Faculty Profiles

Tsai, Y.-K., Karkaria, V., Chen, Y.-P., & Chen, W. (2026). Digital twin-enabled multi-generation control co-design with deep reinforcement learning. Journal of Mechanical Design, 148(7), 071705.

Tsai, Y.-K., & Malak, R. J. (2026). Parametric multi-objective optimization for simultaneous and nested control co-design formulations with tube-based model predictive controllers. Journal of Mechanical Design, 148(11), 111701. https://doi.org/10.1115/1.4071654

Tsai, Y.-K., Chen, Y.-P., Karkaria, V., & Chen, W. (2026). Reinforcement Learning-Based Control Co-Design of Digital Twin-Enabled Full-Vehicle Active Suspension Systems. Structural and Multidisciplinary Optimization, 69(4), 108.

Tsai, Y.-K., & Malak, R. J. (2025). Control co-design with performance-robustness trade-off using tube-based stochastic model predictive control. ASME Letters in Dynamic Systems and Control, 5(3), 030903. https://doi.org/10.1115/1.4067768

Chen, Y.-P., Karkaria, V., Tsai, Y.-K., Rolark, F., Quispe, D., Gao, R. X., … Chen, W. (2025). Real-time decision-making for Digital Twin in additive manufacturing with Model Predictive Control using time-series deep neural networks. Journal of Manufacturing Systems, 80, 412–424. https://doi.org/10.1016/j.jmsy.2025.03.009

Karkaria, V., Tsai, Y.-K., Chen, Y.-P., & Chen, W. (2025). An optimization-centric review on integrating artificial intelligence and digital twin technologies in manufacturing. Engineering Optimization, 57(1), 161–207. https://doi.org/10.1080/0305215x.2024.2434201

Tsai, Y.-K., & Malak, R. J. (2024). Surrogate-assisted constraint-handling technique for parametric multi-objective optimization. Structural and Multidisciplinary Optimization, 67(9), 167.

Tsai, Y.-K., & Malak, R. J. (2023). Robust control co-design using tube-based model predictive control. In Proceedings of 2023 American Control Conference (ACC). IEEE. https://doi.org/10.23919/ACC55779.2023.10156303