Lisa Wu

1.0k total citations
16 papers, 762 citations indexed

About

Lisa Wu is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture. According to data from OpenAlex, Lisa Wu has authored 16 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Networks and Communications, 10 papers in Information Systems and 10 papers in Hardware and Architecture. Recurrent topics in Lisa Wu's work include Parallel Computing and Optimization Techniques (10 papers), Advanced Data Storage Technologies (8 papers) and Cloud Computing and Resource Management (7 papers). Lisa Wu is often cited by papers focused on Parallel Computing and Optimization Techniques (10 papers), Advanced Data Storage Technologies (8 papers) and Cloud Computing and Resource Management (7 papers). Lisa Wu collaborates with scholars based in United States. Lisa Wu's co-authors include Margaret Martonosi, Narayanan Sundaram, Nadathur Satish, Tae Jun Ham, Martha A. Kim, Kenneth A. Ross, Todd Austin, Christopher Weaver, T. Austin and Stephen A. Edwards and has published in prestigious journals such as ACM Transactions on Computer Systems, ACM SIGPLAN Notices and IEEE Micro.

In The Last Decade

Lisa Wu

16 papers receiving 729 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lisa Wu United States	10	465	431	293	264	184	16	762
Rupesh Nasre India	10	408 0.9×	345 0.8×	211 0.7×	150 0.6×	198 1.1×	49	626
Kevin Hsieh United States	14	641 1.4×	659 1.5×	141 0.5×	237 0.9×	217 1.2×	16	1.1k
Michael E. Kounavis United States	17	167 0.4×	576 1.3×	147 0.5×	319 1.2×	141 0.8×	39	900
Jacob Nelson United States	16	455 1.0×	668 1.5×	99 0.3×	126 0.5×	270 1.5×	39	973
Sreepathi Pai United States	13	453 1.0×	394 0.9×	230 0.8×	164 0.6×	216 1.2×	30	645
Gabriel Weisz United States	8	249 0.5×	185 0.4×	206 0.7×	154 0.6×	57 0.3×	11	503
Andrés Márquez United States	13	242 0.5×	242 0.6×	68 0.2×	95 0.4×	93 0.5×	45	408
Saeed Maleki United States	11	199 0.4×	201 0.5×	64 0.2×	225 0.9×	88 0.5×	23	503
Zhijia Zhao United States	12	284 0.6×	239 0.6×	174 0.6×	208 0.8×	107 0.6×	43	498
Subramanya R. Dulloor United States	9	809 1.7×	938 2.2×	210 0.7×	142 0.5×	402 2.2×	10	1.1k

Countries citing papers authored by Lisa Wu

Since Specialization

Citations

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

Fields of papers citing papers by Lisa Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lisa Wu

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

16 of 16 papers shown

1.

Wu, Lisa, Frank Austin Nothaft, Qijing Huang, et al.. (2019). FPGA Accelerated INDEL Realignment in the Cloud. 277–290. 26 indexed citations

2.

Ham, Tae Jun, Lisa Wu, Narayanan Sundaram, Nadathur Satish, & Margaret Martonosi. (2016). Graphicionado: a high-performance and energy-efficient accelerator for graph analytics. International Symposium on Microarchitecture. 1–13. 127 indexed citations

3.

Ham, Tae Jun, Lisa Wu, Narayanan Sundaram, Nadathur Satish, & Margaret Martonosi. (2016). Graphicionado: A high-performance and energy-efficient accelerator for graph analytics. 1–13. 221 indexed citations

4.

Wu, Lisa, et al.. (2015). The Q100 Database Processing Unit. IEEE Micro. 35(3). 34–46. 18 indexed citations

5.

Wu, Lisa, et al.. (2014). Q100. ACM SIGPLAN Notices. 49(4). 255–268. 7 indexed citations

6.

Wu, Lisa, et al.. (2014). Q100. 255–268. 120 indexed citations

7.

Wu, Lisa, et al.. (2014). Hardware Partitioning for Big Data Analytics. IEEE Micro. 34(3). 109–119. 6 indexed citations

8.

Wu, Lisa, et al.. (2014). Energy Analysis of Hardware and Software Range Partitioning. ACM Transactions on Computer Systems. 32(3). 1–24. 7 indexed citations

9.

Wu, Lisa, et al.. (2014). Q100. ACM SIGARCH Computer Architecture News. 42(1). 255–268. 11 indexed citations

10.

Wu, Lisa, et al.. (2013). Navigating big data with high-throughput, energy-efficient data partitioning. 249–260. 74 indexed citations

11.

Wu, Lisa, et al.. (2013). Navigating big data with high-throughput, energy-efficient data partitioning. ACM SIGARCH Computer Architecture News. 41(3). 249–260. 11 indexed citations

12.

Wu, Lisa, Martha A. Kim, & Stephen A. Edwards. (2011). Cache Impacts of Datatype Acceleration. IEEE Computer Architecture Letters. 11(1). 21–24. 5 indexed citations

13.

Wu, Lisa, Christopher Weaver, & T. Austin. (2002). CryptoManiac: a fast flexible architecture for secure communication. 110–119. 30 indexed citations

14.

Wu, Lisa, et al.. (2001). CryptoManiac. 110–119. 89 indexed citations

15.

Wu, Lisa, et al.. (2001). Application specific architectures. 181–181. 2 indexed citations

16.

Wu, Lisa, et al.. (2001). CryptoManiac. ACM SIGARCH Computer Architecture News. 29(2). 110–119. 8 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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