Sujit Gujar

1.1k total citations
48 papers, 440 citations indexed

About

Sujit Gujar is a scholar working on Management Science and Operations Research, Information Systems and Artificial Intelligence. According to data from OpenAlex, Sujit Gujar has authored 48 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Management Science and Operations Research, 14 papers in Information Systems and 13 papers in Artificial Intelligence. Recurrent topics in Sujit Gujar's work include Auction Theory and Applications (24 papers), Mobile Crowdsensing and Crowdsourcing (10 papers) and Blockchain Technology Applications and Security (9 papers). Sujit Gujar is often cited by papers focused on Auction Theory and Applications (24 papers), Mobile Crowdsensing and Crowdsourcing (10 papers) and Blockchain Technology Applications and Security (9 papers). Sujit Gujar collaborates with scholars based in India, Switzerland and Hong Kong. Sujit Gujar's co-authors include Y. Narahari, Boi Faltings, Dimitris Chatzopoulos, Pan Hui, Pan Hui, Reza Hadi Mogavi, Chao Deng, Ahmed Tlili, Simone Bassanelli and Pengyuan Zhou and has published in prestigious journals such as Artificial Intelligence, IEEE Transactions on Dependable and Secure Computing and Proceedings of the ACM on Human-Computer Interaction.

In The Last Decade

Sujit Gujar

47 papers receiving 428 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sujit Gujar India 9 157 144 107 101 92 48 440
Alessandro Checco United Kingdom 14 191 1.2× 193 1.3× 73 0.7× 89 0.9× 128 1.4× 42 583
Andrea Vázquez‐Ingelmo Spain 13 114 0.7× 151 1.0× 18 0.2× 147 1.5× 50 0.5× 56 528
David Bañeres Spain 15 239 1.5× 416 2.9× 12 0.1× 141 1.4× 35 0.4× 50 797
Mirko Marras Italy 12 259 1.6× 102 0.7× 59 0.6× 243 2.4× 31 0.3× 54 509
Natalia Criado United Kingdom 11 351 2.2× 43 0.3× 41 0.4× 110 1.1× 57 0.6× 48 598
Valentin Kuleto Serbia 7 120 0.8× 159 1.1× 12 0.1× 153 1.5× 27 0.3× 19 497
M. Elena Rodríguez Spain 11 214 1.4× 365 2.5× 13 0.1× 138 1.4× 42 0.5× 41 670
Silvia Milano United Kingdom 8 185 1.2× 36 0.3× 26 0.2× 130 1.3× 17 0.2× 14 426
Fred Freitas Brazil 11 628 4.0× 156 1.1× 32 0.3× 209 2.1× 48 0.5× 69 924
Dan Păun Romania 6 126 0.8× 146 1.0× 14 0.1× 100 1.0× 13 0.1× 13 463

Countries citing papers authored by Sujit Gujar

Since Specialization
Citations

This map shows the geographic impact of Sujit Gujar'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 Sujit Gujar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujit Gujar more than expected).

Fields of papers citing papers by Sujit Gujar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sujit Gujar. 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 Sujit Gujar. The network helps show where Sujit Gujar may publish in the future.

Co-authorship network of co-authors of Sujit Gujar

This figure shows the co-authorship network connecting the top 25 collaborators of Sujit Gujar. A scholar is included among the top collaborators of Sujit Gujar 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 Sujit Gujar. Sujit Gujar 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.
Gujar, Sujit, et al.. (2024). Towards Rational Consensus in Honest Majority. 1439–1441. 1 indexed citations
2.
Gujar, Sujit, et al.. (2023). Combinatorial Civic Crowdfunding with Budgeted Agents: Welfare Optimality at Equilibrium and Optimal Deviation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(5). 5582–5590. 1 indexed citations
3.
Jain, Shweta, et al.. (2023). A Novel Demand Response Model and Method for Peak Reduction in Smart Grids -- PowerTAC. 3497–3504. 1 indexed citations
4.
Faltings, Boi, et al.. (2021). Blockchain-based Practical Multi-agent Secure Comparison and its Application in Auctions. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 430–437. 1 indexed citations
5.
Balasubramanian, Vineeth N, et al.. (2020). Human-Machine Collaboration for Face Recognition. 10–18. 3 indexed citations
6.
Faltings, Boi, et al.. (2019). A Truthful, Privacy-Preserving, Approximately Efficient Combinatorial Auction For Single-minded Bidders. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1916–1918. 1 indexed citations
7.
Gujar, Sujit, et al.. (2019). Aggregating Citizen Preferences for Public Projects Through Civic Crowdfunding. Adaptive Agents and Multi-Agents Systems. 1919–1921. 3 indexed citations
8.
Bhat, Sanjay P., et al.. (2019). VidyutVanika: A Reinforcement Learning Based Broker Agent for a Power Trading Competition. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 914–921. 9 indexed citations
9.
Gujar, Sujit, et al.. (2018). A Neural Network Framework for Fair Classifier. arXiv (Cornell University). 4 indexed citations
10.
Gujar, Sujit, et al.. (2018). Design of Coalition Resistant Credit Score Functions for Online Discussion Forums. ePrints@IISc (Indian Institute of Science). 95–103. 2 indexed citations
11.
Chatzopoulos, Dimitris, Sujit Gujar, Boi Faltings, & Pan Hui. (2018). Privacy Preserving and Cost Optimal Mobile Crowdsensing Using Smart Contracts on Blockchain. arXiv (Cornell University). 442–450. 50 indexed citations
12.
Gujar, Sujit, et al.. (2017). Referral-Embedded Provision Point Mechanisms for Crowdfunding of Public Projects. Adaptive Agents and Multi-Agents Systems. 642–650. 1 indexed citations
13.
Jain, Shweta, et al.. (2017). Thompson Sampling Based Mechanisms for Stochastic Multi-Armed Bandit Problems. Adaptive Agents and Multi-Agents Systems. 87–95. 3 indexed citations
14.
Jain, Shweta, et al.. (2017). A quality assuring, cost optimal multi-armed bandit mechanism for expertsourcing. Artificial Intelligence. 254. 44–63. 10 indexed citations
15.
Jain, Shweta, et al.. (2016). A Deterministic MAB Mechanism for Crowdsourcing with Logarithmic Regret and Immediate Payments. Adaptive Agents and Multi-Agents Systems. 86–94. 7 indexed citations
16.
Jain, Shweta, et al.. (2015). An Optimal Bidimensional Multi-Armed Bandit Auction for Multi-unit Procurement. Adaptive Agents and Multi-Agents Systems. 1789–1790. 5 indexed citations
17.
Gujar, Sujit, et al.. (2014). A mechanism to optimally balance cost and quality of labeling tasks outsourced to strategic agents. Adaptive Agents and Multi-Agents Systems. 917–924. 2 indexed citations
18.
Jain, Shweta, Sujit Gujar, Onno Zoeter, & Y. Narahari. (2014). A quality assuring multi-armed bandit crowdsourcing mechanism with incentive compatible learning. Adaptive Agents and Multi-Agents Systems. 1609–1610. 6 indexed citations
19.
Gujar, Sujit & Y. Narahari. (2014). Redistribution Mechanisms for Assignment of Heterogeneous Objects. NOT FOUND REPOSITORY (Indian Institute of Science Bangalore). 2 indexed citations
20.
Zou, James, Sujit Gujar, & David C. Parkes. (2010). Tolerable Manipulability in Dynamic Assignment without Money. Proceedings of the AAAI Conference on Artificial Intelligence. 24(1). 947–952. 5 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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