Mostofa Patwary

2.2k total citations
10 papers, 210 citations indexed

About

Mostofa Patwary is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Mostofa Patwary has authored 10 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Computer Networks and Communications. Recurrent topics in Mostofa Patwary's work include Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Graph Theory and Algorithms (2 papers). Mostofa Patwary is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Graph Theory and Algorithms (2 papers). Mostofa Patwary collaborates with scholars based in United States, Hong Kong and Norway. Mostofa Patwary's co-authors include Mohammad Shoeybi, Raul Puri, Yang Zhang, Hoo-Chang Shin, Bryan Catanzaro, Anima Anandkumar, Pascale Fung, Peng Xu, Fredrik Manne and Alok Choudhary and has published in prestigious journals such as SIAM Journal on Scientific Computing and Rare & Special e-Zone (The Hong Kong University of Science and Technology).

In The Last Decade

Mostofa Patwary

9 papers receiving 200 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mostofa Patwary United States	5	147	39	32	26	22	10	210
Ehsan Zare Borzeshi Australia	9	180 1.2×	53 1.4×	78 2.4×	10 0.4×	11 0.5×	14	231
Delaram Kahrobaei United States	7	168 1.1×	41 1.1×	21 0.7×	48 1.8×	9 0.4×	42	266
Beyza Ermiş Türkiye	7	88 0.6×	24 0.6×	15 0.5×	27 1.0×	13 0.6×	18	172
Mosha Chen China	13	509 3.5×	47 1.2×	59 1.8×	67 2.6×	11 0.5×	19	543
Maosong Sun China	7	214 1.5×	28 0.7×	13 0.4×	33 1.3×	46 2.1×	16	237
Siyuan Cheng China	6	117 0.8×	32 0.8×	9 0.3×	10 0.4×	10 0.5×	15	144
Yuxian Gu China	6	259 1.8×	72 1.8×	14 0.4×	44 1.7×	15 0.7×	9	311
Deepak Nathani United States	5	360 2.4×	53 1.4×	24 0.8×	44 1.7×	4 0.2×	6	399
Wenmian Yang China	8	165 1.1×	38 1.0×	27 0.8×	31 1.2×	7 0.3×	14	236
Ines Chami United States	3	72 0.5×	13 0.3×	17 0.5×	19 0.7×	7 0.3×	6	111

Countries citing papers authored by Mostofa Patwary

Since Specialization

Citations

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

Fields of papers citing papers by Mostofa Patwary

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mostofa Patwary

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

10 of 10 papers shown

1.

Su, Dan, Ying Lin, Joseph Jennings, et al.. (2025). Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset. 2459–2475.

2.

Su, Dan, Mostofa Patwary, Shrimai Prabhumoye, et al.. (2023). Context Generation Improves Open Domain Question Answering. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 793–808. 4 indexed citations

3.

Prabhumoye, Shrimai, Mostofa Patwary, Mohammad Shoeybi, & Bryan Catanzaro. (2023). Adding Instructions during Pretraining: Effective way of Controlling Toxicity in Language Models. 2636–2651. 2 indexed citations

4.

Xu, Peng, Mostofa Patwary, Shrimai Prabhumoye, et al.. (2022). Evaluating Parameter Efficient Learning for Generation. 4824–4833. 1 indexed citations

5.

Xu, Peng, Mostofa Patwary, Mohammad Shoeybi, et al.. (2020). MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2831–2845. 62 indexed citations

6.

Shin, Hoo-Chang, et al.. (2020). BioMegatron: Larger Biomedical Domain Language Model. 4700–4706. 68 indexed citations

7.

Patwary, Mostofa, Milind Chabbi, Heewoo Jun, et al.. (2019). Language Modeling at Scale. abs 1802 8021. 590–599. 3 indexed citations

8.

Khan, Arif, Alex Pothen, Mostofa Patwary, et al.. (2016). Efficient Approximation Algorithms for Weighted $b$-Matching. SIAM Journal on Scientific Computing. 38(5). S593–S619. 24 indexed citations

9.

Patwary, Mostofa, Diana Palsetia, Ankit Agrawal, et al.. (2013). Scalable parallel OPTICS data clustering using graph algorithmic techniques. 1–12. 36 indexed citations

10.

Palsetia, Diana, Mostofa Patwary, Xiaoying Zhang, et al.. (2012). User-Interest based Community Extraction in Social Networks. 10 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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