December 14-17, 2025
Sydney, Australia
https://focs.computer.org/2025/call-for-workshops/

Submission deadline: September 5, 2025

The FOCS 2025 workshops provide an informal forum for researchers to discuss important research questions, directions, and challenges in the field. Workshops often serve the vital purpose of introducing researchers to new areas and agendas. We also encourage workshops focusing on connections between theoretical computer science and other areas.

We invite groups of interested researchers to submit workshop proposals by September 5.

August 13-15, 2025
Toyota Technological Institute at Chicago
https://sites.google.com/ttic.edu/incentivesdatasharing/home

Submission deadline: July 31, 2025
Registration deadline: July 31, 2025

Machine Learning (ML) has achieved remarkable milestones in recent years, but its future hinges on a robust, ethically grounded, and well-incentivized data infrastructure. The next era of AI innovation requires specialized data that is scarce, proprietary, or sensitive (e.g., medical records, autonomous vehicle data, pharmaceutical test results). Collecting such data is cost and labor-intensive and subject to strict privacy and legal constraints. Simultaneously, the era of “free” or lightly regulated data (e.g., scraped from the public internet) is drawing to a close as copyright and user consent concerns rise — evidenced by legal challenges to large generative models and platform restrictions on web scraping. Taken together, these developments underscore the need for a new AI paradigm — one in which data rights are respected, data owners receive fair compensation, and valuable datasets are shared and reused to unlock novel applications. This raises the central question we want to address in our workshop: “How can we design incentive mechanisms to promote data sharing while safeguarding privacy, fairness, and intellectual property?”

August 11-13, 2025
Oxford, UK
https://feasible-math.org/events/PC25/

Proof complexity is a vibrant area in the intersection of computational complexity, algorithms and mathematical logic exploring the inherent difficulty of proving statements in different formal proof systems. This workshop aims to cover both traditional topics and emerging trends in the field, including lower bounds on lengths of proofs, bounded arithmetic, model theory, SAT-solving, connections to algebraic complexity and TFNP, lifting theorems and meta-mathematics of complexity theory. To register for the workshop, please use the following Registration Form: https://form.jotform.com/251323981206352

August 18-20, 2025
Toyotal Technological Institute-Chicago
https://people.csail.mit.edu/joanne/WOLA25

Registration deadline: August 10, 2025

Local algorithms, that is, algorithms that compute and make decisions on parts of the output considering only a portion of the input, have been studied in a number of areas in theoretical computer science and mathematics. Some of these areas include sublinear-time algorithms, distributed algorithms, inference in large networks and graphical models. These communities have similar goals but a variety of approaches, techniques, and methods. This workshop is aimed at fostering dialogue and cross-pollination of ideas between the various communities. To this end, the workshop will feature a small number of longer talks that, in part, survey approaches by various communities, as well as short, focused talks on recent, exciting results.

July 10, 2025
Colocated with ACM EC 25, Stanford University, Stanford, CA
https://sites.google.com/view/ole-2025/home-page

Submission deadline: June 6, 2025

The workshop focuses on the intersection of online learning and economics, exploring how learning algorithms are increasingly used for decision-making in strategic economic settings such as markets and platforms. The event brings together researchers from diverse fields to discuss current challenges, share recent advances, and foster collaboration. The scope of the workshop extends beyond online learning to encompass other relevant domains of machine learning, including, for example, learning theory and reinforcement learning.

Call for posters: More info on the workshop website

June 30, 2025
Lyon, France at COLT 2025
https://vaidehi8913.github.io/predictions-and-uncertainty-colt25/

Submission deadline: May 25, 2025

Predictions from machine learning systems are increasingly being used as inputs to downstream algorithms and decision-making tasks. However, these predictions can be unreliable, and often suffer from biases or overconfidence, highlighting the need for rigorous approaches to modeling their uncertainty. The goal of the workshop is to bring together researchers from across different communities to learn about exciting developments and explore connections between these emerging lines of research. Topics of interest include Conformal Prediction, Algorithms with Predictions, Robust Statistics, Risk-Averse Decision Making, and other approaches for estimating and propagating uncertainty in statistical and algorithmic applications. The workshop includes a poster session, and we invite submissions from a broad range of areas related to uncertainty quantification and using unreliable predictions.