Yuning Jiang

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About

Yuning Jiang is a leading researcher in distributed optimization and control, with a focus on non-convex systems and real-world robotics applications. His most impactful contribution is the development of ALADIN (Augmented Lagrangian Alternating Direction Inexact Newton), a powerful algorithm for distributed non-convex optimization. Jiang spearheaded the creation of ALADIN‑α, an open‑source MATLAB toolbox that makes this advanced method accessible to practitioners and researchers. The associated paper has already garnered 18 citations, underscoring its importance as a practical tool for solving complex, decentralized optimization problems. Beyond algorithmic work, Jiang explores the intersection of optimal control and experiment design, as demonstrated in his 2020 paper on simultaneous optimal tracking control and experiment design. This work, motivated by a robot arm assisting with cooking tasks, highlights his commitment to bridging theory with tangible, human‑centric applications. By providing robust, user‑friendly software and tackling real‑world control challenges, Yuning Jiang is helping to democratize distributed optimization and advance the frontier of autonomous systems.