Sudeshna Das

7.4k total citations · 3 hit papers
88 papers, 3.5k citations indexed

About

Sudeshna Das is a scholar working on Molecular Biology, Physiology and Neurology. According to data from OpenAlex, Sudeshna Das has authored 88 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 32 papers in Physiology and 20 papers in Neurology. Recurrent topics in Sudeshna Das's work include Alzheimer's disease research and treatments (28 papers), Neuroinflammation and Neurodegeneration Mechanisms (18 papers) and Dementia and Cognitive Impairment Research (13 papers). Sudeshna Das is often cited by papers focused on Alzheimer's disease research and treatments (28 papers), Neuroinflammation and Neurodegeneration Mechanisms (18 papers) and Dementia and Cognitive Impairment Research (13 papers). Sudeshna Das collaborates with scholars based in United States, United Kingdom and India. Sudeshna Das's co-authors include Bradley T. Hyman, Alberto Serrano‐Pozo, Tim W. Clark, Eloïse Hudry, Ayush Noori, Steven E. Arnold, Rachel E. Bennett, Miwei Hu, Colin Magdamo and Eric Karran and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Sudeshna Das

79 papers receiving 3.5k citations

Hit Papers

align trajectories

What are hit papers?

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.

APOE and Alzheimer's disease: advances in genetics, pathophysiology, and therapeutic approaches

2020 609 citations Alberto Serrano‐Pozo, Sudeshna Das et al. profile →
The Major Risk Factors for Alzheimer’s Disease: Age, Sex, and Genes Modulate the Microglia Response to Aβ Plaques

2019 539 citations Maya E. Woodbury, Sudeshna Das et al. profile →
Increased mitochondrial calcium levels associated with neuronal death in a mouse model of Alzheimer’s disease

2020 315 citations Sudeshna Das, Alberto Serrano‐Pozo et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sudeshna Das United States	25	1.4k	1.3k	1.1k	461	386	88	3.5k
Lynn M. Bekris United States	26	1.3k 1.0×	1.0k 0.8×	910 0.8×	358 0.8×	379 1.0×	52	3.0k
Maya Koronyo‐Hamaoui United States	28	1.7k 1.2×	1.1k 0.8×	1.5k 1.3×	468 1.0×	346 0.9×	72	4.0k
Kiran Bhaskar United States	27	1.9k 1.4×	1.1k 0.8×	1.3k 1.2×	621 1.3×	328 0.8×	52	3.3k
Diego Mastroeni United States	30	1.9k 1.4×	2.8k 2.0×	980 0.9×	568 1.2×	287 0.7×	60	4.6k
Daniel Paris United States	37	2.0k 1.4×	1.3k 1.0×	1.3k 1.1×	522 1.1×	391 1.0×	100	3.9k
Justin M. Long United States	18	1.8k 1.3×	1.4k 1.0×	841 0.8×	446 1.0×	157 0.4×	27	3.5k
Kristina Mullin United States	20	2.4k 1.8×	1.8k 1.3×	1.0k 0.9×	642 1.4×	409 1.1×	35	4.5k
Mitchell K.P. Lai Singapore	40	1.6k 1.2×	1.4k 1.1×	1.0k 0.9×	701 1.5×	371 1.0×	144	4.8k
Naoyuki Sato Japan	34	1.5k 1.1×	1.3k 0.9×	670 0.6×	471 1.0×	172 0.4×	143	4.1k
Philip B. Verghese United States	22	2.0k 1.4×	1000 0.7×	806 0.7×	631 1.4×	144 0.4×	41	3.2k

Countries citing papers authored by Sudeshna Das

Since Specialization

Citations

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

Fields of papers citing papers by Sudeshna Das

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudeshna Das

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Das, Sudeshna, et al.. (2025). Seed-competent tau oligomers’ activity correlates with the rate of progression in sporadic Alzheimer's disease patients. Journal of Alzheimer s Disease. 109(2). 864–875.

Magdamo, Colin, et al.. (2025). High-Throughput Phenotyping of the Symptoms of Alzheimer Disease and Related Dementias Using Large Language Models: Cross-Sectional Study. PubMed. 4. e66926–e66926.

Gopinath, Karthik, Douglas N. Greve, Colin Magdamo, et al.. (2025). “Recon-all-clinical”: Cortical surface reconstruction and analysis of heterogeneous clinical brain MRI. Medical Image Analysis. 103. 103608–103608. 1 indexed citations

Sun, Haoqi, Sarah E. Turbett, Sudeshna Das, et al.. (2025). A Machine Learning Approach for Identifying People With Neuroinfectious Diseases in Electronic Health Records: Algorithm Development and Validation. JMIR Medical Informatics. 13. e63157–e63157.

Magdamo, Colin, Bradley T. Hyman, John R. Dickson, et al.. (2025). Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study. JMIR Aging. 8. e65178–e65178. 1 indexed citations

Wu, Chao‐Yi, Chen Liu, Jennifer R. Gatchel, et al.. (2025). Combined use of plasma p‐tau217, NfL, and GFAP predicts domain‐specific cognitive decline in cognitively unimpaired and MCI individuals. Alzheimer s & Dementia. 21(12). e70934–e70934.

Magdamo, Colin, John R. Dickson, M. Brandon Westover, et al.. (2024). Evaluating Sociodemographic Bias in an Artificial Intelligence Algorithm to Detect Cognitive Impairment in Electronic Health Records. Alzheimer s & Dementia. 20(S4).

Noori, Ayush, et al.. (2024). Alzheimer DataLENS: An Open Data Analytics Portal for Alzheimer’s Disease Research. Journal of Alzheimer s Disease. 99(s2). S397–S407. 1 indexed citations

Bryant, Annie G., Zhaozhi Li, Alberto Serrano‐Pozo, et al.. (2023). Endothelial Cells Are Heterogeneous in Different Brain Regions and Are Dramatically Altered in Alzheimer's Disease. Journal of Neuroscience. 43(24). 4541–4557. 31 indexed citations

10.

Billot, Benjamin, et al.. (2023). Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets. Proceedings of the National Academy of Sciences. 120(9). e2216399120–e2216399120. 78 indexed citations

11.

Li, Zhaozhi, Astrid Wachter, Ayush Noori, et al.. (2023). The APOEε4 allele exacerbates the transcriptomic responses to Aβ plaques and neurofibrillary tangles in Alzheimer’s disease. Alzheimer s & Dementia. 19(S1). 1 indexed citations

12.

Weinberg, Marc S., Colin Magdamo, Sun Young Chung, et al.. (2023). Association of BCG Vaccine Treatment With Death and Dementia in Patients With Non–Muscle-Invasive Bladder Cancer. JAMA Network Open. 6(5). e2314336–e2314336. 19 indexed citations

13.

Ge, Wendong, Haitham Alabsi, Aayushee Jain, et al.. (2022). Identifying Patients With Delirium Based on Unstructured Clinical Notes: Observational Study. JMIR Formative Research. 6(6). e33834–e33834. 11 indexed citations

14.

Ma, Yuan, Deborah Blacker, Anand Viswanathan, et al.. (2021). Visit-to-Visit Blood Pressure Variability, Neuropathology, and Cognitive Decline. Neurology. 96(23). e2812–e2823. 39 indexed citations

15.

Carlyle, Becky C., Johannes Kreuzer, Sudeshna Das, et al.. (2021). Synaptic proteins associated with cognitive performance and neuropathology in older humans revealed by multiplexed fractionated proteomics. Neurobiology of Aging. 105. 99–114. 41 indexed citations

16.

Fernandes, Marta, Haoqi Sun, Aayushee Jain, et al.. (2020). Classification of the Disposition of Patients Hospitalized with COVID-19: Reading Discharge Summaries Using Natural Language Processing. JMIR Medical Informatics. 9(2). e25457–e25457. 8 indexed citations

17.

Das, Sudeshna, et al.. (2016). The Process of Meaning Making from Trauma Generated out of Sexual Abuse in Childhood. Indian Journal of Positive Psychology. 7(3). 366–370. 2 indexed citations

18.

Das, Sudeshna, et al.. (2013). The Drosophila T-box transcription factor Midline functions within the Notch–Delta signaling pathway to specify sensory organ precursor cell fates and regulates cell survival within the eye imaginal disc. Mechanisms of Development. 130(11-12). 577–601. 10 indexed citations

19.

Clark, Tim W., et al.. (2009). Scientific publications on Web 3.0.. International Conference on Electronic Publishing. 107–129. 1 indexed citations

20.

Das, Sudeshna, et al.. (2005). A Study on the Construction of a Scale for Assessing the Quality of Friendship. Indian Journal of Health and Wellbeing. 6(3). 236–242. 1 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.

Explore authors with similar magnitude of impact