Microsoft (United States)

Papers in the tracked journals with an author at Microsoft (United States): per year and category, where they are published, the institutions its researchers write with, and its most-cited papers. A paper counts as corporate when at least one of its authors is affiliated with an institution that OpenAlex classifies as a company; it counts once for each company among its authors' affiliations. Universities are the institutions OpenAlex classifies as education. Also as Markdown.

← Corporate research

Key findings#

From 2017 to 2026 (so far), authors at Microsoft (United States) took part in 214 papers in the tracked journals, most of them in AI (158), economics (22) and operations research (16).
It ranks #12 among the companies publishing in the tracked journals from 2023 to 2025.
25 of them were published in 2025, against 25 in 2017.
Since 2023, the institutions with the most of these papers were University of Science and Technology of China (9), Microsoft Research Asia (China) (7) and City University of Hong Kong (4).
The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (20), Nature Machine Intelligence (8) and International Journal of Computer Vision (6).
The most-cited of them is “From local explanations to global understanding with explainable AI for trees” (Nature Machine Intelligence, 2020), with 10,493 citations.

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2017	2018	2019	2020	2021	2022	2023	2024	2025	2026 (so far)
AI	12	15	14	16	19	15	15	17	22	13
Economics	4	2	5	3	1	2	1	2	0	2
Operations Research	4	1	1	3	4	1	0	1	1	0
Statistics	1	1	2	1	0	1	1	2	1	0
Higher Education and Research	2	0	0	0	0	0	0	0	0	1
Information Systems	0	0	0	0	0	0	0	0	1	0
Finance	0	0	0	0	0	0	0	0	0	1
Tourism and Hospitality	1	0	0	0	0	0	0	0	0	0
Accounting	1	0	0	0	0	0	0	0	0	0
Management	0	0	0	0	0	0	0	0	0	1
All categories	25	19	22	23	24	19	17	22	25	18

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	IEEE Transactions on Pattern Analysis and Machine Intelligence	20
2	Nature Machine Intelligence	8
3	International Journal of Computer Vision	6
4	IEEE Transactions on Neural Networks and Learning Systems	5
5	Pattern Recognition	4
6	Expert Systems with Applications	4
7	IEEE Transactions on Knowledge and Data Engineering	4
8	Knowledge and Information Systems	3
9	Computer Speech & Language	3
10	Machine Learning	3

Institutions with the most papers, since 2023
#	Institution	Papers
1	University of Science and Technology of China	9
2	Microsoft Research Asia (China)	7
3	City University of Hong Kong	4
4	Nanjing University of Posts and Telecommunications	4
5	Nanyang Technological University	4
6	The University of Sydney	4
7	Zhejiang University	4
8	Carnegie Mellon University	3
9	Johns Hopkins University	3

Countries with the most papers, since 2023
#	Country	Papers
1	United States	82
2	China	30
3	Australia	10
4	United Kingdom	9
5	Hong Kong	9
6	Germany	7
7	Italy	5
8	Singapore	5
9	France	4
10	India	4

Keywords with the most papers, since 2023
#	Keyword	Papers
1	large language models	5
2	text-to-image generation	4
3	generative adversarial networks	3
4	graph neural networks	3
5	node classification	3
6	recommender systems	3
7	reinforcement learning	3
8	transformer models	3
9	Shapley value	2
10	artificial intelligence	2

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	10,493	128.8	From local explanations to global understanding with explainable AI for trees	Nature Machine Intelligence	2020-01-17	Scott Lundberg, Gabriel Erion, Hugh Chen et al.
2	4,889	61.9	Deep High-Resolution Representation Learning for Visual Recognition	IEEE Transactions on Pattern Analysis and Machine Intelligence	2020-04-01	Jingdong Wang, Ke Sun, Tianheng Cheng et al.
3	1,058	9.1	Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy	Business Economics	2017-03-10	Apurv Jain
4	676	12.3	PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning	IEEE Transactions on Pattern Analysis and Machine Intelligence	2022-04-05	Yunbo Wang, Haixu Wu, Jianjin Zhang et al.
5	490	5.5	EA-LSTM: Evolutionary attention-based LSTM for time series prediction	Knowledge-Based Systems	2019-05-27	Youru Li, Zhenfeng Zhu, Deqiang Kong et al.
6	361	6.1	A review of speaker diarization: Recent advances with deep learning	Computer Speech & Language	2021-11-13	Tae‐Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis et al.
7	343	3.8	Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos	IEEE Transactions on Pattern Analysis and Machine Intelligence	2019-04-25	Oscar Koller, Necati Cihan Camgöz, Hermann Ney et al.
8	299	4.6	Improving performance of deep learning models with axiomatic attribution priors and expected gradients	Nature Machine Intelligence	2021-05-31	Gabriel Erion, Joseph D. Janizek, Pascal Sturmfels et al.
9	197	5.9	NaturalSpeech : End-to-End Text-to-Speech Synthesis With Human-Level Quality	IEEE Transactions on Pattern Analysis and Machine Intelligence	2024-01-19	Xu Tan, Jiawei Chen, Haohe Liu et al.
10	193	2.7	Long-Term Visual Localization Revisited	IEEE Transactions on Pattern Analysis and Machine Intelligence	2020-10-21	Carl Toft, Will Maddern, Akihiko Torii et al.

Cite this page

Scholar4AI. (2026). Microsoft (United States). Journal Research Rankings. Retrieved October 31, 2026, from https://scholar4ai.com/companies/microsoft-united-states

@misc{scholar4ai-companies-microsoft-united-states,
  author = {{Scholar4AI}},
  title = {Microsoft (United States)},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/companies/microsoft-united-states}},
  urldate = {2026-10-31},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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