Bhaskar Mitra | ভাস্কর মিত্র

Bhaskar Mitra | ভাস্কর মিত্র

he/him

I am an information retrieval researcher working on AI-mediated online information access and questions of social justice and emancipation in the context of these sociotechnical systems.

Research Theme: Exposure Fairness and Transparency in Information Access

Information access systems mediate what information gets exposure. This raises several concerns of fairness, diversity, transparency, and privacy in the context of information access. This research theme focuses on the study and mitigation of allocative and representational harms from disparate exposure.


Keynotes, invited talks, and lectures

Multisided Exposure Fairness for Search and Recommendation

Lowe's
Virtual, June 2022
SlideShare | PPT



Publications

Towards Understanding Bias in Synthetic Data for Evaluation

Hossein A. Rahmani, Varsha Ramineni, Nick Craswell, Bhaskar Mitra, and Emine Yilmaz
In proc. ACM CIKM, 2025
Publication | PDF | ArXiv

Through the Looking-Glass: Transparency Implications and Challenges in Enterprise AI Knowledge Systems

Karina Cortiñas-Lorenzo, Siân Lindley, Ida Larsen-Ledet, and Bhaskar Mitra
Preprint, 2024
PDF | ArXiv

Result Diversification in Search and Recommendation: A Survey

Haolun Wu, Yansen Zhang, Chen Ma, Fuyuan Lyu, Bowei He, and Bhaskar Mitra
In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024
Publication | PDF | ArXiv

Towards Group-aware Search Success

Haolun Wu, Bhaskar Mitra, and Nick Craswell
In proc. ACM ICTIR, 2024
Publication | PDF | ArXiv

Patterns of gender-specializing query reformulation

Amifa Raj, Bhaskar Mitra, Nick Craswell, and Michael Ekstrand
In proc. ACM SIGIR, 2023
Publication | PDF | ArXiv

De-Biasing Relevance Judgements for Fair Ranking

Amin Bigdeli, Negar Arabzadeh, Shirin Seyedsalehi, Bhaskar Mitra, Morteza Zihayat, and Ebrahim Bagheri
In proc. ECIR, 2023
Publication | PDF

A Multi-objective Optimization Framework for Multi-stakeholder Fairness-aware Recommendation

Haolun Wu, Chen Ma, Bhaskar Mitra, Fernando Diaz, and Xue Liu
In ACM Transactions on Information Systems (TOIS), 2022
Publication | PDF | ArXiv

Inconsistent Ranking Assumptions in Medical Search and Their Downstream Consequences

Daniel Cohen, Kevin Du, Bhaskar Mitra, Laura Mercurio, Navid Rekabsaz, and Carsten Eickhoff
In proc. ACM SIGIR, 2022
Publication | PDF

Joint Multisided Exposure Fairness for Recommendation

Haolun Wu, Bhaskar Mitra, Chen Ma, Fernando Diaz, and Xue Liu
In proc. ACM SIGIR, 2022
Publication | PDF | ArXiv

Bias-aware Fair Neural Ranking for Addressing Stereotypical Gender Biases

Shirin SeyedSalehi, Amin Bigdeli, Negar Arabzadeh, Bhaskar Mitra, Morteza Zihayat, and Ebrahim Bagheri
In proc. Extending Database Technology (EDBT), 2022
Publication | PDF

Exposing Query Identification for Search Transparency

Ruohan Li, Jianxiang Li, Bhaskar Mitra, Fernando Diaz, and Asia J. Biega
In proc. ACM TheWebConf, 2022
Publication | PDF | ArXiv

Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness

Nicola Neophytou, Bhaskar Mitra, and Catherine Stinson
In proc. ECIR, 2022
Publication | PDF | ArXiv

Neural methods for effective, efficient, and exposure-aware information retrieval

Bhaskar Mitra
In ACM SIGIR Forum, 2021
Publication | PDF

Neural Methods for Effective, Efficient, and Exposure-Aware Information Retrieval

Bhaskar Mitra
PhD thesis, University College London, 2021
Publication | PDF | ArXiv

Evaluating Stochastic Rankings with Expected Exposure

Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, and Ben Carterette
In proc. ACM CIKM, 2020
🏆 Best Long Research Paper Nominee
Publication | PDF | ArXiv