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Call for Posters

Table of Contents

The fifth ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (ACM EAAMO ‘25) will take place November 5-7, 2025 in the University of Pittsburgh, Pittsburgh, PA, USA. The event will highlight work along the research-to-practice pipeline to improve access to opportunity for historically underserved and disadvantaged communities and mitigate harms concerning inequitable and unsafe outcomes. In particular, we seek contributions from different fields that offer insights into the intersectional design and impacts of algorithms, optimization, and mechanism design with a grounding in the social sciences and humanistic studies. Submissions include research, surveys, position papers, and problem- and practice-driven submissions by academics and practitioners from different disciplines or sectors.

Call for Posters #

We invite submissions for poster presentations. Accepted submissions will be presented at a poster session during the conference. To submit, authors are only required to provide a title and abstract via the submission form at this link (submission of a full paper is optional but encouraged). The review process will focus largely on fit with the mission of EAAMO and likely interest to the EAAMO community.

Please note that poster presentations do not constitute an accepted paper and remain fully compatible with future submission of the work to peer-reviewed venues.

We especially encourage resubmissions of papers that were not accepted through the call for papers but may still be valuable and engaging as posters for the EAAMO audience.

Application: Submission link
Deadline: July 25, 2025
Author notification: 2025 August 10, 2025

Areas of Interest #

We invite submissions on topics, methodologies, and approaches including, but not limited to:

  • ethical, economic, legal, philosophical, and societal considerations of algorithmically-driven interventions
  • redistributive mechanisms for improving access to opportunity and equitable outcomes
  • micro- and macroeconomic consequences of inequality and market inefficiencies
  • determinants and causes of harm, including inequitable outcomes, market failures, exploitative behavior, and economic inefficiencies
  • machine learning, optimization, and mechanism design for alleviating inefficiencies, inequitable, and unsafe economic and social outcomes
  • uncertainty, safety, privacy, and equity in allocative and representational systems
  • algorithmic, ethical, policy, and societal challenges in computing in resource-constrained settings
  • reliable, trustworthy, and valid inference in societally-consequential domains
  • data collection, curation, governance, protection, and sharing efforts for work related to improving access to opportunity
  • algorithmic approaches and tools to encourage participation, empower, and organize communities for the collective good
  • regulation and policy design related to data, privacy, equity, fairness, and access to opportunity

Application areas of interest include civic participation, data economies, discrimination and bias, digital and economic inequalities, economic development, education, environment and climate, food security, healthcare, housing, infrastructure, labor markets, law and policy, low- and under-resourced computing, social and economic mobility, privacy, public service provision, recommender systems, social work, sustainable development, and transportation. Our broad list of topics illustrates how various perspectives and disciplinary approaches can triangulate progress on focus areas of shared interest.

Chairs: #

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