ACM EAAMO'23 Call for Participation now open: deadline 10 May, 2023

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Sandro Radovanović

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Apr 11, 2023, 12:47:56 PM4/11/23
to Machine Learning and Statistics

Dear all, 


We are excited to announce the Call for Participation for the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '23). The conference will be held from October 30 to November 1, 2023 at Boston University in Boston, MA, USA.


EAAMO '23 will bring together academics and practitioners from diverse disciplines and sectors. The conference will highlight work along the research-to-practice pipeline aimed at improving access to opportunity for historically underserved and disadvantaged communities, as well as mitigating 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 grounding in the social sciences and humanistic studies.


We welcome archival and non-archival contributions to the research track as well as the policy and practice track. Submissions can include research, survey, and position papers as well as problem- and practice-driven submissions by academics and practitioners from any disciplines or sectors alike. 


Important Dates:


Paper Submission Deadline: 10 May 2023, AoE

Submission Notification: 18 July 2023

Paper Submission Page: EasyChair

Event Dates: 30 October - 1 November 2023


The conference will offer opportunities to engage with leading experts, share innovative research and practices, and network with peers. We look forward to your participation in this exciting event.


For any further inquiries about the conference, please contact the Program Chairs at pc...@eaamo.org or the Executive Committee at e...@eaamo.org


Sincerely,

EAAMO '23 Organizers 


Program Chairs: 

Vahideh Manshadi, Yale University
Celestine Mendler-Dünner, Max Planck Institute for Intelligent Systems
Elissa Redmiles, Max Planck Institute for Intelligent Systems
Maria Rodriguez, University at Buffalo
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