collaborators

8 papers

cs.LG2026

Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication

Yuyang Du, Yujun Huang, Gioele Zardini

Designing a neural network processor is an end-to-end co-design problem: network architecture and training budget determine the inference workload; hardware mapping decisions deter…

cs.RO2026

Task-Driven Co-Design of Heterogeneous Multi-Robot Systems

Maximilian Stralz, Meshal Alharbi, Yujun Huang +1

Designing multi-agent robotic systems requires reasoning across tightly coupled decisions spanning heterogeneous domains, including robot design, fleet composition, and planning. M…

eess.SY2026

Quantale-Enriched Co-Design: Toward a Framework for Quantitative Heterogeneous System Design

Hans Riess, Yujun Huang, Matthew Klawonn +2

Monotone co-design enables compositional engineering design by modeling components through feasibility relations between required resources and provided functionalities. However, i…

math.OC2026

Scalable Co-Design via Linear Design Problems: Compositional Theory and Algorithms

Yubo Cai, Yujun Huang, Meshal Alharbi +1

Designing complex engineered systems requires managing tightly coupled trade-offs between subsystem capabilities and resource requirements. Monotone co-design provides a compositio…

math.OC2026

Distributional Uncertainty and Adaptive Decision-Making in System Co-design

Yujun Huang, Gioele Zardini

Complex engineered systems require coordinated design choices across heterogeneous components under conflicting objectives and uncertain specifications. Monotone co-design provides…

math.CT2026

Composable Uncertainty in Symmetric Monoidal Categories for Design Problems

Marius Furter, Yujun Huang, Gioele Zardini

Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, l…