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Research

(B=Book, J=Journal, C=Conference, W=Working-paper)

[B1] Algorithmic Fairness in Multi-stakeholder Platforms
Gourab K. Patro.
Book Chapter. Ethics in Artificial Intelligence: Bias, Fairness and Beyond. Springer Nature, Singapore.

[W1] A Review of the Role of Causality in Developing Trustworthy AI Systems
Niloy Ganguly, Dren Fazlija, Maryam Badar, Marco Fisichella, Sandipan Sikdar, Johanna Schrader, Jonas Wallat, Koustav Rudra, Manolis Koubarakis, Gourab K. Patro, Wadhah Zai El Amri, Wolfgang Nejdl.
arXiv:2302.06975. 2023.

[C10] 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.
The Fifth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-2022), Oxford, UK.
[Slides]

[C9] 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]

[C8] 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]

[J1] 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]

[C7] 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]

[C6] 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]

[C5] 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. IEEE BigData-2020.

[C4] 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]

[C3] 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]

[C2] 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]

[C1] 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]