Dynamical systems have played an important role in the analysis and design of algorithms. Ideas ranging from variational methods, differential and symplectic geometry, numerical analysis, and control theory have paved the way for establishing non-asymptotic convergence guarantees in optimization, sampling, and equilibrium computation in games. Yet, the distinct mathematical backbone of these tools often creates barriers to entry for researchers and practitioners in machine learning. 

This workshop aims to lower that barrier by highlighting the unifying role of dynamical systems across these domains. We will convene optimization, sampling, and game theory experts to foster cross-disciplinary dialogue and collaboration. Emphasis will be placed on emerging applications in machine learning, such as diffusion models, distributed and adversarial training, and agentic AI, where dynamical systems perspectives are increasingly central. Through a combination of talks, posters, and open discussions, we hope to catalyze new collaborations and broaden the accessibility of these foundational methods. 

This is the second edition of the DynaFront workshop; the first one was held during NeurIPS 2025 in San Diego, CA.

This workshop is held during NeurIPS 2026 in Atlanta, GA. 

Speakers:

• Prof. Qiang Liu, University of Texas at Austin

• Prof. Santosh Vempala, Georgia Institute of Technology

• Prof. Lenka Zdeborova, EPFL

• Prof. Tong Zhang, University of Illinois

• Prof. Xunyu Zhou, Columbia University

Important Dates:

• Submission Deadline: August 29 September 4, 2026 (AoE)

• Acceptance Notification: September 29, 2026 (AoE)

• Camera Ready: Nov 30, 2026 (AoE)

• Workshop: December 12, 2026  

• Location: Atlanta, GA

Important Links:

• Submission portal: https://openreview.net/group?id=NeurIPS.cc/2026/Workshop/DynaFront

• Reviewer application form: https://forms.gle/vVn5cptJB6ggT37n6