Aakash Kaku

909 total citations
5 papers, 20 citations indexed

About

Aakash Kaku is a scholar working on Rehabilitation, Epidemiology and Physical Therapy, Sports Therapy and Rehabilitation. According to data from OpenAlex, Aakash Kaku has authored 5 papers receiving a total of 20 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Rehabilitation, 4 papers in Epidemiology and 2 papers in Physical Therapy, Sports Therapy and Rehabilitation. Recurrent topics in Aakash Kaku's work include Stroke Rehabilitation and Recovery (4 papers), Acute Ischemic Stroke Management (3 papers) and Balance, Gait, and Falls Prevention (2 papers). Aakash Kaku is often cited by papers focused on Stroke Rehabilitation and Recovery (4 papers), Acute Ischemic Stroke Management (3 papers) and Balance, Gait, and Falls Prevention (2 papers). Aakash Kaku collaborates with scholars based in United States. Aakash Kaku's co-authors include Avinash Parnandi, Heidi M. Schambra, Carlos Fernandez‐Granda, Dawn M. Nilsen, Kangning Liu, Grace Kim, Narges Razavian and Rajesh Ranganath and has published in prestigious journals such as SHILAP Revista de lepidopterología, npj Digital Medicine and Bioengineering.

In The Last Decade

Aakash Kaku

5 papers receiving 20 citations

Peers

Aakash Kaku

REHAB

EPIDE

NEURO

HI

BE

Basaam Aweid United Kingdom

Bimsara Senanayake Sri Lanka

Vasanthan Rajagopalan India

Jan Fiksa Czechia

Artur Dziadkiewicz United Kingdom

Djamil Vahidassr United Kingdom

Jozef Haring Slovakia

Richard Burgess United States

Xiuge Tan China

Ivan Wiggam United Kingdom

Basaam Aweid United Kingdom

Aakash Kaku

7 ×0.6

REHAB

12 ×1.7

EPIDE

6 ×1.2

NEURO

1 ×0.2

HI

3 ×0.6

BE

Citations per year, relative to Aakash Kaku Aakash Kaku (= 1×) peers Basaam Aweid

Countries citing papers authored by Aakash Kaku

Since Specialization

Citations

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

Fields of papers citing papers by Aakash Kaku

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aakash Kaku

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

All Works

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5 of 5 papers shown

1.

Kaku, Aakash, et al.. (2024). Quantifying impairment and disease severity using AI models trained on healthy subjects. npj Digital Medicine. 7(1). 180–180. 1 indexed citations

2.

Parnandi, Avinash, Aakash Kaku, Grace Kim, et al.. (2023). Data-Driven Quantitation of Movement Abnormality after Stroke. Bioengineering. 10(6). 648–648. 4 indexed citations

3.

Parnandi, Avinash, et al.. (2022). PrimSeq: A deep learning-based pipeline to quantitate rehabilitation training. SHILAP Revista de lepidopterología. 1(6). e0000044–e0000044. 9 indexed citations

4.

Kaku, Aakash, et al.. (2022). StrokeRehab: A Benchmark Dataset for Sub-second Action Identification.. PubMed. 35. 1671–1684. 5 indexed citations

5.

Kaku, Aakash, et al.. (2021). Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning. arXiv (Cornell University). 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.

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