Lifan Xu

984 total citations · 1 hit paper
8 papers, 652 citations indexed

About

Lifan Xu is a scholar working on Computer Networks and Communications, Hardware and Architecture and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lifan Xu has authored 8 papers receiving a total of 652 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Networks and Communications, 3 papers in Hardware and Architecture and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lifan Xu's work include Parallel Computing and Optimization Techniques (3 papers), Advanced Memory and Neural Computing (2 papers) and Network Security and Intrusion Detection (2 papers). Lifan Xu is often cited by papers focused on Parallel Computing and Optimization Techniques (3 papers), Advanced Memory and Neural Computing (2 papers) and Network Security and Intrusion Detection (2 papers). Lifan Xu collaborates with scholars based in United States, Greece and Canada. Lifan Xu's co-authors include John Cavazos, Robert Searles, Nuwan Jayasena, Joseph L. Greathouse, Michael Ignatowski, Alexander Lyashevsky, Michela Taufer, Dong Ping Zhang, Marco Álvarez and Markos A. Katsoulakis and has published in prestigious journals such as PLoS ONE and Journal of Computational Physics.

In The Last Decade

Lifan Xu

8 papers receiving 634 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.

Auto-tuning a high-level language targeted to GPU codes

2012 339 citations Lifan Xu, Robert Searles et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lifan Xu United States	8	500	463	177	141	72	8	652
Hari Angepat United States	9	475 0.9×	453 1.0×	165 0.9×	149 1.1×	69 1.0×	14	654
Daniel Lustig United States	16	744 1.5×	647 1.4×	145 0.8×	227 1.6×	145 2.0×	35	872
Subarno Banerjee United States	4	306 0.6×	313 0.7×	115 0.6×	148 1.0×	92 1.3×	10	523
Kyle Spafford United States	7	574 1.1×	551 1.2×	97 0.5×	207 1.5×	69 1.0×	10	706
Perhaad Mistry United States	10	482 1.0×	439 0.9×	178 1.0×	87 0.6×	52 0.7×	18	648
Jeffrey Stuecheli United States	14	652 1.3×	637 1.4×	264 1.5×	143 1.0×	65 0.9×	17	808
Jingfei Kong United States	9	338 0.7×	324 0.7×	90 0.5×	81 0.6×	149 2.1×	12	502
Omer Khan United States	15	537 1.1×	445 1.0×	297 1.7×	96 0.7×	171 2.4×	92	788
Richard Veras United States	6	540 1.1×	419 0.9×	334 1.9×	61 0.4×	84 1.2×	11	698
Marco Vanneschi Italy	13	424 0.8×	680 1.5×	75 0.4×	223 1.6×	120 1.7×	82	790

Countries citing papers authored by Lifan Xu

Since Specialization

Citations

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

Fields of papers citing papers by Lifan Xu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lifan Xu

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

8 of 8 papers shown

1.

Searles, Robert, Lifan Xu, William Killian, et al.. (2017). Parallelization of Machine Learning Applied to Call Graphs of Binaries for Malware Detection. 69–77. 15 indexed citations

2.

Xu, Lifan, et al.. (2016). Dynamic Android Malware Classification Using Graph-Based Representations. 220–231. 18 indexed citations

3.

Xu, Lifan, Dong Ping Zhang, & Nuwan Jayasena. (2015). Scaling Deep Learning on Multiple In-Memory Processors. 11 indexed citations

4.

Wang, Wei, Lifan Xu, John Cavazos, H. Howie Huang, & Matthew W. Kay. (2014). Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators. PLoS ONE. 9(1). e86484–e86484. 12 indexed citations

5.

Jayasena, Nuwan, et al.. (2014). TOP-PIM. 85–98. 232 indexed citations

6.

Katsoulakis, Markos A., et al.. (2012). Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms. Journal of Computational Physics. 231(23). 7795–7814. 14 indexed citations

7.

Xu, Lifan, et al.. (2012). Auto-tuning a high-level language targeted to GPU codes. 1–10. 339 indexed citations breakdown →

8.

Xu, Lifan, et al.. (2010). Parallelization of tau-leap coarse-grained Monte Carlo simulations on GPUs. 1–9. 11 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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