Andrew Katumba

1.0k total citations
48 papers, 627 citations indexed

About

Andrew Katumba is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Insect Science. According to data from OpenAlex, Andrew Katumba has authored 48 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Electrical and Electronic Engineering, 23 papers in Artificial Intelligence and 5 papers in Insect Science. Recurrent topics in Andrew Katumba's work include Optical Network Technologies (23 papers), Neural Networks and Reservoir Computing (20 papers) and Photonic and Optical Devices (14 papers). Andrew Katumba is often cited by papers focused on Optical Network Technologies (23 papers), Neural Networks and Reservoir Computing (20 papers) and Photonic and Optical Devices (14 papers). Andrew Katumba collaborates with scholars based in Belgium, Uganda and United States. Andrew Katumba's co-authors include Peter Bienstman, Joni Dambre, Matthias Freiberger, Xin Yin, Damien Rontani, Marc Sciamanna, Günther Roelkens, Sarah Uvin, John L. Nosher and Grum Gebreyesus and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Optics Express.

In The Last Decade

Andrew Katumba

37 papers receiving 586 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Katumba Belgium 15 490 431 55 37 32 48 627
Yifan Zhao United States 9 244 0.5× 258 0.6× 70 1.3× 16 0.4× 77 2.4× 17 441
Yuchen Guo China 9 52 0.1× 106 0.2× 60 1.1× 10 0.3× 41 1.3× 46 303
Alireza Moini Australia 7 112 0.2× 69 0.2× 103 1.9× 15 0.4× 29 0.9× 15 286
Danijela Marković France 11 130 0.3× 143 0.3× 131 2.4× 20 0.5× 16 0.5× 24 278
Chengyang Hu China 9 241 0.5× 226 0.5× 41 0.7× 3 0.1× 47 1.5× 19 400
Weifang Huang China 9 211 0.4× 210 0.5× 32 0.6× 126 3.4× 23 0.7× 24 411
Jong-Seok Park United States 17 483 1.0× 39 0.1× 92 1.7× 19 0.5× 139 4.3× 28 663
Martin A. Trefzer United Kingdom 10 200 0.4× 184 0.4× 24 0.4× 39 1.1× 36 1.1× 72 342
Todor Mladenov United States 10 189 0.4× 71 0.2× 76 1.4× 11 0.3× 21 0.7× 22 269

Countries citing papers authored by Andrew Katumba

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Katumba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Katumba

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Katumba. A scholar is included among the top collaborators of Andrew Katumba 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 Andrew Katumba. Andrew Katumba 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.
Katumba, Andrew, et al.. (2025). A dataset of lung ultrasound images for automated AI-based lung disease classification. Data in Brief. 62. 112034–112034.
2.
Katumba, Andrew, et al.. (2025). Automated AI ‐Based Lung Disease Classification Using Point‐of‐Care Ultrasound. SHILAP Revista de lepidopterología. 7(1).
3.
4.
Katumba, Andrew, et al.. (2025). IoT and Machine Learning Techniques for Precision Beekeeping: A Review. AI. 6(2). 26–26.
5.
Katumba, Andrew, et al.. (2025). Deep learning for accurate B-line detection and localization in lung ultrasound imaging. Frontiers in Artificial Intelligence. 8. 1560523–1560523. 2 indexed citations
6.
Katumba, Andrew, et al.. (2024). Leveraging edge computing and deep learning for the real-time identification of bean plant pathologies. SHILAP Revista de lepidopterología. 9. 100627–100627. 6 indexed citations
7.
Nakatumba‐Nabende, Joyce, et al.. (2024). Building Text and Speech Benchmark Datasets and Models for Low‐Resourced East African Languages: Experiences and Lessons. SHILAP Revista de lepidopterología. 5(2). 5 indexed citations
8.
Nakatumba‐Nabende, Joyce, et al.. (2023). Using machine learning for image-based analysis of sweetpotato root sensory attributes. SHILAP Revista de lepidopterología. 5. 100291–100291. 8 indexed citations
9.
Katumba, Andrew, et al.. (2023). Implementing Smartphone-Based Telemedicine for Cervical Cancer Screening in Uganda: Qualitative Study of Stakeholders’ Perceptions. Journal of Medical Internet Research. 25. e45132–e45132. 5 indexed citations
10.
Katumba, Andrew, et al.. (2023). Coffee and cashew nut dataset: A dataset for detection, classification, and yield estimation for machine learning applications. Data in Brief. 52. 109952–109952. 3 indexed citations
11.
Katumba, Andrew, et al.. (2020). Photonic neuromorphic information processing and reservoir computing. APL Photonics. 5(2). 66 indexed citations
12.
Katumba, Andrew, Xin Yin, Joni Dambre, & Peter Bienstman. (2019). A Neuromorphic Silicon Photonics Nonlinear Equalizer For Optical Communications With Intensity Modulation and Direct Detection. Journal of Lightwave Technology. 37(10). 2232–2239. 46 indexed citations
13.
Freiberger, Matthias, et al.. (2019). Improving Time Series Recognition and Prediction With Networks and Ensembles of Passive Photonic Reservoirs. IEEE Journal of Selected Topics in Quantum Electronics. 26(1). 1–11. 33 indexed citations
14.
Sciamanna, Marc, Andrew Katumba, Matthias Freiberger, et al.. (2018). All-Optical Reservoir Computing on a Photonic Chip Using Silicon-Based Ring Resonators. IEEE Journal of Selected Topics in Quantum Electronics. 24(6). 1–8. 81 indexed citations
15.
Freiberger, Matthias, Andrew Katumba, Peter Bienstman, & Joni Dambre. (2018). Training Passive Photonic Reservoirs With Integrated Optical Readout. IEEE Transactions on Neural Networks and Learning Systems. 30(7). 1943–1953. 26 indexed citations
16.
Katumba, Andrew, et al.. (2018). Neuromorphic Computing Based on Silicon Photonics and Reservoir Computing. IEEE Journal of Selected Topics in Quantum Electronics. 24(6). 1–10. 35 indexed citations
17.
Katumba, Andrew, et al.. (2018). Low-Loss Photonic Reservoir Computing with Multimode Photonic Integrated Circuits. Scientific Reports. 8(1). 2653–2653. 35 indexed citations
18.
Rahim, Abdul, Amin Abbasi, André Richter, et al.. (2018). 50 Gb/s DMT and 120 Mb/s LTE signal transmission over 5 km of optical fiber using a silicon photonics transceiver. Advanced Photonics 2018 (BGPP, IPR, NP, NOMA, Sensors, Networks, SPPCom, SOF). IW1B.4–IW1B.4.
19.
Katumba, Andrew, Xin Yin, Joni Dambre, & Peter Bienstman. (2018). Silicon Photonics Neuromorphic Computing and its Application to Telecommunications (Invited). 2. 1–3.
20.
Freiberger, Matthias, Andrew Katumba, Peter Bienstman, & Joni Dambre. (2017). On-Chip Passive Photonic Reservoir Computing with Integrated Optical Readout. 1–4. 8 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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