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.
Additive manufacturing of metallic components – Process, structure and properties
20176.0k citationsT. DebRoy, Huiliang Wei et al.Progress in Materials Scienceprofile →
An improved prediction of residual stresses and distortion in additive manufacturing
2016598 citationsTuhin Mukherjee, Wei Zhang et al.profile →
Scientific, technological and economic issues in metal printing and their solutions
2019421 citationsT. DebRoy, Tuhin Mukherjee et al.Nature Materialsprofile →
Mechanistic models for additive manufacturing of metallic components
2020392 citationsHuiliang Wei, Tuhin Mukherjee et al.Progress in Materials Scienceprofile →
Printability of alloys for additive manufacturing
2016387 citationsTuhin Mukherjee, J.S. Zuback et al.profile →
Metallurgy, mechanistic models and machine learning in metal printing
2020346 citationsT. DebRoy, Tuhin Mukherjee et al.profile →
Control of grain structure, phases, and defects in additive manufacturing of high-performance metallic components
2023137 citationsTuhin Mukherjee, J. W. Elmer et al.Progress in Materials Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Tuhin Mukherjee
Since
Specialization
Citations
This map shows the geographic impact of Tuhin 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 Tuhin Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tuhin Mukherjee more than expected).
This network shows the impact of papers produced by Tuhin 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 Tuhin Mukherjee. The network helps show where Tuhin Mukherjee may publish in the future.
Co-authorship network of co-authors of Tuhin Mukherjee
This figure shows the co-authorship network connecting the top 25 collaborators of Tuhin Mukherjee.
A scholar is included among the top collaborators of Tuhin Mukherjee 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 Tuhin Mukherjee. Tuhin Mukherjee is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Mukherjee, Tuhin, J. W. Elmer, Huiliang Wei, et al.. (2023). Control of grain structure, phases, and defects in additive manufacturing of high-performance metallic components. Progress in Materials Science. 138. 101153–101153.137 indexed citations breakdown →
Wei, Huiliang, Tuhin Mukherjee, Wei Zhang, et al.. (2020). Mechanistic models for additive manufacturing of metallic components. Progress in Materials Science. 116. 100703–100703.392 indexed citations breakdown →
14.
DebRoy, T., Tuhin Mukherjee, J. Milewski, et al.. (2019). Scientific, technological and economic issues in metal printing and their solutions. Nature Materials. 18(10). 1026–1032.421 indexed citations breakdown →
DebRoy, T., Huiliang Wei, J.S. Zuback, et al.. (2017). Additive manufacturing of metallic components – Process, structure and properties. Progress in Materials Science. 92. 112–224.6046 indexed citations breakdown →
18.
Mukherjee, Tuhin. (2012). To judge an interdisciplinary approach for stock market prediction: Evidence from India. International Conference on Bioinformatics. 2(11). 185–191.2 indexed citations
19.
Ghoshal, Arnab, et al.. (2011). An empirical study in indian share market using neural network and genetic algorithm. Asian Journal of Research in Banking and Finance. 1(1). 1–19.1 indexed citations
20.
Mukherjee, Tuhin, et al.. (2010). Performance evaluation of Neural Network approach in financial prediction: Evidence from Indian Market. 597–602.13 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.