Ashis Talukder

10.1k total citations
59 papers, 794 citations indexed

About

Ashis Talukder is a scholar working on Nutrition and Dietetics, Pediatrics, Perinatology and Child Health and General Health Professions. According to data from OpenAlex, Ashis Talukder has authored 59 papers receiving a total of 794 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Nutrition and Dietetics, 19 papers in Pediatrics, Perinatology and Child Health and 13 papers in General Health Professions. Recurrent topics in Ashis Talukder's work include Child Nutrition and Water Access (19 papers), Global Maternal and Child Health (13 papers) and Food Security and Health in Diverse Populations (8 papers). Ashis Talukder is often cited by papers focused on Child Nutrition and Water Access (19 papers), Global Maternal and Child Health (13 papers) and Food Security and Health in Diverse Populations (8 papers). Ashis Talukder collaborates with scholars based in Bangladesh, Australia and United Kingdom. Ashis Talukder's co-authors include Benojir Ahammed, Iqramul Haq, Shaharior Rahman Razu, Sheikh Mohammed Shariful Islam, Larry D. Lynd, Hou Kroeun, Judy McLean, Christine M. McDonald, Tim Green and Md. Maniruzzaman and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ashis Talukder

53 papers receiving 774 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashis Talukder Bangladesh 15 230 227 194 144 80 59 794
Kapil Yadav India 15 111 0.5× 149 0.7× 118 0.6× 110 0.8× 53 0.7× 44 974
Benojir Ahammed Bangladesh 14 116 0.5× 179 0.8× 107 0.6× 108 0.8× 204 2.5× 43 923
Innocent B. Mboya Tanzania 15 91 0.4× 121 0.5× 101 0.5× 100 0.7× 53 0.7× 59 678
Md. Belal Hossain Bangladesh 15 220 1.0× 203 0.9× 172 0.9× 93 0.6× 7 0.1× 62 673
Hari Kusnanto Indonesia 15 63 0.3× 156 0.7× 171 0.9× 218 1.5× 72 0.9× 125 822
Syed Azizur Rahman United Arab Emirates 13 86 0.4× 290 1.3× 209 1.1× 102 0.7× 11 0.1× 60 816
Stephan Brenner Germany 18 92 0.4× 618 2.7× 433 2.2× 155 1.1× 31 0.4× 60 1.0k
Wendy Janssens Netherlands 14 68 0.3× 190 0.8× 257 1.3× 82 0.6× 10 0.1× 49 963
Anwar Islam Canada 14 110 0.5× 232 1.0× 240 1.2× 139 1.0× 5 0.1× 33 843
Vikas Bhatia India 12 93 0.4× 161 0.7× 111 0.6× 95 0.7× 30 0.4× 48 418

Countries citing papers authored by Ashis Talukder

Since Specialization
Citations

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

Fields of papers citing papers by Ashis Talukder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashis Talukder

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

All Works

20 of 20 papers shown
1.
Talukder, Ashis, et al.. (2024). Prediction of suicidal ideation with associated risk factors among university students in the southern part of Bangladesh: Machine learning approach. Journal of Affective Disorders. 349. 502–508. 10 indexed citations
2.
Razu, Shaharior Rahman, et al.. (2024). Prevalence and factors associated with tobacco smoking in Bangladesh. Discover Public Health. 21(1). 3 indexed citations
3.
Haq, Iqramul, Md. Ismail Hossain, Salma Akter, et al.. (2024). Individual- and community-level factors associated with the presence of adequate iodized salt in households in Bangladesh: a multilevel modelling approach. International Health. 17(1). 49–61.
4.
Talukder, Ashis, Matthew Kelly, Darren J. Gray, & Haribondhu Sarma. (2024). Prevalence and trends of double burden of malnutrition at household-level in South and Southeast Asia. Discover Public Health. 21(1). 2 indexed citations
5.
Talukder, Ashis, et al.. (2023). Understanding School Dropout and Its Impact on the Community in the Khulna Region of Bangladesh. Open Journal of Social Sciences. 11(11). 582–596. 2 indexed citations
6.
7.
Islam, Sheikh Mohammed Shariful, Ashis Talukder, Md. Abdul Awal, et al.. (2022). Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries. Frontiers in Cardiovascular Medicine. 9. 839379–839379. 54 indexed citations
8.
Islam, Md. Akhtarul, et al.. (2022). Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model. International Journal of Clinical Practice. 2022(1). 2212624–2212624. 7 indexed citations
9.
10.
Aktar, Sakifa, Ashis Talukder, Md. Martuza Ahamad, et al.. (2021). Machine Learning Approaches to Identify Patient Comorbidities and Symptoms That Increased Risk of Mortality in COVID-19. Diagnostics. 11(8). 1383–1383. 26 indexed citations
11.
Hossain, Md. Ismail, et al.. (2021). People’s Concerns With the Prediction of COVID-19 in Bangladesh: Application of Autoregressive Integrated Moving Average Model. International Journal of Travel Medicine and Global Health. 9(2). 84–93. 4 indexed citations
12.
Talukder, Ashis, et al.. (2021). Does worriedness among the rural adults promote COVID-19 related awareness in Bangladesh?. Heliyon. 7(3). e06556–e06556.
13.
Talukder, Ashis, et al.. (2021). Factors associated with age of mother at first birth in Albania: application of quantile regression model. Heliyon. 7(3). e06547–e06547. 6 indexed citations
14.
Talukder, Ashis, et al.. (2020). Early marriage in Bangladesh : a cross-sectional study exploring the associated factors.. Journal of international women's studies. 14 indexed citations
15.
Talukder, Ashis, et al.. (2020). Prevalence of Diabetes Mellitus and Its Associated Factors in Bangladesh: Application of Two-level Logistic Regression Model. Scientific Reports. 10(1). 10237–10237. 57 indexed citations
16.
Talukder, Ashis, et al.. (2020). Assessing the true association between hypertension status and stature of individuals in Bangladesh: propensity score analysis. Journal of Human Hypertension. 35(3). 250–256. 4 indexed citations
17.
Talukder, Ashis & Benojir Ahammed. (2020). Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh. Nutrition. 78. 110861–110861. 69 indexed citations
18.
Talukder, Ashis, et al.. (2018). Factors affecting stunting among children under five years of age in Bangladesh. Family Medicine & Primary Care Review. 356–362. 3 indexed citations
19.
Talukder, Ashis, et al.. (2017). Determination of Influencing Factors for Integrated Pest Management Adoption: A Logistic Regression Analysis. Agrotechnology. 6(2). 12 indexed citations
20.
McDonald, Christine M., Judy McLean, Hou Kroeun, et al.. (2014). Household food insecurity and dietary diversity as correlates of maternal and child undernutrition in rural Cambodia. European Journal of Clinical Nutrition. 69(2). 242–246. 75 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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