3 papers
cs.AI2026
From Feasible to Practical: Pareto-Optimal Synthesis Planning
Friedrich Hastedt, Dongda Zhang, Antonio del Rio Chanona
Current computer-aided synthesis planning (CASP) methods often treat retrosynthesis as solved once a single feasible route is identified, focusing primarily on convergence or short…
cs.CE2025
Constraint-Guided Symbolic Regression for Data-Efficient Kinetic Model Discovery
Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, King Kuok +4
The industrialization of catalytic processes hinges on the availability of reliable kinetic models for design, optimization, and control. Traditional mechanistic models demand exte…
eess.SY2025
Reinforcement learning for robust dynamic metabolic control
Sebastián Espinel-Ríos, River Walser, Dongda Zhang
Dynamic metabolic control allows key metabolic fluxes to be modulated in real time, enhancing bioprocess flexibility and expanding available optimization degrees of freedom. This i…