2019
- Hasnain, A., Boddupalli, N., Yeung, E. A data-driven Koopman framework for programming the steady state of biological systems with parametric uncertainty, submitted to the 2020 Proceedings of the IEEE American Control Conference. [preprint]
- Liu, Z., Chen, L., Ding, G., and Yeung E. 2019 Towards scalable koopman operator learning: convergence rates and distributed implementation, submitted to the 2020 Proceedings of the IEEE American Control Conference. [preprint]
- Sinha, S., Nandanoori, S., and Yeung, E. 2019. Online Learning of Dynamical Systems: An Operator Theoretic Approach, submitted to the 2020 Proceedings of the IEEE American Control Conference. [preprint]
- Nandanoori S., Sinha, S., and Yeung E. 2019. Data-Driven Operator Theoretic Methods for Global Phase Space Learning, submitted to the 2020 Proceedings of the IEEE American Control Conference. [preprint]
- Balakrishnan, S., Hasnain, A., Boddupalli, N., Joshy, D., and Yeung E. 2019. Prediction of the Growth Rate Population Dynamics of Bacteria by Causal Jump Dynamic Mode Decomposition, submitted to the 2020 Proceedings of the IEEE American Control Conference [preprint].
- Khan, N., Yeung E., Farris, Y., Fansler, S., Bernstein, H. 2019. A broad-host event detector: expanding and quantifying performance across bacterial species. to appear in Synthetic Biology [preprint]
- Stinis, P., Hagge, T., Tartakovsky, A.M. and Yeung, E., 2019. Enforcing constraints for interpolation and extrapolation in generative adversarial networks. Journal of Computational Physics, 397, p.108844.
- Tschirhart, T., Shukla, V., Kelly, E.E., Schultzhaus, Z., NewRingeisen, E., Erickson, J.S., Wang, Z., garcia, W., Curl, E., Egbert, R.G. and Yeung, E., 2019. Synthetic Biology Tools for the Fast-Growing Marine Bacterium Vibrio natriegens. ACS synthetic biology.
- Boddupalli, N., Hasnain, A. and Yeung, E., 2019. Persistence of Excitation for Koopman Operator Represented Dynamical Systems. to appear in the Proceedings of the 2019 IEEE Conference on Decision and Control.
- Hasnain, A., Boddupalli, N. and Yeung, E., 2019. Optimal reporter placement in sparsely measured genetic networks using the Koopman operator. to appear in the Proceedings of the 2019 IEEE Conference on Decision and Control
- Hasnain A., Sinha S., Dorfan Y., Borujeni A. E., Park Y., Maschhoff P., Saxena U., Urrutia J., Gaffney N., Becker D., Maheshri N., Gordon B., Voigt C., and Yeung E.. A Data-Driven Method for Quantifying the Impact of a Genetic Circuit on its Host. to appear in the Proceedings of the 2019 IEEE Conference on Biomedical Circuits and Systems Conference
- Sinha S., Vaidya U., and Yeung E.. On Computation of the Koopman Operator from Sparse Data. Proceedings of the 2019 IEEE American Control Conference
- Yeung E., Kundu S., and Hodas N.. Using Deep Neural Networks to Learn Koopman Operators for Nonlinear Dynamical Systems Proceedings of the 2019 IEEE American Control Conference
2018
- Johnson, C. and Yeung E. A Class of Logistic Functions for Approximating State-Inclusive Koopman Operators. Proceedings of the 2018 IEEE American Control Conference
- Liu Z., Kundu S., Chen L. and Yeung E. Decomposition of Nonlinear Dynamical Systems Using Koopman Gramians. Proceedings of the 2018 IEEE American Control Conference
- Yeung E., Liu Z, and Hodas, N. A Koopman Operator Approach for Computing and Balancing Gramians For Discrete-Time Nonlinear Systems. Proceedings of the 2018 IEEE American Control Conference
- You P., Pang J.Z. and Yeung E. Stabilization of Power Networks via Market Dynamics. Proceedings of the Ninth International Conference on Future Energy Systems
- Maruf A., Kundu S., Yeung E., and Anghel M. Decomposition of Nonlinear Dynamical Networks via Comparison Systems. Proceedings of the 2018 European Control Conference, pp. 190-196.
- You, P., Pang, J. and Yeung, E., 2018. Deep Koopman Controller Synthesis for Cyber-Resilient Market-Based Frequency Regulation. IFAC-PapersOnLine, 51(28), pp.720-725.
