Esha Choukse

569 total citations · 2 hit papers
23 papers, 298 citations indexed

About

Esha Choukse is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture. According to data from OpenAlex, Esha Choukse has authored 23 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Networks and Communications, 13 papers in Information Systems and 12 papers in Hardware and Architecture. Recurrent topics in Esha Choukse's work include Cloud Computing and Resource Management (13 papers), Parallel Computing and Optimization Techniques (12 papers) and Advanced Data Storage Technologies (10 papers). Esha Choukse is often cited by papers focused on Cloud Computing and Resource Management (13 papers), Parallel Computing and Optimization Techniques (12 papers) and Advanced Data Storage Technologies (10 papers). Esha Choukse collaborates with scholars based in United States, United Kingdom and Germany. Esha Choukse's co-authors include Mattan Erez, Michael B. Sullivan, Jung Rae Kim, Íñigo Goiri, Ricardo Bianchini, Pratyush Patel, Saeed Maleki, Alaa R. Alameldeen, Josep Torrellas and Akshitha Sriraman and has published in prestigious journals such as IEEE Micro, IEEE Computer Architecture Letters and ACM SIGARCH Computer Architecture News.

In The Last Decade

Esha Choukse

21 papers receiving 291 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.

Splitwise: Efficient Generative LLM Inference Using Phase Splitting

2024 67 citations Pratyush Patel, Esha Choukse et al. profile →
DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency

2025 17 citations Íñigo Goiri, Josep Torrellas et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Esha Choukse United States	10	162	147	73	63	57	23	298
Marco Lattuada Italy	10	116 0.7×	133 0.9×	54 0.7×	54 0.9×	75 1.3×	40	258
Stephen D. Strowes United Kingdom	8	212 1.3×	34 0.2×	79 1.1×	85 1.3×	39 0.7×	14	257
Markus Happe Germany	9	92 0.6×	129 0.9×	48 0.7×	120 1.9×	38 0.7×	18	277
Charlie Tai United States	6	253 1.6×	98 0.7×	15 0.2×	103 1.6×	97 1.7×	15	305
Mohammad Alian United States	12	238 1.5×	175 1.2×	76 1.0×	122 1.9×	83 1.5×	29	373
Jalil Boukhobza France	10	204 1.3×	84 0.6×	28 0.4×	71 1.1×	78 1.4×	46	288
Resit Sendag United States	9	165 1.0×	185 1.3×	23 0.3×	94 1.5×	29 0.5×	37	260
Jiaqi Gao China	10	199 1.2×	39 0.3×	33 0.5×	50 0.8×	77 1.4×	29	252
Rajeev Wankar India	9	191 1.2×	55 0.4×	39 0.5×	22 0.3×	85 1.5×	42	221
Yuebin Bai China	9	129 0.8×	74 0.5×	86 1.2×	70 1.1×	73 1.3×	33	251

Countries citing papers authored by Esha Choukse

Since Specialization

Citations

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

Fields of papers citing papers by Esha Choukse

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Esha Choukse

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

20 of 20 papers shown

1.

Goiri, Íñigo, et al.. (2025). TAPAS: Thermal- and Power-Aware Scheduling for LLM Inference in Cloud Platforms. 1266–1281. 3 indexed citations

2.

Jain, Kunal, Esha Choukse, Jue Zhang, et al.. (2025). Performance Aware LLM Load Balancer for Mixed Workloads. 19–30. 1 indexed citations

3.

Berger, Daniel S., Fiodar Kazhamiaka, Chaojie Zhang, et al.. (2025). Enabling Sustainable Cloud Computing With Low-Carbon Server Design. IEEE Micro. 45(4). 19–28.

4.

Goiri, Íñigo, et al.. (2025). DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency. 1348–1362. 17 indexed citations breakdown →

5.

Choukse, Esha, Pratyush Patel, Íñigo Goiri, et al.. (2025). Splitwise: Efficient Generative LLM Inference Using Phase Splitting. IEEE Micro. 45(4). 54–59. 2 indexed citations

6.

Chaudhry, Gohar Irfan, Esha Choukse, Íñigo Goiri, et al.. (2025). Towards Resource-Efficient Compound AI Systems. 218–224. 1 indexed citations

7.

Patel, Pratyush, et al.. (2024). Splitwise: Efficient Generative LLM Inference Using Phase Splitting. 118–132. 67 indexed citations breakdown →

8.

Berger, Daniel S., Fiodar Kazhamiaka, Chaojie Zhang, et al.. (2024). Designing Cloud Servers for Lower Carbon. 452–470. 13 indexed citations

9.

Choukse, Esha, et al.. (2024). DyLeCT: Achieving Huge-page-like Translation Performance for Hardware-compressed Memory. 1129–1143. 1 indexed citations

10.

Goiri, Íñigo, Esha Choukse, Mayukh Das, et al.. (2024). SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud. 437–451. 3 indexed citations

11.

Patel, Pratyush, et al.. (2024). Input-Dependent Power Usage in GPUs. 1872–1877. 1 indexed citations

12.

Choukse, Esha, et al.. (2024). Mosaic: Harnessing the Micro-Architectural Resources of Servers in Serverless Environments. 1397–1412. 2 indexed citations

13.

Patel, Pratyush, et al.. (2024). Characterizing Power Management Opportunities for LLMs in the Cloud. 207–222. 23 indexed citations

14.

Frost, Kali, Esha Choukse, Rodrigo Fonseca, et al.. (2023). Myths and Misconceptions Around Reducing Carbon Embedded in Cloud Platforms. 1–7. 12 indexed citations

15.

Patel, Pratyush, et al.. (2023). Towards Improved Power Management in Cloud GPUs. IEEE Computer Architecture Letters. 22(2). 141–144. 11 indexed citations

16.

Choukse, Esha, Íñigo Goiri, Ashish Raniwala, et al.. (2022). Overclocking in Immersion-Cooled Datacenters. IEEE Micro. 42(4). 10–17. 9 indexed citations

17.

Liu, Yuqing, et al.. (2022). Translation-optimized Memory Compression for Capacity. 992–1011. 4 indexed citations

18.

Choukse, Esha, Mattan Erez, & Alaa R. Alameldeen. (2018). Compresso: Pragmatic Main Memory Compression. 546–558. 21 indexed citations

19.

Choukse, Esha, Mattan Erez, & Alaa R. Alameldeen. (2018). CompressPoints: An Evaluation Methodology for Compressed Memory Systems. IEEE Computer Architecture Letters. 17(2). 126–129. 4 indexed citations

20.

Kim, Jung Rae, Michael B. Sullivan, Esha Choukse, & Mattan Erez. (2016). Bit-plane compression. ACM SIGARCH Computer Architecture News. 44(3). 329–340. 40 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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