Latifa Oukhellou

3.6k total citations · 1 hit paper
74 papers, 2.4k citations indexed

About

Latifa Oukhellou is a scholar working on Transportation, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Latifa Oukhellou has authored 74 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Transportation, 20 papers in Artificial Intelligence and 15 papers in Electrical and Electronic Engineering. Recurrent topics in Latifa Oukhellou's work include Transportation Planning and Optimization (18 papers), Human Mobility and Location-Based Analysis (17 papers) and Fault Detection and Control Systems (8 papers). Latifa Oukhellou is often cited by papers focused on Transportation Planning and Optimization (18 papers), Human Mobility and Location-Based Analysis (17 papers) and Fault Detection and Control Systems (8 papers). Latifa Oukhellou collaborates with scholars based in France, Algeria and Canada. Latifa Oukhellou's co-authors include Étienne Côme, Samer Mohammed, Faïcel Chamroukhi, Ferhat Attal, Yacine Amirat, Patrice Aknin, Mohamed Khalil El Mahrsi, Martin Trépanier, Thierry Denœux and Allou Samé and has published in prestigious journals such as Applied Energy, International Journal of Hydrogen Energy and IEEE Access.

In The Last Decade

Latifa Oukhellou

69 papers receiving 2.3k citations

Hit Papers

Physical Human Activity Recognition Using Wearable Sensors 2015 2026 2018 2022 2015 100 200 300 400 500
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.

  1. Physical Human Activity Recognition Using Wearable Sensors
    2015 578 citations Ferhat Attal, Samer Mohammed et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Latifa Oukhellou France 25 662 593 455 431 409 74 2.4k
Petteri Nurmi Finland 27 538 0.8× 659 1.1× 684 1.5× 283 0.7× 205 0.5× 155 2.7k
Isaac Skog Sweden 28 176 0.3× 391 0.7× 1.6k 3.6× 697 1.6× 581 1.4× 88 3.1k
Baoding Zhou China 22 373 0.6× 455 0.8× 935 2.1× 169 0.4× 113 0.3× 67 1.9k
Lin Liao China 24 618 0.9× 759 1.3× 645 1.4× 588 1.4× 110 0.3× 62 3.0k
Jiadi Yu China 31 196 0.3× 634 1.1× 771 1.7× 920 2.1× 311 0.8× 186 3.2k
Keiichi Yasumoto Japan 23 269 0.4× 490 0.8× 652 1.4× 220 0.5× 163 0.4× 292 2.1k
Shonali Krishnaswamy Australia 26 551 0.8× 952 1.6× 460 1.0× 1.4k 3.3× 275 0.7× 156 3.4k
Mikkel Baun Kjærgaard Denmark 24 420 0.6× 774 1.3× 1.1k 2.5× 516 1.2× 110 0.3× 130 3.2k
Hae Young Noh United States 29 112 0.2× 627 1.1× 732 1.6× 353 0.8× 789 1.9× 170 2.8k
Angelos Amditis Greece 26 146 0.2× 407 0.7× 620 1.4× 348 0.8× 102 0.2× 244 2.6k

Countries citing papers authored by Latifa Oukhellou

Since Specialization
Citations

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

Fields of papers citing papers by Latifa Oukhellou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Latifa Oukhellou

This figure shows the co-authorship network connecting the top 25 collaborators of Latifa Oukhellou. A scholar is included among the top collaborators of Latifa Oukhellou 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 Latifa Oukhellou. Latifa Oukhellou 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.
Furno, Angelo, et al.. (2026). Federated dynamic modeling and learning for spatiotemporal data forecasting. Neurocomputing. 672. 132712–132712.
2.
Côme, Étienne, et al.. (2024). Deep Probabilistic Forecasting of Multivariate Count Data With “Sums and Shares” Distributions: A Case Study on Pedestrian Counts in a Multimodal Transport Hub. IEEE Transactions on Intelligent Transportation Systems. 25(11). 15687–15701. 1 indexed citations
3.
Côme, Étienne, et al.. (2024). How Has the Paris Rail Public-Transportation Network Recovered After the COVID-19 Pandemic? Applying a Mixture of Regressions Model. Transportation Research Record Journal of the Transportation Research Board. 2679(3). 330–345.
4.
5.
Furno, Angelo, et al.. (2023). Adaptative generalisation over a value hierarchy for the k-anonymisation of Origin–Destination matrices. Transportation Research Part C Emerging Technologies. 154. 104236–104236. 3 indexed citations
6.
Côme, Étienne, et al.. (2023). Forecasting passenger flows and headway at train level for a public transport line: Focus on atypical situations. Transportation Research Part C Emerging Technologies. 153. 104195–104195. 7 indexed citations
7.
8.
Boubezoul, Abderrahmane, et al.. (2022). Online Human Intention Detection through Machine-learning based Algorithm for the Control of Lower-limbs Wearable Robot. SPIRE - Sciences Po Institutional REpository. 809–814. 1 indexed citations
9.
Samé, Allou, et al.. (2022). Dynamic clustering and modeling of temporal data subject to common regressive effects. Neurocomputing. 500. 217–230. 1 indexed citations
10.
Samé, Allou, et al.. (2021). Online common change-point detection in a set of nonstationary categorical time series. Neurocomputing. 439. 176–196. 2 indexed citations
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Samé, Allou, et al.. (2016). Hourly Solar Irradiance Forecasting Based on Machine Learning Models. 441–446. 32 indexed citations
14.
Senouci, Mustapha Réda, Abdelhamid Mellouk, Latifa Oukhellou, & Amar Aïssani. (2015). WSNs deployment framework based on the theory of belief functions. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
15.
Han, Yufei, Étienne Côme, & Latifa Oukhellou. (2014). Towards Bicycle Demand Prediction of Large-Scale Bicycle Sharing System. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 8 indexed citations
16.
Côme, Étienne, et al.. (2014). Spatio-temporal usage pattern analysis of the Paris shared bicycle scheme: a data mining approach. 6 indexed citations
17.
Attal, Ferhat, et al.. (2014). The Powered Two Wheelers fall detection using Multivariate CUmulative SUM (MCUSUM) control charts. 1280–1285. 9 indexed citations
18.
Côme, Étienne & Latifa Oukhellou. (2014). Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris. ACM Transactions on Intelligent Systems and Technology. 5(3). 1–21. 120 indexed citations
19.
Candusso, Denis, et al.. (2014). PEMFC stack voltage singularity measurement and fault classification. International Journal of Hydrogen Energy. 39(36). 21631–21637. 37 indexed citations
20.
Senouci, Mustapha Réda, Abdelhamid Mellouk, Latifa Oukhellou, & Amar Aïssani. (2012). Efficient uncertainty-aware deployment algorithms for wireless sensor networks. 2163–2167. 14 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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