Bhaskar Mitra

3.7k total citations · 1 hit paper
50 papers, 1.2k citations indexed

About

Bhaskar Mitra is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Bhaskar Mitra has authored 50 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 21 papers in Information Systems and 8 papers in Management Science and Operations Research. Recurrent topics in Bhaskar Mitra's work include Topic Modeling (30 papers), Information Retrieval and Search Behavior (13 papers) and Natural Language Processing Techniques (13 papers). Bhaskar Mitra is often cited by papers focused on Topic Modeling (30 papers), Information Retrieval and Search Behavior (13 papers) and Natural Language Processing Techniques (13 papers). Bhaskar Mitra collaborates with scholars based in United States, United Kingdom and Canada. Bhaskar Mitra's co-authors include Nick Craswell, Fernando Díaz, Filip Radlinski, Milad Shokouhi, Eric Nalisnick, Rich Caruana, Hamed Zamani, Daniel Campos, Emine Yılmaz and Paul Thomas and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems and Information Retrieval.

In The Last Decade

Bhaskar Mitra

44 papers receiving 1.2k citations

Hit Papers

Large Language Models can Accurately Predict Searcher Pre... 2024 2026 2025 2024 10 20 30 40
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Large Language Models can Accurately Predict Searcher Preferences
    2024 41 citations Paul Thomas, Seth Spielman et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bhaskar Mitra United States 18 960 623 234 143 77 50 1.2k
Enrique Amigó Spain 16 840 0.9× 388 0.6× 156 0.7× 104 0.7× 112 1.5× 51 1.1k
Olga Vechtomova Canada 14 706 0.7× 661 1.1× 208 0.9× 99 0.7× 141 1.8× 48 1.1k
Weizhi Ma China 20 1.1k 1.2× 1.1k 1.8× 238 1.0× 251 1.8× 53 0.7× 76 1.6k
Clare R. Voss United States 18 1.2k 1.3× 311 0.5× 145 0.6× 125 0.9× 85 1.1× 76 1.4k
Ben He China 23 1.2k 1.2× 910 1.5× 250 1.1× 132 0.9× 164 2.1× 77 1.5k
Bo-June Hsu United States 13 715 0.7× 338 0.5× 116 0.5× 112 0.8× 88 1.1× 23 1.1k
Corinna Breitinger Germany 12 509 0.5× 526 0.8× 123 0.5× 79 0.6× 36 0.5× 26 884
Nicola Ferro Italy 17 631 0.7× 533 0.9× 157 0.7× 147 1.0× 100 1.3× 166 1.0k
Debasis Ganguly Ireland 14 564 0.6× 358 0.6× 131 0.6× 43 0.3× 58 0.8× 100 806
Giuseppe Rizzo Italy 18 778 0.8× 374 0.6× 113 0.5× 157 1.1× 41 0.5× 64 1.0k

Countries citing papers authored by Bhaskar Mitra

Since Specialization
Citations

This map shows the geographic impact of Bhaskar Mitra's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bhaskar Mitra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bhaskar Mitra more than expected).

Fields of papers citing papers by Bhaskar Mitra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bhaskar Mitra. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bhaskar Mitra. The network helps show where Bhaskar Mitra may publish in the future.

Co-authorship network of co-authors of Bhaskar Mitra

This figure shows the co-authorship network connecting the top 25 collaborators of Bhaskar Mitra. A scholar is included among the top collaborators of Bhaskar Mitra based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bhaskar Mitra. Bhaskar Mitra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rahmani, Hossein A., Clemencia Siro, Mohammad Aliannejadi, et al.. (2025). LLM4Eval@WSDM 2025: Large Language Model for Evaluation in Information Retrieval. UvA-DARE (University of Amsterdam). 1120–1121.
2.
Fröbe, Maik, Joel Mackenzie, Bhaskar Mitra, Franco Maria Nardini, & Martin Potthast. (2024). ReNeuIR at SIGIR 2024: The Third Workshop on Reaching Efficiency in Neural Information Retrieval. ISTI Open Portal. 3051–3054. 1 indexed citations
3.
4.
Mitra, Bhaskar, et al.. (2024). Towards Group-aware Search Success. 123–131. 1 indexed citations
5.
Thomas, Paul, Seth Spielman, Nick Craswell, & Bhaskar Mitra. (2024). Large Language Models can Accurately Predict Searcher Preferences. 1930–1940. 41 indexed citations breakdown →
6.
Rahmani, Hossein A., Clemencia Siro, Mohammad Aliannejadi, et al.. (2024). LLM4Eval: Large Language Model for Evaluation in IR. UvA-DARE (University of Amsterdam). 3040–3043. 11 indexed citations
7.
Yuan, Ye, et al.. (2024). Learning to Extract Structured Entities Using Language Models. 6817–6834.
8.
Rahmani, Hossein A., et al.. (2024). Synthetic Test Collections for Retrieval Evaluation. 2647–2651. 10 indexed citations
9.
Shah, Chirag, et al.. (2023). Taking Search to Task. 1–13. 11 indexed citations
10.
Mitra, Bhaskar, et al.. (2023). Patterns of Gender-Specializing Query Reformulation. 2241–2245. 2 indexed citations
11.
Mitra, Bhaskar, et al.. (2022). Joint Multisided Exposure Fairness for Recommendation. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 703–714. 25 indexed citations
12.
Lin, Jimmy, Daniel Campos, Nick Craswell, Bhaskar Mitra, & Emine Yılmaz. (2022). Fostering Coopetition While Plugging Leaks. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2939–2948. 3 indexed citations
13.
Craswell, Nick, Bhaskar Mitra, Emine Yılmaz, et al.. (2021). TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime. 2369–2375. 29 indexed citations
14.
Mitra, Bhaskar & Nick Craswell. (2019). An Introduction to Neural Information Retrieval. CERN Document Server (European Organization for Nuclear Research). 71 indexed citations
15.
Zamani, Hamed, Bhaskar Mitra, Song Xia, Nick Craswell, & Saurabh Tiwary. (2018). Neural Ranking Models with Multiple Document Fields. 700–708. 41 indexed citations
16.
Nanni, Federico, et al.. (2017). Benchmark for Complex Answer Retrieval. MADOC (University of Mannheim). 293–296. 11 indexed citations
17.
Mitra, Bhaskar, Fernando Díaz, & Nick Craswell. (2017). Learning to Match using Local and Distributed Representations of Text for Web Search. 1291–1299. 224 indexed citations
18.
Mitra, Bhaskar, et al.. (2016). A Proposal for Evaluating Answer Distillation from Web Data. 2 indexed citations
19.
Díaz, Fernando, Bhaskar Mitra, & Nick Craswell. (2016). Query Expansion with Locally-Trained Word Embeddings. 367–377. 119 indexed citations
20.
Mitra, Bhaskar, et al.. (2014). An Eye-tracking Study of User Interactions with Query Auto Completion. 549–558. 44 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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