Sumit Mukherjee

25 papers and 220 indexed citations i.

About

Sumit Mukherjee is a scholar working on Statistics and Probability, Mathematical Physics and Artificial Intelligence. According to data from OpenAlex, Sumit Mukherjee has authored 25 papers receiving a total of 220 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistics and Probability, 14 papers in Mathematical Physics and 6 papers in Artificial Intelligence. Recurrent topics in Sumit Mukherjee’s work include Stochastic processes and statistical mechanics (13 papers), Random Matrices and Applications (11 papers) and Markov Chains and Monte Carlo Methods (7 papers). Sumit Mukherjee is often cited by papers focused on Stochastic processes and statistical mechanics (13 papers), Random Matrices and Applications (11 papers) and Markov Chains and Monte Carlo Methods (7 papers). Sumit Mukherjee collaborates with scholars based in United States, Germany and United Kingdom. Sumit Mukherjee's co-authors include Bhaswar B. Bhattacharya, Amir Dembo, Anirban Basak, Promit Ghosal, Sabyasachi Chatterjee, Ming Yuan, Persi Diaconis, Rajarshi Mukherjee, Subhabrata Sen and Frank Aurzada and has published in prestigious journals such as IEEE Transactions on Information Theory, The Annals of Statistics and Communications in Mathematical Physics.

In The Last Decade

Co-authorship network of co-authors of Sumit Mukherjee i

Fields of papers citing papers by Sumit Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sumit Mukherjee

Since Specialization
Citations

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

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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2025