Jeff Rasley

2.5k total citations · 2 hit papers
15 papers, 1.3k citations indexed

About

Jeff Rasley is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jeff Rasley has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jeff Rasley's work include Advanced Neural Network Applications (5 papers), Parallel Computing and Optimization Techniques (4 papers) and Topic Modeling (4 papers). Jeff Rasley is often cited by papers focused on Advanced Neural Network Applications (5 papers), Parallel Computing and Optimization Techniques (4 papers) and Topic Modeling (4 papers). Jeff Rasley collaborates with scholars based in United States and United Kingdom. Jeff Rasley's co-authors include Yuxiong He, Olatunji Ruwase, Samyam Rajbhandari, Rodrigo Fonseca, Colin Dixon, John D. Carter, Brent Stephens, Eric Rozner, Wes Felter and Kanak Agarwal and has published in prestigious journals such as ACM SIGCOMM Computer Communication Review and Proceedings of the AAAI Conference on Human Computation and Crowdsourcing.

In The Last Decade

Jeff Rasley

15 papers receiving 1.3k citations

Hit Papers

DeepSpeed 2020 2026 2022 2024 2020 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeff Rasley United States 11 663 452 378 244 186 15 1.3k
Seunghak Lee United States 12 602 0.9× 432 1.0× 333 0.9× 255 1.0× 120 0.6× 24 1.1k
Qirong Ho United States 17 1.1k 1.6× 415 0.9× 505 1.3× 336 1.4× 159 0.9× 38 1.5k
Kang Chen China 20 331 0.5× 482 1.1× 400 1.1× 266 1.1× 314 1.7× 76 1.2k
Antonino Mazzeo Italy 18 330 0.5× 316 0.7× 134 0.4× 334 1.4× 284 1.5× 120 989
Jidong Zhai China 23 543 0.8× 959 2.1× 443 1.2× 518 2.1× 611 3.3× 120 1.6k
Kai Shuang China 20 343 0.5× 718 1.6× 179 0.5× 513 2.1× 78 0.4× 93 1.2k
Cody Hao Yu United States 15 364 0.5× 326 0.7× 379 1.0× 115 0.5× 492 2.6× 29 1.2k
Long Zheng China 16 254 0.4× 388 0.9× 293 0.8× 233 1.0× 283 1.5× 114 822

Countries citing papers authored by Jeff Rasley

Since Specialization
Citations

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

Fields of papers citing papers by Jeff Rasley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeff Rasley

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

All Works

15 of 15 papers shown
1.
Anthony, Quentin, Ammar Ahmad Awan, Jeff Rasley, et al.. (2023). MCR-DL: Mix-and-Match Communication Runtime for Deep Learning. 996–1006. 4 indexed citations
2.
Aminabadi, Reza Yazdani, Samyam Rajbhandari, Ammar Ahmad Awan, et al.. (2022). DeepSpeed- Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale. 1–15. 108 indexed citations
3.
Rajbhandari, Samyam, et al.. (2021). ZeRO-infinity. 1–14. 131 indexed citations
4.
Rajbhandari, Samyam, Jeff Rasley, Olatunji Ruwase, & Yuxiong He. (2020). ZeRO: Memory optimizations Toward Training Trillion Parameter Models. 1–16. 368 indexed citations breakdown →
5.
Rasley, Jeff, Samyam Rajbhandari, Olatunji Ruwase, & Yuxiong He. (2020). DeepSpeed. 3505–3506. 380 indexed citations breakdown →
6.
Zhang, Minjia, Samyam Rajbhandari, Wenhan Wang, et al.. (2019). Accelerating Large Scale Deep Learning Inference through DeepCPU at Microsoft.. 5–7. 3 indexed citations
7.
Rajbhandari, Samyam, Jeff Rasley, Olatunji Ruwase, & Yuxiong He. (2019). ZeRO: Memory Optimization Towards Training A Trillion Parameter Models.. 26 indexed citations
8.
Rasley, Jeff, Yuxiong He, Feng Yan, Olatunji Ruwase, & Rodrigo Fonseca. (2017). HyperDrive. 1–13. 22 indexed citations
9.
Rasley, Jeff, Konstantinos Karanasos, Srikanth Kandula, et al.. (2016). Efficient queue management for cluster scheduling. 1–15. 64 indexed citations
10.
Papoutsaki, Alexandra, et al.. (2015). Crowdsourcing from Scratch: A Pragmatic Experiment in Data Collection by Novice Requesters. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 3. 140–149. 13 indexed citations
11.
Rasley, Jeff, et al.. (2015). Detecting latent cross-platform API violations. 4440. 484–495. 2 indexed citations
12.
Rasley, Jeff, Brent Stephens, Colin Dixon, et al.. (2014). Planck. ACM SIGCOMM Computer Communication Review. 44(4). 407–418. 64 indexed citations
13.
Rasley, Jeff, Brent Stephens, Colin Dixon, et al.. (2014). Planck. 407–418. 116 indexed citations
14.
Rasley, Jeff, Brent Stephens, Colin Dixon, et al.. (2014). Low-latency Network Monitoring via Oversubscribed Port Mirroring. 1 indexed citations
15.
Cappos, Justin, et al.. (2010). Retaining sandbox containment despite bugs in privileged memory-safe code. 212–223. 28 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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