Xiaodi Wu

2.1k citations
53 papers · 1.2k · h-index 16

Impact in

  • Catalysis top 5%
    • Catalysis and Oxidation Reactions
    • Quantum Computing Algorithms and Architecture
    • Quantum Information and Cryptography

Papers in

Xiaodi Wu

50 papers receiving 1.2k citations

Peers

Xiaodi Wu
Comparison fields: 5 of 74
  • Catalysis 279
  • Artificial Intelligence 736
  • Atomic and Molecular Physics, and Optics 350
  • Computational Theory and Mathematics 165
  • Materials Chemistry 371
Replace Keisuke Tanaka with:
Keisuke Tanaka Japan
Joonwoo Bae South Korea
Maho Nakata Japan
Shiyu Wang China
JJ Johan Lukkien Netherlands
Yingzhou Li United States
Elena V. Konstantinova Russia
Franziska Biegler Germany
Xiaodi Wu relative to Keisuke Tanaka Japan Keisuke Tanaka's profile →
Citations per field
00.5×2×3.2×
Keisuke Tanaka · 1×
Citations per year

Countries citing papers authored by Xiaodi Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodi Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaodi Wu, 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 Xiaodi Wu Line = papers co-authored together Xiaodi Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007221
2 2020182
3 2017130
4 202179
5 200771
6 201666
7 202460
8 200755
9 201934
10 201828
11
Quantitative robustness analysis of quantum programs
201923
12 201122
13 202021
14 202320
15 201719
16 201618
17 202415
18 200814
19 202212
20 201712

About Xiaodi Wu

Xiaodi Wu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics, Catalysis and Hardware and Architecture, having authored 53 papers that have together received 1.2k indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (37 papers), Quantum Information and Cryptography (26 papers), Quantum Mechanics and Applications (10 papers), Computability, Logic, AI Algorithms (9 papers), Catalytic Processes in Materials Science (4 papers), Stochastic Gradient Optimization Techniques (3 papers), Catalysis and Oxidation Reactions (3 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Catalysis (279 citations), Artificial Intelligence (736 citations), Atomic and Molecular Physics, and Optics (350 citations), Computational Theory and Mathematics (165 citations) and Materials Chemistry (371 citations). Xiaodi Wu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Aram W. Harrow, Duan Weng, Xiaodong Wu, Qing Liang, Jun Qin Fan, Māris Ozols, Tianyi Peng, Rui Ran, Jeongwan Haah and Nengkun Yu. Their work appears in journals such as Proceedings of the ACM on Programming Languages, Communications in Mathematical Physics, Quantum, INFORMS journal on computing and IEEE Transactions on Information Theory.

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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