collaborators

12 papers

math.OC2026

Structure-Preserving Spectral Dynamic Programming on Compact Lie Groups

Shanqing Liu, Yang Qi

We study spectral approximations of the dynamic programming semigroup for finite-horizon optimal control on a connected compact Lie group , and of the associated first-order Ham…

math.OC2026

Singularities in Multi-Objective Optimization and their Crossing during Continuation

Arjun Manoj, Michail E. Kavousanakis, Shanqing Liu +1

Continuation methods help trace Pareto sets in multi-objective optimization but are inherently local: a single run traces a single connected branch, requiring multiple restarts to…

math.OC2026

PI-SONet: A Physics-Informed Symplectic Operator Network for Real-Time Optimal Control of Multi-Agent Systems

Alan John Varghese, Shanqing Liu, Paula Chen +3

Many real-life applications involve controlling high-dimensional multi-agent systems in real-time. Existing optimal control solvers often suffer from the curse-of-dimensionality an…

math.OC2026

Tropical low-rank approximation and application to optimal control of N-body systems

Marianne Akian, Stephane Gaubert, Shanqing Liu +1

We study the approximation of the value function of deterministic optimal control problems with fixed initial state, motivated by \(N\)-body systems. In this setting, the action fu…

math.OC2026

PINNs in PDE Constrained Optimal Control Problems: Direct vs Indirect Methods

Zhen Zhang, Shanqing Liu, Alessandro Alla +2

We study physics-informed neural networks (PINNs) as numerical tools for the optimal control of semilinear partial differential equations. We first recall the classical direct and…

cs.LG2026

Automatic selection of the best neural architecture for time series forecasting

Qianying Cao, Shanqing Liu, Alan John Varghese +3

Time series forecasting plays a pivotal role in a wide range of applications, including weather prediction, healthcare, structural health monitoring, predictive maintenance, energy…