Key dates 

Submission deadline 

December 12, 2023 


Author notification

April 2024


Registration opens

April 22, 2024


Final paper upload deadline

May 20, 2024


Early-bird registration closes

May 31, 2024


Registration closes

June 27, 2024



News and updates 

  • The proceedings for L4DC 2024 are now available here
  • Registration for L4DC 2024 is now open! See here for details.
  • The submission portal for upload of final papers is now open! See here for details. 
  • L4DC 2024 is now soliciting sponsorship. You may download a sponsorship flyer here.

Over the next decade, the biggest generator of data is expected to be devices that sense and control the physical world.

The explosion of real-time data that is emerging from the physical world requires a rapprochement of 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 our 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 overall goal is to create a new community of people who think rigorously across the disciplines, ask new questions, and develop the foundations of this new scientific area. We are happy to welcome you to the University of Oxford for the 6th annual L4DC.







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Call for papers

A "call for papers flyer" (pdf) is available here.

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
  • Physics-constrained learning
  • Physical learning in dynamical and control systems applications in robotics, autonomy, biology, energy systems, transportation systems, cognitive systems, neuroscience, etc.

While the conference is open to any topic on the interface between machine learning, control, optimization and related areas, its primary goal is to address scientific and application challenges in real-time physical processes modeled by dynamical or control systems.

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  • Paper submission deadline: 1 December 2023 
  • Author notification: April 2024
  • Final paper upload deadline: May 2024
  • Conference: 15-17 July 2024
  • Papers are to be submitted via EasyChair here using the L4DC template here.
  • All papers must be written in English and be uploaded in pdf format.

  • Submissions are limited to 10 pages with unlimited allowance for references. Acknowledgements do not count towards the page limit.

  • If the submitted paper includes an appendix, it should be within the 10-page limit.

  • Authors may include links to supplementary material (long proofs, additional experiments, etc), but reviews and acceptance decisions will be based only on the submitted paper (10 pages). 

  • L4DC reviewing is single blind.
  • 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.

  • Please contact the conference organizers at l4dc@eng.ox.ac.uk if you have any questions.

Submissions that are substantially similar to papers that have been previously published, accepted for publication, or submitted in parallel to other peer-reviewed conferences with proceedings or journals may not be submitted to L4DC.

Accepted papers will be published electronically in the Proceedings of Machine Learning Research (PMLR).

Code of Conduct

At the L4DC conference, we aim to create a safe, welcoming, and positive environment that facilitates exchanging ideas and forming professional connections. We expect all participants to be respectful towards each other. The conference will not tolerate harassment, discrimination, or personal attacks. Participants must stop any problematic behavior immediately. 

It is important to note that problematic communication can occur even without an explicit intent to offend or harass. Hence, we ask that all participants be mindful of how their comments can be interpreted, and err on the side of caution during formal and informal interactions.

Full Code of Conduct and Terms and Conditions for conference registration available here.

Building the L4DC Community:


L4DC is interdisciplinary, bringing together researchers from control, robotics, machine learning, and optimization. One of the goals of L4DC is to build strong ties between these disciplines and enable active collaboration. Please consider taking on the constructive role of contributing to the community, instead of taking on a critical role to pinpoint flaws and weaknesses in the works of others during the conference. Focusing on weak points could cause others to retreat back to places where they feel comfortable, and instead of interdisciplinary interaction, we could end up with separate sub-clusters of people only interacting within their own fields. So please help us create a positive tone so that it is easy for the participants to leave their comfort zones, gain new perspectives, and form new collaborations.