✨Our work is featured on the Massachusetts Institute of Technology News homepage spotlight today! 🔗 https://lnkd.in/dgd6nBi4 At its core, this research tackles a simple but powerful idea: engineering design must embrace uncertainty, not ignore it. Traditional methods rely on best- and worst-case bounds — but in the real world, systems like autonomous vehicles, UAVs, and future mobility networks face probabilistic risks, trade-offs, and interdependent uncertainties. In our recent paper, "On Composable and Parametric Uncertainty in Systems Co-Design", we extend our monotone co-design framework to reason about uncertainty in a unified and modular way: 📊 Moving beyond intervals to capture distributions and risk trade-offs 🧩 Preserving compositionality, so subsystems (e.g., sensors, actuators, batteries, algorithms) can be combined seamlessly. We do this via applied category theory! 💥 🚁 Demonstrating through a case study on UAV design how uncertainty-aware methods can reveal insights invisible to deterministic models (e.g., when a design is infeasible with 12.8% probability vs. being simply “worst-case infeasible”) This is part of a broader vision: developing tools that allow engineers to design complex systems with rigor, transparency, and adaptability — even under uncertainty. Great work with my students Yujun Huang and Marius Furter, and the support of MIT Civil and Environmental Engineering, MIT Laboratory for Information and Decision Systems (LIDS), and MIT Institute for Data, Systems, and Society (IDSS) #MIT #Research #SystemsDesign #Uncertainty #Autonomy #CoDesign #Engineering
Solid framework!
E. W. Schuster Macro…•29K followers
6moThanks for posting!