Tze Meng Low

908 total citations
38 papers, 464 citations indexed

About

Tze Meng Low is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Tze Meng Low has authored 38 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Hardware and Architecture, 15 papers in Computer Networks and Communications and 13 papers in Computational Theory and Mathematics. Recurrent topics in Tze Meng Low's work include Parallel Computing and Optimization Techniques (20 papers), Graph Theory and Algorithms (9 papers) and Advanced Data Storage Technologies (7 papers). Tze Meng Low is often cited by papers focused on Parallel Computing and Optimization Techniques (20 papers), Graph Theory and Algorithms (9 papers) and Advanced Data Storage Technologies (7 papers). Tze Meng Low collaborates with scholars based in United States, Spain and Greece. Tze Meng Low's co-authors include Franz Franchetti, Enrique S. Quintana–Ort́ı, Francisco D. Igual, Tyler Smith, James C. Hoe, Robert A. Geijn, Field G. Zee, Daniele G. Spampinato, Larry Pileggi and Jeremy Johnson and has published in prestigious journals such as Proceedings of the IEEE, SIAM Journal on Scientific Computing and Molecular Ecology Resources.

In The Last Decade

Tze Meng Low

35 papers receiving 444 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tze Meng Low United States	11	276	186	145	101	76	38	464
Jiawei Hong United States	10	235 0.9×	310 1.7×	152 1.0×	53 0.5×	182 2.4×	27	525
Riyadh Baghdadi United States	9	235 0.9×	122 0.7×	148 1.0×	187 1.9×	17 0.2×	21	431
Sergio Barrachina Spain	12	135 0.5×	94 0.5×	256 1.8×	103 1.0×	60 0.8×	44	534
Gabriel Weisz United States	8	249 0.9×	185 1.0×	154 1.1×	206 2.0×	13 0.2×	11	503
Daniele G. Spampinato Switzerland	10	173 0.6×	114 0.6×	86 0.6×	75 0.7×	57 0.8×	20	328
Vinod Grover United States	15	488 1.8×	345 1.9×	145 1.0×	70 0.7×	51 0.7×	25	579
Kishore Kothapalli India	14	217 0.8×	416 2.2×	191 1.3×	197 2.0×	147 1.9×	76	665
Arch D. Robison United States	8	231 0.8×	219 1.2×	74 0.5×	33 0.3×	58 0.8×	18	424
Isaac D. Scherson United States	13	226 0.8×	421 2.3×	95 0.7×	53 0.5×	98 1.3×	86	579
Emanuele Del Sozzo Italy	12	202 0.7×	104 0.6×	110 0.8×	94 0.9×	25 0.3×	43	372

Countries citing papers authored by Tze Meng Low

Since Specialization

Citations

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

Fields of papers citing papers by Tze Meng Low

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tze Meng Low. 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 Tze Meng Low. The network helps show where Tze Meng Low may publish in the future.

Co-authorship network of co-authors of Tze Meng Low

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

All Works

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20 of 20 papers shown

Low, Tze Meng, et al.. (2025). FATHOM: Fast Attention Through Optimizing Memory. 1166–1178.

Low, Tze Meng, et al.. (2023). Exploiting Fusion Opportunities in Linear Algebraic Graph Query Engines. 8. 1–7.

Barrachina, Sergio, Adrián Castelló, Manuel F. Dolz, et al.. (2022). Reformulating the direct convolution for high-performance deep learning inference on ARM processors. Journal of Systems Architecture. 135. 102806–102806. 11 indexed citations

Low, Tze Meng, et al.. (2021). quickLD: An efficient software for linkage disequilibrium analyses. Molecular Ecology Resources. 21(7). 2580–2587. 10 indexed citations

Schatz, Martin, et al.. (2020). A Flexible Framework for Multidimensional DFTs. SIAM Journal on Scientific Computing. 42(5). C245–C264. 4 indexed citations

Alachiotis, Nikolaos, et al.. (2020). qLD: High-performance Computation of Linkage Disequilibrium on CPU and GPU. University of Twente Research Information. 65–72. 3 indexed citations

Spampinato, Daniele G., et al.. (2019). Delta-Stepping SSSP: From Vertices and Edges to GraphBLAS Implementations. arXiv (Cornell University). 241–250. 6 indexed citations

Low, Tze Meng, et al.. (2019). Efficient SpMV Operation for Large and Highly Sparse Matrices using Scalable Multi-way Merge Parallelization. 347–358. 54 indexed citations

Zhang, Jiyuan, Franz Franchetti, & Tze Meng Low. (2018). High Performance Zero-Memory Overhead Direct Convolutions. International Conference on Machine Learning. 5771–5780. 7 indexed citations

10.

McMillan, Scott, et al.. (2018). PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV. 1–7. 12 indexed citations

11.

Franchetti, Franz, Tze Meng Low, Richard Veras, et al.. (2018). SPIRAL: Extreme Performance Portability. Proceedings of the IEEE. 106(11). 1935–1968. 48 indexed citations

12.

Jeong, Haewon, Tze Meng Low, & Pulkit Grover. (2018). Masterless Coded Computing: A Fully-Distributed Coded FFT Algorithm. 887–894. 10 indexed citations

13.

Zee, Field G., Tyler Smith, Bryan Marker, et al.. (2016). The BLIS Framework. ACM Transactions on Mathematical Software. 42(2). 1–19. 51 indexed citations

14.

Low, Tze Meng, Francisco D. Igual, Tyler Smith, & Enrique S. Quintana–Ort́ı. (2016). Analytical Modeling Is Enough for High-Performance BLIS. ACM Transactions on Mathematical Software. 43(2). 1–18. 87 indexed citations

15.

Alachiotis, Nikolaos, et al.. (2016). Efficient Computation of Linkage Disequilibria as Dense Linear Algebra Operations. 418–427. 9 indexed citations

16.

Veras, Richard, Tze Meng Low, & Franz Franchetti. (2016). A scale-free structure for power-law graphs. 11. 1–7. 2 indexed citations

17.

Veras, Richard, et al.. (2016). Compilers, hands-off my hands-on optimizations. 1–8. 1 indexed citations

18.

Low, Tze Meng. (2013). A calculus of loop invariants for dense linear algebra optimization. Texas ScholarWorks (Texas Digital Library). 1 indexed citations

19.

Zee, Field G., Paolo Bientinesi, Tze Meng Low, & Robert A. Geijn. (2008). Scalable parallelization of FLAME code via the workqueuing model. ACM Transactions on Mathematical Software. 34(2). 1–29. 14 indexed citations

20.

Low, Tze Meng, et al.. (2006). Accumulating Householder transformations, revisited. ACM Transactions on Mathematical Software. 32(2). 169–179. 22 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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