Federico Monti

4.4k total citations · 2 hit papers
16 papers, 1.9k citations indexed

About

Federico Monti is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Information Systems. According to data from OpenAlex, Federico Monti has authored 16 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Molecular Biology and 3 papers in Information Systems. Recurrent topics in Federico Monti's work include Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers) and Video Surveillance and Tracking Methods (3 papers). Federico Monti is often cited by papers focused on Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers) and Video Surveillance and Tracking Methods (3 papers). Federico Monti collaborates with scholars based in Italy, Switzerland and United Kingdom. Federico Monti's co-authors include Michael M. Bronstein, Emanuele Rodolà, Davide Boscaini, Jan Svoboda, Jonathan Masci, Pablo Gaínza, Bruno E. Correia, Freyr Sverrisson, Xavier Bresson and Marco Tagliasacchi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Methods.

In The Last Decade

Federico Monti

14 papers receiving 1.8k citations

Hit Papers

align trajectories sort by overperformance

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.

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs

2017 981 citations Federico Monti, Davide Boscaini et al. IRIS Research product catalog (Sapienza University of Rome) profile →
Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

2019 449 citations Pablo Gaínza, Freyr Sverrisson et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Federico Monti Italy	8	688	651	444	269	230	16	1.9k
Davide Boscaini Italy	7	562 0.8×	711 1.1×	402 0.9×	221 0.8×	456 2.0×	20	1.8k
Christos Boutsidis United States	19	714 1.0×	535 0.8×	317 0.7×	255 0.9×	491 2.1×	28	1.7k
Emanuele Rodolà Italy	26	666 1.0×	1.8k 2.7×	420 0.9×	268 1.0×	1.2k 5.0×	82	3.2k
Jie Gui China	30	975 1.4×	2.1k 3.2×	565 1.3×	181 0.7×	274 1.2×	106	4.1k
S. V. N. Vishwanathan United States	25	2.5k 3.6×	1.4k 2.2×	575 1.3×	302 1.1×	252 1.1×	68	3.9k
Thomas Unterthiner Austria	13	814 1.2×	2.0k 3.0×	654 1.5×	854 3.2×	135 0.6×	22	3.7k
L.P. Cordella Italy	17	739 1.1×	1.2k 1.8×	159 0.4×	227 0.8×	45 0.2×	53	1.9k
Serhii Havrylov Ukraine	3	1.4k 2.1×	803 1.2×	122 0.3×	99 0.4×	64 0.3×	6	2.4k
Nicol N. Schraudolph Switzerland	22	1.4k 2.0×	541 0.8×	425 1.0×	424 1.6×	225 1.0×	45	2.5k
Chunpeng Wang China	35	362 0.5×	2.6k 4.0×	76 0.2×	564 2.1×	181 0.8×	175	4.0k

Countries citing papers authored by Federico Monti

Since Specialization

Citations

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

Fields of papers citing papers by Federico Monti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Federico Monti

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

16 of 16 papers shown

Pisani, F., K. K. Mujeeb Rahman, Federico Monti, et al.. (2025). A fiber laser source for parallel dual-window multiplex SRS (DWM-SRS): single-shot CH-stretching and fingerprint imaging. 56–56. 1 indexed citations

Pisani, F., K. K. Mujeeb Rahman, Federico Monti, et al.. (2025). A Fiber Laser Source for Parallel Dual-Window Multiplex SRS (DWM-SRS): Single-Shot Ch-Stretching and Fingerprint Imaging. 1–1.

Monti, Federico, Laura Leoni, Bernardo Stefanini, et al.. (2024). RANK–RANKL–OPG Axis in MASLD: Current Evidence Linking Bone and Liver Diseases and Future Perspectives. International Journal of Molecular Sciences. 25(17). 9193–9193. 6 indexed citations

Monti, Federico, et al.. (2022). Interaction data are identifiable even across long periods of time. Nature Communications. 13(1). 313–313. 14 indexed citations

McCloskey, Kevin, Ankur Taly, Federico Monti, Michael P. Brenner, & Lucy J. Colwell. (2019). Using attribution to decode binding mechanism in neural network models for chemistry. Proceedings of the National Academy of Sciences. 116(24). 11624–11629. 60 indexed citations

Gaínza, Pablo, Freyr Sverrisson, Federico Monti, et al.. (2019). Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning. Nature Methods. 17(2). 184–192. 449 indexed citations breakdown →

Gaínza, Pablo, Freyr Sverrisson, Federico Monti, et al.. (2019). MaSIF - Deciphering interaction fingerprints from protein molecular surfaces. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

Bruna, Joan, Federico Monti, L. Gerhardt, et al.. (2018). Graph Neural Networks for IceCube Signal Classification. 386–391. 32 indexed citations

Monti, Federico, Michael M. Bronstein, & Xavier Bresson. (2018). Deep Geometric Matrix Completion: A New Way for Recommender Systems. 6852–6856. 7 indexed citations

10.

Monti, Federico, Michael M. Bronstein, & Xavier Bresson. (2017). Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. Neural Information Processing Systems. 30. 3697–3707. 126 indexed citations

11.

Tridello, Gloria, Stefano Ceri, Marco Tagliasacchi, et al.. (2017). Ratiometric sweat secretion optical test in cystic fibrosis, carriers and healthy subjects. Journal of Cystic Fibrosis. 17(2). 186–189. 16 indexed citations

12.

Monti, Federico, Davide Boscaini, Jonathan Masci, et al.. (2017). Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs. IRIS Research product catalog (Sapienza University of Rome). 5425–5434. 981 indexed citations breakdown →

13.

Cavina, Nicolò, et al.. (2017). Application of Acoustic and Vibration-Based Knock Detection Techniques to a High Speed Engine. SAE technical papers on CD-ROM/SAE technical paper series. 1. 4 indexed citations

14.

Tomè, Denis, Federico Monti, Luca Baroffio, et al.. (2016). Deep Convolutional Neural Networks for pedestrian detection. Signal Processing Image Communication. 47. 482–489. 148 indexed citations

15.

Monti, Federico & Carlo S. Regazzoni. (2010). A joint approach to shape-based human tracking and behavior analysis. CINECA IRIS Institutial Research Information System (University of Genoa). 1–8.

16.

Monti, Federico, et al.. (2008). Feature Classification for Robust Shape-Based Collaborative Tracking and Model Updating. EURASIP Journal on Image and Video Processing. 2008. 1–21. 5 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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