Michael Wu

2.4k total citations · 1 hit paper
47 papers, 1.7k citations indexed

About

Michael Wu is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Hardware and Architecture. According to data from OpenAlex, Michael Wu has authored 47 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Electrical and Electronic Engineering, 34 papers in Computer Networks and Communications and 5 papers in Hardware and Architecture. Recurrent topics in Michael Wu's work include Advanced Wireless Communication Techniques (26 papers), Error Correcting Code Techniques (16 papers) and Advanced MIMO Systems Optimization (13 papers). Michael Wu is often cited by papers focused on Advanced Wireless Communication Techniques (26 papers), Error Correcting Code Techniques (16 papers) and Advanced MIMO Systems Optimization (13 papers). Michael Wu collaborates with scholars based in United States, Netherlands and Switzerland. Michael Wu's co-authors include Joseph R. Cavallaro, Willy Zwaenepoel, Christoph Studer, Bei Yin, Chris Dick, Guohui Wang, Yang Sun, Guohui Wang, Aida Vosoughi and Blaine Rister and has published in prestigious journals such as IEEE Transactions on Signal Processing, Remote Sensing and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Michael Wu

47 papers receiving 1.6k citations

Hit Papers

Large-Scale MIMO Detection for 3GPP LTE: Algorithms and F... 2014 2026 2018 2022 2014 100 200 300
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.

  1. Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations
    2014 306 citations Michael Wu, Bei Yin et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Wu United States 19 1.1k 1.1k 336 159 112 47 1.7k
Mario Porrmann Germany 22 935 0.9× 640 0.6× 856 2.5× 259 1.6× 82 0.7× 175 1.7k
N. Felber Switzerland 20 829 0.8× 556 0.5× 210 0.6× 276 1.7× 33 0.3× 62 1.3k
Gerald E. Sobelman United States 19 815 0.7× 386 0.4× 308 0.9× 106 0.7× 55 0.5× 139 1.1k
Jianhao Hu China 18 891 0.8× 580 0.5× 68 0.2× 223 1.4× 139 1.2× 146 1.3k
Peter Athanas United States 16 457 0.4× 469 0.4× 623 1.9× 167 1.1× 38 0.3× 94 1.0k
Ahmed Louri United States 25 1.6k 1.4× 1.0k 0.9× 590 1.8× 359 2.3× 27 0.2× 191 2.1k
Greg Stitt United States 22 497 0.5× 947 0.9× 1.3k 4.0× 145 0.9× 29 0.3× 104 1.6k
Frank Hannig Germany 16 333 0.3× 532 0.5× 807 2.4× 95 0.6× 38 0.3× 162 1.2k
J. Kahle United States 7 497 0.5× 705 0.6× 846 2.5× 106 0.7× 16 0.1× 10 1.3k
Ian Kuon Canada 13 1.2k 1.1× 496 0.5× 1.2k 3.5× 160 1.0× 23 0.2× 14 1.8k

Countries citing papers authored by Michael Wu

Since Specialization
Citations

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

Fields of papers citing papers by Michael Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Wu

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

All Works

20 of 20 papers shown
1.
Merello, Manuel, et al.. (2025). ForestSplat: Proof-of-Concept for a Scalable and High-Fidelity Forestry Mapping Tool Using 3D Gaussian Splatting. Remote Sensing. 17(6). 993–993. 2 indexed citations
2.
Wu, Michael, et al.. (2024). Characterizing Emerging Page Replacement Policies for Memory-Intensive Applications. 284–294. 2 indexed citations
3.
Wu, Michael, et al.. (2023). HALO: A Hardware–Software Co-Designed Processor for Brain–Computer Interfaces. IEEE Micro. 43(3). 64–72. 4 indexed citations
4.
Wu, Michael, et al.. (2023). Prefetching Using Principles of Hippocampal-Neocortical Interaction. 53–60. 1 indexed citations
5.
Wu, Michael, et al.. (2020). Hardware-Software Co-Design for Brain-Computer Interfaces. 391–404. 17 indexed citations
6.
Wu, Michael, Bei Yin, Kaipeng Li, et al.. (2017). Implicit vs. Explicit Approximate Matrix Inversion for Wideband Massive MU-MIMO Data Detection. Journal of Signal Processing Systems. 90(10). 1311–1328. 16 indexed citations
7.
Wu, Michael, Chris Dick, Joseph R. Cavallaro, & Christoph Studer. (2016). FPGA design of a coordinate descent data detector for large-scale MU-MIMO. Repository for Publications and Research Data (ETH Zurich). 1894–1897. 23 indexed citations
8.
Cheng, Albert M. K., et al.. (2015). Scheduling Mixed-Criticality Real-Time Tasks in a Fault-Tolerant System. RePEc: Research Papers in Economics. 6(2). 65–86. 13 indexed citations
9.
Yin, Bei, Michael Wu, Joseph R. Cavallaro, & Christoph Studer. (2015). VLSI design of large-scale soft-output MIMO detection using conjugate gradients. 1498–1501. 53 indexed citations
10.
Yin, Bei, Michael Wu, Guohui Wang, et al.. (2014). A 3.8Gb/s large-scale MIMO detector for 3GPP LTE-Advanced. 3879–3883. 43 indexed citations
11.
12.
Wu, Michael, Guohui Wang, Bei Yin, Christoph Studer, & Joseph R. Cavallaro. (2013). HSPA&#x003B;/LTE-A turbo decoder on GPU and multicore CPU. 3. 824–828. 10 indexed citations
13.
Wu, Michael, Bei Yin, Aida Vosoughi, et al.. (2013). Approximate matrix inversion for high-throughput data detection in the large-scale MIMO uplink. Rice Digital Scholarship Archive (Rice University). 2155–2158. 119 indexed citations
14.
Rister, Blaine, Guohui Wang, Michael Wu, & Joseph R. Cavallaro. (2013). A fast and efficient sift detector using the mobile GPU. Rice Digital Scholarship Archive (Rice University). 53 indexed citations
15.
Wu, Michael, Bei Yin, & Joseph R. Cavallaro. (2012). Flexible N-Way MIMO Detector on GPU. Rice Digital Scholarship Archive (Rice University). 3. 318–323. 5 indexed citations
16.
Wang, Guohui, et al.. (2011). A massively parallel implementation of QC-LDPC decoder on GPU. Rice Digital Scholarship Archive (Rice University). 7810. 82–85. 34 indexed citations
17.
Wu, Michael, Yang Sun, & Joseph R. Cavallaro. (2010). Implementation of a 3GPP LTE turbo decoder accelerator on GPU. Rice Digital Scholarship Archive (Rice University). 15. 192–197. 27 indexed citations
18.
Wu, Michael, et al.. (2010). Physical layer algorithm and hardware verification of MIMO relays using cooperative partial detection. Rice Digital Scholarship Archive (Rice University). 5614–5617. 4 indexed citations
19.
Wu, Michael & Willy Zwaenepoel. (1994). eNVy. 86–97. 188 indexed citations
20.
Wu, Michael & Willy Zwaenepoel. (1994). eNVy. ACM SIGOPS Operating Systems Review. 28(5). 86–97. 13 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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