Wrick Talukdar

1.1k total citations · 1 hit paper
6 papers, 854 citations indexed

About

Wrick Talukdar is a scholar working on Artificial Intelligence, Health Informatics and Management Science and Operations Research. According to data from OpenAlex, Wrick Talukdar has authored 6 papers receiving a total of 854 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Health Informatics and 2 papers in Management Science and Operations Research. Recurrent topics in Wrick Talukdar's work include Topic Modeling (4 papers), Machine Learning in Healthcare (2 papers) and Natural Language Processing Techniques (2 papers). Wrick Talukdar is often cited by papers focused on Topic Modeling (4 papers), Machine Learning in Healthcare (2 papers) and Natural Language Processing Techniques (2 papers). Wrick Talukdar collaborates with scholars based in United States. Wrick Talukdar's co-authors include Anjanava Biswas and has published in prestigious journals such as ArXiv.org, World Journal of Advanced Engineering Technology and Sciences and International Research Journal of Modernization in Engineering Technology and Science.

In The Last Decade

Wrick Talukdar

5 papers receiving 36 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.

Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation

2024 829 citations Anjanava Biswas, Wrick Talukdar International Journal of Innovative Science and Research Technology (IJISRT) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wrick Talukdar United States	3	87	82	73	73	48	6	854
Anjanava Biswas United States	3	85 1.0×	81 1.0×	73 1.0×	73 1.0×	47 1.0×	7	857
Zhuoyue Wang China	7	96 1.1×	72 0.9×	72 1.0×	71 1.0×	45 0.9×	14	1.0k
Lakshin Pathak India	3	72 0.8×	71 0.9×	73 1.0×	70 1.0×	40 0.8×	17	824
Supriyanto Supriyanto Indonesia	5	72 0.8×	80 1.0×	74 1.0×	75 1.0×	40 0.8×	23	852
Mili Virani India	2	69 0.8×	69 0.8×	73 1.0×	69 0.9×	38 0.8×	4	811
Deepika Kanyal India	3	69 0.8×	68 0.8×	73 1.0×	69 0.9×	37 0.8×	7	820
Jyotsana Patel India	2	69 0.8×	68 0.8×	73 1.0×	69 0.9×	37 0.8×	4	817
Raj Sekhar India	4	72 0.8×	68 0.8×	73 1.0×	69 0.9×	42 0.9×	4	848
Nyoman Ariana Indonesia	2	69 0.8×	68 0.8×	72 1.0×	72 1.0×	37 0.8×	9	812
Shweta Khare Sweden	5	69 0.8×	68 0.8×	73 1.0×	70 1.0×	37 0.8×	10	868

Countries citing papers authored by Wrick Talukdar

Since Specialization

Citations

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

Fields of papers citing papers by Wrick Talukdar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wrick Talukdar

This figure shows the co-authorship network connecting the top 25 collaborators of Wrick Talukdar. A scholar is included among the top collaborators of Wrick Talukdar 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 Wrick Talukdar. Wrick Talukdar 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:

6 of 6 papers shown

1.

Biswas, Anjanava & Wrick Talukdar. (2024). FinEmbedDiff: A Cost-Effective Approach of Classifying Financial Documents with Vector Sampling using Multi-modal Embedding Models. International Research Journal of Modernization in Engineering Technology and Science.

2.

Talukdar, Wrick & Anjanava Biswas. (2024). Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for Accurate Natural Language Task Modeling. International Journal of Innovative Science and Research Technology (IJISRT). 1499–1508. 11 indexed citations

3.

Biswas, Anjanava & Wrick Talukdar. (2024). Enhancing Clinical Documentation with Synthetic Data: Leveraging Generative Models for Improved Accuracy. International Journal of Innovative Science and Research Technology (IJISRT). 1553–1566. 2 indexed citations

4.

Biswas, Anjanava & Wrick Talukdar. (2024). Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation. International Journal of Innovative Science and Research Technology (IJISRT). 994–1008. 829 indexed citations breakdown →

5.

Talukdar, Wrick, et al.. (2023). Guardrails for trust, safety, and ethical development and deployment of Large Language Models (LLM). ArXiv.org. 4(6). 55–82. 10 indexed citations

6.

Talukdar, Wrick & Anjanava Biswas. (2023). Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity. World Journal of Advanced Engineering Technology and Sciences. 10(2). 283–296. 2 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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