J. Ngadiuba

58.7k total citations
19 papers, 252 citations indexed

About

J. Ngadiuba is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Radiation. According to data from OpenAlex, J. Ngadiuba has authored 19 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Nuclear and High Energy Physics, 8 papers in Artificial Intelligence and 4 papers in Radiation. Recurrent topics in J. Ngadiuba's work include Particle physics theoretical and experimental studies (12 papers), Particle Detector Development and Performance (8 papers) and Radiation Detection and Scintillator Technologies (4 papers). J. Ngadiuba is often cited by papers focused on Particle physics theoretical and experimental studies (12 papers), Particle Detector Development and Performance (8 papers) and Radiation Detection and Scintillator Technologies (4 papers). J. Ngadiuba collaborates with scholars based in United States, Switzerland and Serbia. J. Ngadiuba's co-authors include M. Pierini, Vladimir Lončar, J. Duarte, T. K. Aarrestad, S. Summers, Z. Wu, Duc Hoang, Dylan Rankin, Giuseppe Di Guglielmo and Ekaterina Govorkova and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and Scientific Data.

In The Last Decade

J. Ngadiuba

19 papers receiving 249 citations

Peers

J. Ngadiuba

NHEP

CVPR

EEE

S. Summers Switzerland

Zijian Zhao China

U. Fuchs Switzerland

Róbert Lórencz Czechia

Enrico Calore Italy

Roger Labahn Germany

Lazaros Papadopoulos Greece

Ali J. Abboud Iraq

Aimin Yu China

K. Schossmaier Switzerland

S. Summers Switzerland

J. Ngadiuba

52 ×0.4

NHEP

63 ×0.6

44 ×0.8

CVPR

37 ×0.8

EEE

19 ×0.7

Citations per year, relative to J. Ngadiuba J. Ngadiuba (= 1×) peers S. Summers

Countries citing papers authored by J. Ngadiuba

Since Specialization

Citations

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

Fields of papers citing papers by J. Ngadiuba

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Ngadiuba

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

19 of 19 papers shown

Ngadiuba, J., et al.. (2025). Fast jet tagging with MLP-Mixers on FPGAs. Machine Learning Science and Technology. 6(3). 35025–35025. 1 indexed citations

Que, Zhiqiang, J. Duarte, J. Haller, et al.. (2024). Ultrafast jet classification at the HL-LHC. Machine Learning Science and Technology. 5(3). 35017–35017. 6 indexed citations

Gandrakota, A., et al.. (2024). Robust anomaly detection for particle physics using multi-background representation learning. Machine Learning Science and Technology. 5(3). 35082–35082. 2 indexed citations

Baldi, Tommaso Lisini, J. Ngadiuba, Nhan Viet Tran, et al.. (2024). Reliable edge machine learning hardware for scientific applications. eScholarship (California Digital Library). 1–5. 1 indexed citations

Que, Zhiqiang, J. Duarte, J. Haller, et al.. (2024). Ultrafast jet classification at the HL-LHC. Repository for Publications and Research Data (ETH Zurich). 3 indexed citations

Govorkova, Ekaterina, T. K. Aarrestad, Vladimir Lončar, et al.. (2022). Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. Nature Machine Intelligence. 4(2). 154–161. 50 indexed citations

Govorkova, Ekaterina, T. K. Aarrestad, Vladimir Lončar, et al.. (2022). Author Correction: Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. Nature Machine Intelligence. 4(4). 414–414. 1 indexed citations

Govorkova, Ekaterina, et al.. (2022). LHC physics dataset for unsupervised New Physics detection at 40 MHz. Scientific Data. 9(1). 118–118. 20 indexed citations

Lončar, Vladimir, M. Pierini, S. Summers, et al.. (2022). Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. Machine Learning Science and Technology. 3(4). 45011–45011. 17 indexed citations

10.

Jawahar, Pratik, T. K. Aarrestad, N. Chernyavskaya, et al.. (2022). Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows. Frontiers in Big Data. 5. 803685–803685. 19 indexed citations

11.

Aarrestad, T. K., et al.. (2021). Jet Single Shot Detection. SHILAP Revista de lepidopterología. 251. 4027–4027. 1 indexed citations

12.

Zhuang, Hao, T. K. Aarrestad, Vladimir Lončar, et al.. (2020). Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml. arXiv (Cornell University). 15 indexed citations

13.

Ngadiuba, J., Vladimir Lončar, M. Pierini, et al.. (2020). Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML. DSpace@MIT (Massachusetts Institute of Technology). 44 indexed citations

14.

Guglielmo, Giuseppe Di, J. Duarte, P. Harris, et al.. (2020). Fast inference of Boosted Decision Trees in FPGAs for particle physics. Journal of Instrumentation. 15(5). P05026–P05026. 50 indexed citations

15.

Wozniak, K. A., Olmo Cerri, J. Duarte, et al.. (2020). New Physics Agnostic Selections For New Physics Searches. SHILAP Revista de lepidopterología. 245. 6039–6039. 3 indexed citations

16.

Duarte, J., Song Han, Philip Harris, et al.. (2019). Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. 305–305. 5 indexed citations

17.

Kilminster, B., L. Caminada, S. Donato, et al.. (2018). Measurements of $t\overline{t}$ cross sections in association with b jets and inclusive jets and their ratio using dilepton final states in pp collisions at $\sqrt{s}$ = 13 TeV. Zurich Open Repository and Archive (University of Zurich). 2 indexed citations

18.

Kilminster, B., L. Caminada, S. Donato, et al.. (2017). A search for new phenomena in pp collisions at $\sqrt {s} = 13$ TeV in final states with missing transverse momentum and at least one jet using the $α_{T}$ variable. The European Physical Journal C. 294. 1 indexed citations

19.

Lei, C. M., D. Menasce, L. Moroni, et al.. (2015). The pixel tracking telescope at the Fermilab Test Beam Facility. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 811. 162–169. 11 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.

Explore authors with similar magnitude of impact