Bounding convex relaxations of process models from below by tractable black-box sampling. - Yingkai Song; Huiyi Cao; Chiral Mehta; Kamil A. Khan (Comput. Chem. Eng., 2021)

Optimization-based convex relaxations for nonconvex parametric systems of ordinary differential equations. - Yingkai Song; Kamil A. Khan (Math. Program., 2022)

Generalized derivatives of optimal-value functions with parameterized convex programs embedded. - Yingkai Song; Paul I. Barton (J. Glob. Optim., 2024)

Computing subgradients of convex relaxations for solutions of parametric ordinary differential equations. - Yingkai Song; Kamil A. Khan (Optim. Methods Softw., 2024)

New Generalized Derivatives for Solving Variational Inequalities Using the Nonsmooth Newton Methods. - Yingkai Song; Paul I. Barton (J. Optim. Theory Appl., 2024)

New inequalities for comparing ordinary differential equations arising in global dynamic optimization. - Yingkai Song; Kamil A. Khan (Syst. Control. Lett., 2025)

Computing AD-compatible subgradients of convex relaxations of implicit functions. - Yingkai Song; Kamil A. Khan (CoRR, 2025)