Dear colleagues,
On behalf of the L4DC 2025 organizing committee, I would like to bring your attention to the call for papers for the 7th Annual Learning for Dynamics and Control Conference (L4DC 2025), scheduled to take place in Ann Arbor, Michigan on June 4-6, 2025. Please find attached a CfP that you can share with your colleagues who might be interested.
We are happy to welcome you to Ann Arbor for the 7th annual L4DC.
Conference: June 5-6, 2025. Tutorials: June 4, 2025.
The explosion of real-time data arising from devices that sense and control the physical world requires improving synergy in research areas such as machine learning, control theory, and optimization. While control theory has been firmly rooted in the tradition of model-based design, the availability and scale of data (both temporal and spatial) will require rethinking the foundations of the discipline. From a machine learning perspective, one of the main challenges going forward is to go beyond pattern recognition and address problems in data-driven control and optimization of dynamical processes. Our conference has been building a new community of people who think rigorously across the disciplines, ask new questions, and develop the foundations of this new scientific area.
We invite submissions of short papers addressing topics including:
• Foundations of learning of dynamics models
• System identification
• Optimization for machine learning
• Data-driven optimization for dynamical systems
• Distributed learning over distributed systems
• Reinforcement learning for physical systems
• Safe reinforcement learning and safe adaptive control
• Statistical learning for dynamical and control systems
• Bridging model-based and learning-based dynamical and control systems
• Machine learning for reduced-order modeling and physics-constrained systems
• Physical learning in dynamical and control systems applications in robotics, autonomy, biology, energy systems, transportation systems, cognitive systems, neuroscience, etc.
The conference is open to any topic on the interface between machine learning, control, and optimization; its primary goal is to address scientific and application challenges in real-time processes modeled by dynamical or control systems.
Paper submissions:
• All accepted papers will be presented as posters at the conference. A selected set of papers deemed particularly exceptional by the program committee will be presented as oral talks.
• Accepted papers will be published electronically in the Proceedings of Machine Learning Research (PMLR).
• Submissions are limited to 10 pages in PMLR format with unlimited allowance for references.
Further information at https://sites.google.com/umich.edu/l4dc2025/ or contact us at l4dc-2025@umich.edu
L4DC 2025 Organizing Committee:
General Chair: Necmiye Ozay, University of Michigan
Program Co-Chairs: Laura Balzano, Dimitra Panagou, University of Michigan
Program Vice-Chair: Alessandro Abate, University of Oxford
Local Arrangements Chair: Vasileios Tzoumas, University of Michigan
Tutorials Chair: Florian Dörfler, ETH Zürich
Publicity Chair: Sze Zheng Yong, Northeastern University
Awards Chair: Na Li, Harvard University
Website Chair: Salar Fattahi, University of Michigan
Steering Committee: Ali Jadbabaei, MIT; John Lygeros; ETH Zürich; George Pappas, UPenn; Pablo Parrilo, MIT; Ben Recht, UC Berkeley; Claire Tomlin, UC Berkeley; Melanie Zeilinger, ETH Zürich
