Sumit Kumar Jha

2.7k citations
124 papers · 1.0k · h-index 17

Impact in

Papers in

Sumit Kumar Jha

104 papers receiving 954 citations

Peers

Sumit Kumar Jha
Comparison fields: 5 of 102
  • Software 96
  • Hardware and Architecture 145
  • Computational Theory and Mathematics 185
  • Artificial Intelligence 291
  • Computer Vision and Pattern Recognition 174
Replace Susmit Jha with:
Susmit Jha United States
M. Watheq El‐Kharashi Egypt
Paris Kitsos Greece
Indranil Sengupta India
Nicola Bombieri Italy
James Bornholt United States
Alex Nicolau United States
Akhilesh Tyagi United States
Peter Athanas United States
David Gregg Ireland
Sumit Kumar Jha relative to Susmit Jha United States Susmit Jha's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sumit Kumar Jha

Since Specialization
Citations

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

Fields of papers citing papers by Sumit Kumar Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sumit Kumar Jha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sumit Kumar Jha Line = papers co-authored together Sumit Kumar Jha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 124 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200886
2 201986
3 200356
4 201145
5 200942
6 200235
7 199734
8 199732
9 202332
10 202030
11 201727
12 202122
13 201622
14
Attribution-Based Confidence Metric For Deep Neural Networks
201919
15 201819
16 201517
17 201616
18 202216
19 201414
20 202014

About Sumit Kumar Jha

Sumit Kumar Jha is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology and Software, having authored 124 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (40 papers), Ferroelectric and Negative Capacitance Devices (39 papers), Formal Methods in Verification (21 papers), Gene Regulatory Network Analysis (17 papers), Semiconductor materials and devices (15 papers), Adversarial Robustness in Machine Learning (11 papers), Neuroscience and Neural Engineering (9 papers) and Anomaly Detection Techniques and Applications (7 papers). The work is most often cited by research in Software (96 citations), Hardware and Architecture (145 citations), Computational Theory and Mathematics (185 citations), Artificial Intelligence (291 citations) and Computer Vision and Pattern Recognition (174 citations). Sumit Kumar Jha has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Susmit Jha, Alvaro Velasquez, Rickard Ewetz, Christopher J. Langmead, E. M. Clarke, Steven Lawrence Fernandes, Yuichi Motai, Arvind Ramanathan, Alex Groce and Sagar Chaki. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, BMC Bioinformatics, IEEE Transactions on Circuits & Systems II Express Briefs, Theoretical Computer Science and Computer Physics Communications.

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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