FSE 2026
Sun 5 - Thu 9 July 2026 Montreal, Canada
FSE 2026 (series) /

Broadening Participation Panel/Round TableFSE 2026

Broadening Participation Panel/Round Table: Diversity in the AI Era

The rapid adoption of AI technologies has created new opportunities while also raising important questions about representation, participation, and fairness. This panel brings together researchers and practitioners to discuss the role of diversity in the development of AI technologies and the behavior of AI systems. Topics include bias and stereotyping in Large Language Models, the contribution of diverse perspectives to AI development, challenges in creating AI technologies that serve different populations, and opportunities to broaden participation in the AI ecosystem.

Panelists

  • Dr. Mariam Barry is a Senior Scientist at BNP Paribas and affiliated Researcher at Ecole Polytechnique in France. Her work focuses on machine learning, large scale data systems, continual learning, and AI applications in industry, with particular expertise in financial technologies and operational AI systems.

  • Dr. Cleyton Magalhães is an Associate Professor at the Federal Rural University of Pernambuco, Brazil. His research focuses on Software Testing, Human Aspects of Software Engineering, and Software Fairness. He combines extensive academic experience with more than six years of industry experience in software quality assurance, bringing perspectives from both research and practice to software engineering.

  • Dr. Zhou Yang is an Assistant Professor at the University of Alberta and an Amii Fellow. His research focuses on Trustworthy AI, Automated Software Engineering, Human-AI Interaction, and Software Engineering for AI. His work has received several international distinctions, including the IEEE Computer Society Best Paper Award and ACM Distinguished Paper Award.

  • Dr. Alicia Takaoka is a Postdoctoral Researcher at Erasmus University Rotterdam. Her research focuses on AI, inclusion, human-computer interaction, and participatory design, with particular attention to diversity, marginalized communities, and the responsible development of AI systems

  • Dr. Lili Wei is an Assistant Professor at McGill University whose research investigates software testing, software quality, and AI-assisted software engineering. She is an active member of the international software engineering community and currently serves as Proceedings Co-Chair for FSE 2026 and General Chair of PROMISE 2026.

Plenary
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Wed 8 Jul

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15:30 - 16:00
Coffee BreakCatering

The poster presentations will be held in this coffee break area near the MB Atrium on the first floor. Authors are expected to stand near their posters during the scheduled coffee breaks to present their work and answer questions.

Authors should print their own posters and bring them to the conference venue. Posters should be mounted on the designated poster boards before 8 July.

Each poster board is double-sided and measures 4 × 6 ft. Each side can hold two portrait-oriented posters, with a recommended poster size of 24 × 36 inches. Each board can therefore accommodate four posters in total.

Authors who need local printing may use the Concordia Print Store: https://www.concordia.ca/print/store.html. Other printing shops are also available near the venue.

15:30
30m
Coffee break
Break
Catering

16:00 - 17:00
Broadening Participation panel/round tableBroadening Participation Panel/Round Table at MB 2.430
Chair(s): Mariam Barry BNP Paribas, Ronnie de Souza Santos University of Calgary, Cleyton Magalhaes Universidade Federal Rural de Pernambuco, Alicia JW Takaoka Erasmus University Rotterdam, Zhou Yang University of Alberta; CIFAR AI Chair; Alberta Machine Intelligence Institute

The rapid adoption of AI technologies has created new opportunities while also raising important questions about representation, participation, and fairness. This panel brings together researchers and practitioners to discuss the role of diversity in the development of AI technologies and the behavior of AI systems. Topics include bias and stereotyping in Large Language Models, the contribution of diverse perspectives to AI development, challenges in creating AI technologies that serve different populations, and opportunities to broaden participation in the AI ecosystem.

Broadening Participation Panel