Pierre Baldi

2.3k total citations · 1 hit paper
12 papers, 1.8k citations indexed

About

Pierre Baldi is a scholar working on Molecular Biology, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Pierre Baldi has authored 12 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Artificial Intelligence and 2 papers in Aerospace Engineering. Recurrent topics in Pierre Baldi's work include Antenna Design and Optimization (2 papers), RNA and protein synthesis mechanisms (2 papers) and Radio Astronomy Observations and Technology (1 paper). Pierre Baldi is often cited by papers focused on Antenna Design and Optimization (2 papers), RNA and protein synthesis mechanisms (2 papers) and Radio Astronomy Observations and Technology (1 paper). Pierre Baldi collaborates with scholars based in United States, Israel and Austria. Pierre Baldi's co-authors include Stephen McAleer, Siyu Shao, Ruqiang Yan, Karin Flick, Lan Huang, Yimeng Dou, Bernhard Auer, Peter Kaiser, Meng Cui and Christian Tagwerker and has published in prestigious journals such as Nature, Bioinformatics and IEEE Transactions on Medical Imaging.

In The Last Decade

Pierre Baldi

9 papers receiving 1.7k citations

Hit Papers

Highly Accurate Machine Fault Diagnosis Using Deep Transf... 2018 2026 2020 2023 2018 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre Baldi United States 9 945 528 373 328 292 12 1.8k
Fudong Li China 20 817 0.9× 475 0.9× 91 0.2× 362 1.1× 252 0.9× 73 1.7k
Hai‐Peng Ren China 27 646 0.7× 244 0.5× 145 0.4× 272 0.8× 18 0.1× 183 2.3k
Wuquan Deng China 11 182 0.2× 97 0.2× 113 0.3× 323 1.0× 49 0.2× 14 994
Falai Chen China 30 122 0.1× 425 0.8× 276 0.7× 53 0.2× 268 0.9× 157 3.1k
Li Liu China 17 156 0.2× 105 0.2× 95 0.3× 69 0.2× 31 0.1× 141 1.2k
William T. Baumann United States 22 508 0.5× 106 0.2× 670 1.8× 61 0.2× 34 0.1× 73 1.9k
Yangfan Li China 19 168 0.2× 91 0.2× 37 0.1× 246 0.8× 40 0.1× 73 1.2k
Hong Xia China 21 598 0.6× 166 0.3× 58 0.2× 153 0.5× 126 0.4× 99 1.1k

Countries citing papers authored by Pierre Baldi

Since Specialization
Citations

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

Fields of papers citing papers by Pierre Baldi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pierre Baldi

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

All Works

12 of 12 papers shown
1.
Lu, Di, et al.. (2025). Optimization of Antenna Array Configurations Using Deep Learning. IEEE Open Journal of Antennas and Propagation. 6(5). 1367–1374.
2.
3.
Baldi, Pierre, Piero Fariselli, & Giorgio Parisi. (2024). Build an international AI ‘telescope’ to curb the power of big tech companies. Nature. 634(8035). 782–782.
4.
Shao, Siyu, Stephen McAleer, Ruqiang Yan, & Pierre Baldi. (2018). Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning. IEEE Transactions on Industrial Informatics. 15(4). 2446–2455. 1180 indexed citations breakdown →
5.
Urban, Gregor, Duc T. T. Phan, Agua Sobrino, et al.. (2018). Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16(3). 1029–1035. 48 indexed citations
6.
Karnes, William E., Talal Alkayali, Mohit Mittal, et al.. (2017). Su1642 Automated Polyp Detection Using Deep Learning: Leveling the Field. Gastrointestinal Endoscopy. 85(5). AB376–AB377. 9 indexed citations
7.
Wang, Juan, et al.. (2017). Detecting Cardiovascular Disease from Mammograms With Deep Learning. IEEE Transactions on Medical Imaging. 36(5). 1172–1181. 160 indexed citations
8.
Randall, Arlo, et al.. (2011). Rationally selected single‐site mutants of the Thermoascus aurantiacus endoglucanase increase hydrolytic activity on cellulosic substrates. Biotechnology and Bioengineering. 109(6). 1595–1599. 14 indexed citations
9.
Baldi, Pierre, et al.. (2006). Mycobacterium tuberculosisの必須アシル‐CoAカルボキシラーゼカルボキシルトランスフェラーゼドメインAccD5の構造依存阻害剤デザイン. Proc Natl Acad Sci USA. 103(9). 3072–3077. 31 indexed citations
10.
Tagwerker, Christian, Karin Flick, Meng Cui, et al.. (2006). A Tandem Affinity Tag for Two-step Purification under Fully Denaturing Conditions. Molecular & Cellular Proteomics. 5(4). 737–748. 298 indexed citations
11.
Pollastri, Gianluca, Pierre Baldi, Piero Fariselli, & Rita Casadio. (2001). Improved prediction of the number of residue contacts in proteins by recurrent neural networks. Bioinformatics. 17(suppl_1). S234–S242. 35 indexed citations
12.
Baldi, Pierre. (2000). On the convergence of a clustering algorithm for protein-coding regions in microbial genomes. Bioinformatics. 16(4). 367–371. 12 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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