M.L. Crespo

5.9k total citations
69 papers, 439 citations indexed

About

M.L. Crespo is a scholar working on Nuclear and High Energy Physics, Radiation and Electrical and Electronic Engineering. According to data from OpenAlex, M.L. Crespo has authored 69 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Nuclear and High Energy Physics, 20 papers in Radiation and 20 papers in Electrical and Electronic Engineering. Recurrent topics in M.L. Crespo's work include Particle Detector Development and Performance (20 papers), Radiation Detection and Scintillator Technologies (14 papers) and CCD and CMOS Imaging Sensors (9 papers). M.L. Crespo is often cited by papers focused on Particle Detector Development and Performance (20 papers), Radiation Detection and Scintillator Technologies (14 papers) and CCD and CMOS Imaging Sensors (9 papers). M.L. Crespo collaborates with scholars based in Italy, Argentina and Malaysia. M.L. Crespo's co-authors include A. Cicuttin, Jeong–A Lee, Mamun Bin Ibne Reaz, Claudio Tuniz, Mohammad Arif Sobhan Bhuiyan, Giovanni Ramponi, Verónica Gil-Costa, Clément Zanolli, Sergio Carrato and Muhammad E. H. Chowdhury and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

M.L. Crespo

59 papers receiving 417 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M.L. Crespo Italy 11 118 87 67 58 38 69 439
A. Cicuttin Italy 11 103 0.9× 90 1.0× 67 1.0× 59 1.0× 37 1.0× 60 375
H. Vogt Germany 16 444 3.8× 138 1.6× 14 0.2× 163 2.8× 2 0.1× 120 863
Edward A. Martin United States 7 52 0.4× 11 0.1× 3 0.0× 26 0.4× 10 0.3× 12 334
Caiwen Ma China 13 68 0.6× 58 0.7× 80 1.2× 5 0.1× 3 0.1× 75 535
Michał Niedźwiecki Poland 8 24 0.2× 44 0.5× 5 0.1× 48 0.8× 5 0.1× 27 281
A. Razdan United States 13 75 0.6× 36 0.4× 7 0.1× 2 0.0× 30 0.8× 33 566
M.J. Bellido Spain 9 107 0.9× 11 0.1× 33 0.5× 10 0.2× 48 437
Ilia V. Safonov Russia 10 18 0.2× 56 0.6× 9 0.1× 30 0.5× 1 0.0× 55 457
Mitchell J. Myjak United States 11 127 1.1× 59 0.7× 96 1.4× 21 0.4× 43 407
Imants Svalbe Australia 15 31 0.3× 57 0.7× 187 2.8× 5 0.1× 3 0.1× 63 748

Countries citing papers authored by M.L. Crespo

Since Specialization
Citations

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

Fields of papers citing papers by M.L. Crespo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.L. Crespo. 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 M.L. Crespo. The network helps show where M.L. Crespo may publish in the future.

Co-authorship network of co-authors of M.L. Crespo

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

All Works

20 of 20 papers shown
1.
2.
Reaz, Mamun Bin Ibne, Sawal Hamid Md Ali, M.L. Crespo, et al.. (2025). Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach. Artificial Intelligence in Medicine. 166. 103153–103153. 2 indexed citations
3.
Crespo, M.L., A. Cicuttin, S. Levorato, et al.. (2024). A SoC-FPGA based readout platform for the free-running AMBER data acquisition system. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1066. 169546–169546. 1 indexed citations
4.
Bogovać, M., et al.. (2024). Gamma/Neutron Online Discrimination Based on Machine Learning With CLYC Detectors. IEEE Transactions on Nuclear Science. 71(12). 2602–2614.
5.
Lee, Jeong–A, et al.. (2024). Real-time object detection, tracking, and monitoring framework for security surveillance systems. Heliyon. 10(15). e34922–e34922. 16 indexed citations
6.
Reaz, Mamun Bin Ibne, M.L. Crespo, A. Cicuttin, et al.. (2024). A Versatile and Wireless Multichannel Capacitive EMG Measurement System for Digital Healthcare. IEEE Internet of Things Journal. 11(11). 20120–20137. 2 indexed citations
7.
Bressan, A., Sergio Carrato, C. Chatterjee, et al.. (2023). The high voltage system the novel MPGD-based photon detectors ofCOMPASS RICH-1 and its development towards a scalable HVPSS forMPGDs. Journal of Instrumentation. 18(7). C07014–C07014. 1 indexed citations
8.
Brunbauer, F., C. Chatterjee, G. Cicala, et al.. (2023). Progress in coupling MPGD-based photon detectors with nanodiamond photocathodes. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1056. 168575–168575.
9.
Reaz, Mamun Bin Ibne, M.L. Crespo, A. Cicuttin, et al.. (2023). A Flexible Capacitive Electromyography Biomedical Sensor for Wearable Healthcare Applications. IEEE Transactions on Instrumentation and Measurement. 72. 1–13. 13 indexed citations
10.
Reaz, Mamun Bin Ibne, Sawal Hamid Md Ali, M.L. Crespo, et al.. (2023). Machine Learning Algorithms for Predicting the Risk of Chronic Kidney Disease in Type 1 Diabetes Patients: A Retrospective Longitudinal Study. SSRN Electronic Journal.
11.
Reaz, Mamun Bin Ibne, Sawal Hamid Md Ali, Shamim Ahmad, et al.. (2022). Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data. Journal of Personalized Medicine. 12(9). 1507–1507. 7 indexed citations
12.
13.
Cicuttin, A., et al.. (2022). A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition. Sensors. 22(20). 7697–7697. 7 indexed citations
14.
Crespo, M.L., et al.. (2022). Data Analysis and Filter Optimization for Pulse-Amplitude Measurement: A Case Study on High-Resolution X-ray Spectroscopy. Sensors. 22(13). 4776–4776. 2 indexed citations
15.
Cicuttin, A., et al.. (2022). Looking for suitable rules for true random number generation with asynchronous cellular automata. Nonlinear Dynamics. 111(3). 2711–2722. 2 indexed citations
16.
Crespo, M.L., et al.. (2021). Remote Laboratory for E-Learning of Systems on Chip and Their Applications to Nuclear and Scientific Instrumentation. Electronics. 10(18). 2191–2191. 7 indexed citations
17.
Crespo, M.L., et al.. (2021). Muon–Electron Pulse Shape Discrimination for Water Cherenkov Detectors Based on FPGA/SoC. Electronics. 10(3). 224–224. 6 indexed citations
18.
Dasgupta, S., J. Agarwala, C.D.R. Azevedo, et al.. (2020). A modular mini-pad photon detector prototype for RICH application at the Electron Ion Collider. CERN Document Server (European Organization for Nuclear Research).
19.
20.
Kavka, Carlos & M.L. Crespo. (1998). Robot arm fuzzy control by a neuro-genetic algorithm. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).

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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