Lixue Xia

2.7k citations
45 papers · 2.1k · h-index 27

Impact in

Papers in

Lixue Xia

45 papers receiving 2.1k citations

Peers

Lixue Xia
Comparison fields: 5 of 60
  • Electrical and Electronic Engineering 1.9k
  • Cellular and Molecular Neuroscience 434
  • Hardware and Architecture 145
  • Computer Vision and Pattern Recognition 407
  • Artificial Intelligence 543
Replace Shihui Yin with:
Shihui Yin United States
Kailash Gopalakrishnan United States
Anirban Nag United States
Win-San Khwa Taiwan
Priyanka Raina United States
Ren-Shuo Liu Taiwan
Ping Chi United States
Zhenhua Zhu China
Pallab Datta United States
Aayush Ankit United States
Lixue Xia relative to Shihui Yin United States Shihui Yin's profile →
Citations per field
00.5×10×14.5×
Shihui Yin · 1×
Citations per year

Countries citing papers authored by Lixue Xia

Since Specialization
Citations

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

Fields of papers citing papers by Lixue Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lixue Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lixue Xia Line = papers co-authored together Lixue Xia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015188
2 2016140
3 2017139
4 2017133
5 2017126
6 2017121
7 2021121
8 201797
9 201687
10 201580
11 201968
12 202057
13 201657
14 201856
15 201754
16 201953
17 201845
18 201544
19 201844
20 201741

About Lixue Xia

Lixue Xia is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Cellular and Molecular Neuroscience, Artificial Intelligence and Cognitive Neuroscience, having authored 45 papers that have together received 2.1k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (40 papers), Ferroelectric and Negative Capacitance Devices (35 papers), Advanced Neural Network Applications (10 papers), Neuroscience and Neural Engineering (7 papers), CCD and CMOS Imaging Sensors (7 papers), Machine Learning and ELM (6 papers), Neural dynamics and brain function (5 papers) and Semiconductor materials and devices (4 papers). The work is most often cited by research in Electrical and Electronic Engineering (1.9k citations), Cellular and Molecular Neuroscience (434 citations), Hardware and Architecture (145 citations), Computer Vision and Pattern Recognition (407 citations) and Artificial Intelligence (543 citations). Lixue Xia has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yu Wang, Huazhong Yang, Tianqi Tang, Boxun Li, Yuan Xie, Krishnendu Chakrabarty, Yu Cao, Shimeng Yu, Ming Cheng and Mengyun Liu. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Batteries, ACM Transactions on Design Automation of Electronic Systems, IEEE Journal on Emerging and Selected Topics in Circuits and Systems and Journal of Computer Science and Technology.

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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