Shinjini Kundu

1.2k total citations
19 papers, 690 citations indexed

About

Shinjini Kundu is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Neurology. According to data from OpenAlex, Shinjini Kundu has authored 19 papers receiving a total of 690 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Health Informatics and 3 papers in Neurology. Recurrent topics in Shinjini Kundu's work include Artificial Intelligence in Healthcare and Education (4 papers), Functional Brain Connectivity Studies (3 papers) and Advanced Neuroimaging Techniques and Applications (3 papers). Shinjini Kundu is often cited by papers focused on Artificial Intelligence in Healthcare and Education (4 papers), Functional Brain Connectivity Studies (3 papers) and Advanced Neuroimaging Techniques and Applications (3 papers). Shinjini Kundu collaborates with scholars based in United States, United Kingdom and Denmark. Shinjini Kundu's co-authors include Gustavo K. Rohde, David Gur, Frank C. Sciurba, Jiantao Pu, John Tedrow, Joseph K. Leader, Suicheng Gu, Luca Foschini, Roxanne E. Jensen and Zhimin Wang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and NeuroImage.

In The Last Decade

Shinjini Kundu

18 papers receiving 676 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shinjini Kundu United States 11 173 164 153 139 50 19 690
Christopher A. Lovejoy United Kingdom 9 238 1.4× 335 2.0× 306 2.0× 66 0.5× 24 0.5× 14 844
Nhan Do United States 18 207 1.2× 88 0.5× 201 1.3× 98 0.7× 73 1.5× 85 1.2k
Inga Strümke Norway 9 271 1.6× 144 0.9× 168 1.1× 48 0.3× 102 2.0× 35 892
Vajira Thambawita Norway 10 247 1.4× 88 0.5× 183 1.2× 57 0.4× 134 2.7× 33 792
Luca Foschini United States 12 208 1.2× 160 1.0× 95 0.6× 41 0.3× 20 0.4× 28 696
Jarrel Seah Australia 15 119 0.7× 166 1.0× 341 2.2× 135 1.0× 31 0.6× 28 548
Varun Buch United States 8 132 0.8× 141 0.9× 152 1.0× 55 0.4× 30 0.6× 11 423
Raffaele Rasoini Italy 5 221 1.3× 249 1.5× 162 1.1× 43 0.3× 22 0.4× 8 715
Ravi Aggarwal United Kingdom 8 205 1.2× 182 1.1× 276 1.8× 81 0.6× 39 0.8× 12 769
Michelle Livne Germany 10 161 0.9× 102 0.6× 205 1.3× 161 1.2× 177 3.5× 17 702

Countries citing papers authored by Shinjini Kundu

Since Specialization
Citations

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

Fields of papers citing papers by Shinjini Kundu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shinjini Kundu

This figure shows the co-authorship network connecting the top 25 collaborators of Shinjini Kundu. A scholar is included among the top collaborators of Shinjini Kundu 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 Shinjini Kundu. Shinjini Kundu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Sivakumar, R., et al.. (2025). FDA Approval of Artificial Intelligence and Machine Learning Devices in Radiology. JAMA Network Open. 8(11). e2542338–e2542338.
2.
Kundu, Shinjini, Haris I. Sair, Elliott H. Sherr, Pratik Mukherjee, & Gustavo K. Rohde. (2024). Discovering the gene-brain-behavior link in autism via generative machine learning. Science Advances. 10(24). eadl5307–eadl5307. 4 indexed citations
3.
Sadeghi, Mohammad Amin, Daniel J. Stevens, Shinjini Kundu, et al.. (2024). Detecting Alzheimer’s Disease Stages and Frontotemporal Dementia in Time Courses of Resting-State fMRI Data Using a Machine Learning Approach. Journal of Imaging Informatics in Medicine. 37(6). 2768–2783. 10 indexed citations
4.
Kundu, Shinjini, Jeanelle Ariza, Amber Nolan, et al.. (2023). Mapping the individual human cortex using multidimensional MRI and unsupervised learning. Brain Communications. 5(6). fcad258–fcad258. 5 indexed citations
5.
Kundu, Shinjini. (2021). How will artificial intelligence change medical training?. Communications Medicine. 1(1). 8–8. 19 indexed citations
6.
Kundu, Shinjini. (2021). AI in medicine must be explainable. Nature Medicine. 27(8). 1328–1328. 184 indexed citations
7.
Kundu, Shinjini, Haiqing Huang, Kirk I. Erickson, et al.. (2021). Investigating impact of cardiorespiratory fitness in reducing brain tissue loss caused by ageing. Brain Communications. 3(4). fcab228–fcab228. 4 indexed citations
8.
Cutillo, Christine M., Karlie R. Sharma, Luca Foschini, et al.. (2020). Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency. npj Digital Medicine. 3(1). 47–47. 197 indexed citations
9.
Kundu, Shinjini, Beth G. Ashinsky, Mustapha Bouhrara, et al.. (2020). Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning. Proceedings of the National Academy of Sciences. 117(40). 24709–24719. 31 indexed citations
10.
Kundu, Shinjini, Anish Ghodadra, Saeed Fakhran, Lea Alhilali, & Gustavo K. Rohde. (2019). Assessing Postconcussive Reaction Time Using Transport-Based Morphometry of Diffusion Tensor Images. American Journal of Neuroradiology. 40(7). 1117–1123. 5 indexed citations
11.
Kundu, Shinjini, Soheil Kolouri, Kirk I. Erickson, et al.. (2017). Discovery and visualization of structural biomarkers from MRI using transport-based morphometry. NeuroImage. 167. 256–275. 20 indexed citations
12.
Kolouri, Soheil, et al.. (2017). The cumulative distribution transform and linear pattern classification. Applied and Computational Harmonic Analysis. 45(3). 616–641. 37 indexed citations
13.
Bonfield, Christopher M., Lesley M. Foley, Shinjini Kundu, et al.. (2015). The influence of surgical correction on white matter microstructural integrity in rabbits with familial coronal suture craniosynostosis. Neurosurgical FOCUS. 38(5). E3–E3. 7 indexed citations
14.
Kundu, Shinjini. (2014). Rapid improvement in post-infectious gastroparesis symptoms with mirtazapine. World Journal of Gastroenterology. 20(21). 6671–6671. 17 indexed citations
15.
Kundu, Shinjini, et al.. (2014). Resolution of Suicidal Ideation With Corticosteroids in a Patient With Concurrent Addison’s Disease and Depression. The Primary Care Companion For CNS Disorders. 16(6). 2 indexed citations
16.
Kundu, Shinjini, Lea Alhilali, Lananh Nguyen, & Saeed Fakhran. (2014). Angioglioma Misdiagnosed as Encephalomalacia on Magnetic Resonance Imaging for Over a Decade. Journal of Computer Assisted Tomography. 38(3). 485–487. 1 indexed citations
17.
Kundu, Shinjini, Suicheng Gu, Joseph K. Leader, et al.. (2013). Assessment of lung volume collapsibility in chronic obstructive lung disease patients using CT. European Radiology. 23(6). 1564–1572. 18 indexed citations
18.
Wang, Zhimin, Suicheng Gu, Joseph K. Leader, et al.. (2012). Optimal threshold in CT quantification of emphysema. European Radiology. 23(4). 975–984. 113 indexed citations
19.
Kundu, Shinjini. (2012). Light field compression using homography and 2D warping. 1349–1352. 16 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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