. C. Cyr, S. Thomas. 2026. "Muon in Vision Transformers: Optimizer-Recipe Interactions and Gradient Spectra." arXiv preprint arXiv:2605.24770.

Stinis P. 2026. "Enhancing classification accuracy through chaos." arXiv preprint arXiv.2603.15299

Wang, S., Z. Zhang, I. Lyngaas, H. Yoon, J. Choi, S. Liang, J. Wang, H. G. Chipilski, A. M. Aji, F. Bao, P. J. van Leeuwen, D. Lu, and G. Zhang. 2026. “Global attention with linear complexity for exascale generative data assimilation in Earth system prediction.” arXiv preprint https://arxiv.org/abs/2604.16590

Wu, L., Y. Che, W. G. Y Tan, E. Iliakis, R. D. Braatz, and J. Drgona. 2026. “Fixed-time-stable ODE Representation of Lasso.” In IEEE Control Systems Letters 10: 373–378. https://doi.10.1109/LCSYS.2026.3694505.

Wu, L., W. G. Y Tan, L. Zhou, R. D. Braatz, and J. Drgona. 2026. “Least-squares Multi-Step Koopman Operator Learning for Model Predictive Control.” arXiv preprint https://arxiv.org/pdf/2601.11901

Wu, L., B. Yang, J. Li, X. Yang, Y. Mo, Y. Shi, A. D. Ames, and J. Drgona. 2026. “πMPC: A Parallel-in-horizon and Construction-free NMPC Solver.” arXiv preprint https://arxiv.org/pdf/2601.14414

Wu, L., W. G. Y Tan, R. D. Braatz, and J. Drgona. 2026, “Koopman-BoxQP: solving large-scale NMPC problems at kHz Rate.” In press by 8th Annual Learning for Dynamics & Control Conference, available at https://arxiv.org/pdf/2602.18331

Wu, L., Y. Che, B. Yang, K. Lin, and J. Drgona. 2026. “Time-Certified and Efficient NMPC via Koopman Operator.” arXiv preprint https://arxiv.org/pdf/2602.15596

Zhen, Z., Y. Chen, and Y. R. Gel. 2026. “Statistical Contrastive Learning for Spatio-Temporal Anomaly Detection.” Data Science in Science 5: 2648108.

2025

Cao, Q., S. Liu, A. J. Varghese, J. Darbon, M. Triantafyllou, and G.E. Karniadakis. 2025. “Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions.” arXiv preprint https://doi.10.48550/arXiv.2501.12215.

Chen, Y., and Y. R. Gel. 2025. “Bringing Shape to Spatio-Temporal Graph Contrastive Learning.” Proceedings of the 2025 IEEE International Conference on Big Data.

Eisenlohr, J., Y. Choi, and M. Murillo. 2025. "Fourier–Thermodynamic Latent Modeling for Temperature-Dependent Plasma Mixing." Machine Learning and the Physical Sciences Workshop, NeurIPS 2025.

Tatsuoka, C., M. Yang, D. Xiu, and G. Zhang. 2025. “Multi-fidelity parameter estimation using conditional diffusion models.” arXiv preprint https://arxiv.org/abs/2504.01894. 

Wu, L., Y. Che, R. D. Braatz, and J. Drgona. 2025. “A Time-certified Predictor-corrector IPM Algorithm for Box-QP.” In IEEE Control Systems Letters 9: 3059–3064. https://doi.10.1109/LCSYS.2025.3647842.

Zhang, Z., C. Tatsuoka, D. Xiu, and G. Zhang. 2025. “Exact conditional score-guided generative modeling for amortized inference in uncertainty quantification.” arXiv preprint https://arxiv.org/abs/2506.18227.