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ResearchPublished PapersFairness in Agreement With European Values: An Interdisciplinary Perspective on AI RegulationAlejandra Bringas Colmenarejo, Luca Nannini, Alisa Rieger, Kristen Marie Scott, Xuan Zhao, Gourab K. Patro, Gjergji Kasneci, Katharina Kinder-Kurlanda. The Fifth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-2022), Oxford, UK. [Slides] Fair ranking: a critical review, challenges, and future directions Gourab K. Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, Nikhil Garg. The Fifth ACM Conference on Fairness, Accountability, and Transparency (FAccT-2022), Seoul, South Korea. [Slides] 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] |