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Research

Working Papers

Fairness implications of encoding protected categorical attributes
Carlos Mougan, Jose M. Alvarez, Gourab K Patro, Salvatore Ruggieri, Steffen Staab.

On Fair Virtual Conference Scheduling: Achieving Equitable Participant and Speaker Satisfaction
Gourab K Patro, Abhijnan Chakraborty, Niloy Ganguly, Krishna P. Gummadi.

Published Papers

Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation
Alejandra Bringas Colmenarejo, Luca Nannini, Alisa Rieger, Kristen Marie Scott, Xuan Zhao, Gourab K. Patro, Gjergji Kasneci, Katharina Kinder-Kurlanda.
Accepted to appear in the fifth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-2022).

Fair ranking: a critical review, challenges, and future directions
Gourab K. Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, Nikhil Garg.
Accepted to appear in the fifth ACM Conference on Fairness, Accountability, and Transparency (FAccT-2022).

Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction
Gourab K. Patro, Prithwish Jana, Abhijnan Chakraborty, Krishna P. Gummadi, Niloy Ganguly.
The Thirty-first Web Conference (WWW-2022), Oral Presentation, Lyon, France.
[Dataset & Code, Slides]

Towards Fair Recommendation in Two-Sided Platforms
Gourab K Patro*, Arpita Biswas*, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty.
ACM Transactions on the Web (TWEB), Volume 16, Issue 2, May 2022, Article No. 8, Pages 1–34.
[Code]

Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness
Jessie Finocchiaro, Roland Maio, Faidra Monachou, Gourab K Patro, Manish Raghavan, Ana-Andreea Stoica, Stratis Tsirtsis.
The Fourth ACM Conference on Fairness, Accountability, and Transparency (FAccT-2021).
[Slides]

Two-Sided Fairness in Non-Personalised Recommendations
Aadi Swadipto Mondal*, Rakesh Bal*, Sayan Sinha*, Gourab K Patro.
The Thirty-fifth AAAI Conference on Artificial Intelligence (AAAI-2021), Student Poster, Vancouver, Canada.
[Code, Poster]

Analyzing ‘Near Me’ Services: Potential for Exposure Bias in Location-based Retrieval
Ashmi Banerjee, Gourab K Patro, Linus W. Dietz, Abhijnan Chakraborty.
The International Workshop on Fair and Interpretable Learning Algorithms (FILA-2020).

Towards Safety and Sustainability: Designing Local Recommendations for Post-pandemic World
Gourab K Patro, Abhijnan Chakraborty, Ashmi Banerjee, Niloy Ganguly.
The Fourteenth ACM Conference on Recommender Systems (RecSys-2020), Oral Presentation, Virtual Event, Brazil.
Also invited to showcase at IndiaHCI-2021.
[Dataset & Code, Slides, Teaser, Video]

FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms
Gourab K Patro*, Arpita Biswas*, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty.
The Twenty-ninth Web Conference (WWW-2020), Oral Presentation, Taipei, Taiwan.
[Code, Slides, Video]

Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations
Gourab K Patro, Abhijnan Chakraborty, Niloy Ganguly, Krishna P. Gummadi.
The Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI-2020), Oral Presentation, New York, USA.
[Slides]

Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations
Abhijnan Chakraborty, Gourab K Patro, Niloy Ganguly, Krishna P. Gummadi, Patrick Loiseau.
The Second ACM Conference on Fairness, Accountability, and Transparency (FAT*-2019), Atlanta, Georgia, USA.
[Slides]