Jack Sampson

2.5k total citations
83 papers, 2.0k citations indexed

About

Jack Sampson is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Computer Networks and Communications. According to data from OpenAlex, Jack Sampson has authored 83 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Electrical and Electronic Engineering, 43 papers in Hardware and Architecture and 36 papers in Computer Networks and Communications. Recurrent topics in Jack Sampson's work include Parallel Computing and Optimization Techniques (43 papers), Interconnection Networks and Systems (19 papers) and Advanced Memory and Neural Computing (18 papers). Jack Sampson is often cited by papers focused on Parallel Computing and Optimization Techniques (43 papers), Interconnection Networks and Systems (19 papers) and Advanced Memory and Neural Computing (18 papers). Jack Sampson collaborates with scholars based in United States, China and Taiwan. Jack Sampson's co-authors include Michael Taylor, Steven Swanson, Ganesh Venkatesh, Vijaykrishnan Narayanan, Saturnino Garcia, Jose Lugo-Martinez, Xueqing Li, Yuan Xie, Karthik Swaminathan and Dean M. Tullsen and has published in prestigious journals such as IEEE Transactions on Circuits and Systems I Regular Papers, ACM SIGPLAN Notices and IEEE Micro.

In The Last Decade

Jack Sampson

78 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jack Sampson United States	19	1.2k	1.1k	1.0k	349	139	83	2.0k
G. De Micheli United States	14	858 0.7×	735 0.7×	887 0.9×	198 0.6×	97 0.7×	35	1.6k
Lars Bauer Germany	21	841 0.7×	1.0k 0.9×	765 0.7×	164 0.5×	241 1.7×	114	1.8k
Keith I. Farkas United States	19	1.7k 1.5×	1.5k 1.4×	786 0.8×	365 1.0×	164 1.2×	41	2.2k
Trevor Pering United States	20	945 0.8×	1.0k 0.9×	1.3k 1.3×	299 0.9×	280 2.0×	39	2.4k
Alper Buyuktosunoglu United States	29	2.8k 2.4×	2.0k 1.8×	1.8k 1.7×	587 1.7×	137 1.0×	126	3.5k
Cheng‐Kuan Lin Taiwan	24	412 0.4×	1.9k 1.7×	881 0.9×	160 0.5×	77 0.6×	139	2.1k
Aviral Shrivastava United States	25	1.5k 1.2×	1.1k 1.0×	815 0.8×	80 0.2×	145 1.0×	173	2.1k
Pedro López Spain	25	869 0.7×	2.1k 2.0×	816 0.8×	464 1.3×	168 1.2×	145	2.4k
Andreas Herkersdorf Germany	21	983 0.8×	924 0.8×	508 0.5×	100 0.3×	56 0.4×	198	1.5k
Tom Burd United States	10	1.1k 1.0×	627 0.6×	1.1k 1.1×	177 0.5×	82 0.6×	21	1.9k

Countries citing papers authored by Jack Sampson

Since Specialization

Citations

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

Fields of papers citing papers by Jack Sampson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jack Sampson

This figure shows the co-authorship network connecting the top 25 collaborators of Jack Sampson. A scholar is included among the top collaborators of Jack Sampson 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 Jack Sampson. Jack Sampson 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

Payer, Mathias, et al.. (2025). SoK: Challenges and Paths Toward Memory Safety for eBPF. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 848–866. 1 indexed citations

Payer, Mathias, et al.. (2024). Comprehensive Memory Safety Validation: An Alternative Approach to Memory Safety. IEEE Security & Privacy. 22(4). 40–49. 2 indexed citations

Kandemir, Mahmut, et al.. (2022). An architecture interface and offload model for low-overhead, near-data, distributed accelerators. 1160–1177. 8 indexed citations

Hung, Je-Min, Chun‐Ying Lee, Cheng-Xin Xue, et al.. (2021). CiM3D: Comparator-in-Memory Designs Using Monolithic 3-D Technology for Accelerating Data-Intensive Applications. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 7(1). 79–87. 5 indexed citations

Srinivasa, Srivatsa, Xueqing Li, Wei-Hao Chen, et al.. (2019). ROBIN: Monolithic-3D SRAM for Enhanced Robustness with In-Memory Computation Support. IEEE Transactions on Circuits and Systems I Regular Papers. 66(7). 2533–2545. 22 indexed citations

Sampson, Jack, et al.. (2019). Context-Aware Convolutional Neural Network over Distributed System in Collaborative Computing. 1–6. 10 indexed citations

Sampson, Jack, et al.. (2019). Context-Aware Collaborative Object Recognition For Distributed Multi Camera Time Series Data. 154–161. 1 indexed citations

George, Sumitha, et al.. (2018). MDACache: Caching for Multi-Dimensional-Access Memories. 841–854. 12 indexed citations

Ma, Kaisheng, Zheng Yang, Shuangchen Li, et al.. (2015). Architecture exploration for ambient energy harvesting nonvolatile processors. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 526–537. 199 indexed citations

10.

Irick, Kevin, et al.. (2015). A scalable architecture for multi-class visual object detection. 1–8. 11 indexed citations

11.

Cheng, Hsiang-Yun, Matt Poremba, M.J. Irwin, et al.. (2015). EECache. ACM Transactions on Architecture and Code Optimization. 12(2). 1–22. 6 indexed citations

12.

Gupta, Anshuman, Jack Sampson, & Michael Taylor. (2014). Quality Time: A simple online technique for quantifying multicore execution efficiency. 53. 169–179. 2 indexed citations

13.

Cotter, Matthew, et al.. (2014). A hardware accelerated multilevel visual classifier for embedded visual-assist systems. 96–100. 6 indexed citations

14.

Swaminathan, Karthik, et al.. (2014). Modeling steep slope devices: From circuits to architectures. Design, Automation & Test in Europe Conference & Exhibition (DATE), 2014. 1–6. 5 indexed citations

15.

Kontorinis, Vasileios, et al.. (2012). Battery Provisioning and Associated Costs for Data Center Power Capping. eScholarship (California Digital Library). 7 indexed citations

16.

Kontorinis, Vasileios, Barış Akşanlı, Jack Sampson, et al.. (2012). Managing distributed UPS energy for effective power capping in data centers. 104 indexed citations

17.

Venkatesh, Ganesh, et al.. (2011). Quasi-ASICs: Trading Area for Energy by Exploiting Similarity in Synthesized Cores for Irregular Code. eScholarship (California Digital Library).

18.

Venkatesh, Ganesh, et al.. (2011). QsCores. 163–174. 99 indexed citations

19.

Narayanasamy, Satish, Ganesh Venkatesh, Jack Sampson, et al.. (2006). Unbounded page-based transactional memory. 347–358. 81 indexed citations

20.

Sampson, Jack, et al.. (2005). Fast synchronization for chip multiprocessors. ACM SIGARCH Computer Architecture News. 33(4). 64–69. 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.

Explore authors with similar magnitude of impact