Sadiqa Jafari

637 total citations
19 papers, 382 citations indexed

About

Sadiqa Jafari is a scholar working on Automotive Engineering, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Sadiqa Jafari has authored 19 papers receiving a total of 382 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Automotive Engineering, 13 papers in Electrical and Electronic Engineering and 6 papers in Control and Systems Engineering. Recurrent topics in Sadiqa Jafari's work include Advanced Battery Technologies Research (15 papers), Advancements in Battery Materials (10 papers) and Electric Vehicles and Infrastructure (7 papers). Sadiqa Jafari is often cited by papers focused on Advanced Battery Technologies Research (15 papers), Advancements in Battery Materials (10 papers) and Electric Vehicles and Infrastructure (7 papers). Sadiqa Jafari collaborates with scholars based in South Korea. Sadiqa Jafari's co-authors include Yung-Cheol Byun, Zeinab Shahbazi, Sang-Joon Lee, Jisoo Kim and Wonil Choi and has published in prestigious journals such as IEEE Access, Energy and Sensors.

In The Last Decade

Sadiqa Jafari

19 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sadiqa Jafari South Korea 13 264 213 118 54 46 19 382
Mitra Pourabdollah Sweden 10 445 1.7× 340 1.6× 94 0.8× 14 0.3× 22 0.5× 14 494
Punit Tulpule United States 17 817 3.1× 735 3.5× 165 1.4× 25 0.5× 19 0.4× 42 929
Yitong Shang China 15 555 2.1× 755 3.5× 137 1.2× 11 0.2× 17 0.4× 32 815
M. Vaziri United States 13 39 0.1× 348 1.6× 239 2.0× 33 0.6× 26 0.6× 39 411
Raphael Luz Austria 5 198 0.8× 77 0.4× 110 0.9× 13 0.2× 33 0.7× 11 257
Rodrigo García‐Valle Denmark 13 231 0.9× 619 2.9× 325 2.8× 24 0.4× 21 0.5× 25 656
Hongqian Wei China 13 299 1.1× 304 1.4× 116 1.0× 15 0.3× 8 0.2× 27 467
Dominik Karbowski United States 15 595 2.3× 324 1.5× 259 2.2× 10 0.2× 34 0.7× 72 688
Alivelu M. Parimi India 12 74 0.3× 451 2.1× 351 3.0× 16 0.3× 10 0.2× 75 571

Countries citing papers authored by Sadiqa Jafari

Since Specialization
Citations

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

Fields of papers citing papers by Sadiqa Jafari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sadiqa Jafari

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

All Works

19 of 19 papers shown
1.
Jafari, Sadiqa & Yung-Cheol Byun. (2025). Interpretable AI for explaining and predicting battery state of health using PSO-enhanced deep learning models. Energy Reports. 14. 1779–1798. 2 indexed citations
2.
Jafari, Sadiqa & Yung-Cheol Byun. (2025). AI-driven state of power prediction in battery systems: A PSO-optimized deep learning approach with XAI. Energy. 331. 136764–136764. 7 indexed citations
3.
Jafari, Sadiqa, Jisoo Kim, & Yung-Cheol Byun. (2024). A novel fusion-based deep learning approach with PSO and explainable AI for batteries State of Charge estimation in Electric Vehicles. Energy Reports. 12. 3364–3385. 2 indexed citations
4.
Jafari, Sadiqa, et al.. (2024). Optimized XGBoost modeling for accurate battery capacity degradation prediction. Results in Engineering. 24. 102786–102786. 27 indexed citations
5.
Jafari, Sadiqa, Jisoo Kim, & Yung-Cheol Byun. (2024). Integrating ensemble learning and meta bagging techniques for temperature-specific State of Health prediction in Lithium-ion Batteries. Energy Reports. 12. 2388–2407. 8 indexed citations
6.
Jafari, Sadiqa & Yung-Cheol Byun. (2024). Efficient state of charge estimation in electric vehicles batteries based on the extra tree regressor: A data-driven approach. Heliyon. 10(4). e25949–e25949. 24 indexed citations
7.
Jafari, Sadiqa, Jisoo Kim, Wonil Choi, & Yung-Cheol Byun. (2024). Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries. IEEE Access. 13. 11463–11478. 5 indexed citations
8.
Jafari, Sadiqa & Yung-Cheol Byun. (2023). A CNN-GRU Approach to the Accurate Prediction of Batteries’ Remaining Useful Life from Charging Profiles. Computers. 12(11). 219–219. 20 indexed citations
9.
Jafari, Sadiqa & Yung-Cheol Byun. (2023). Optimizing Battery RUL Prediction of Lithium-Ion Batteries Based on Harris Hawk Optimization Approach Using Random Forest and LightGBM. IEEE Access. 11. 87034–87046. 38 indexed citations
10.
Jafari, Sadiqa, et al.. (2023). A Novel Approach for Predicting Remaining Useful Life and Capacity Fade in Lithium-Ion Batteries Using Hybrid Machine Learning. IEEE Access. 11. 131950–131963. 22 indexed citations
11.
Jafari, Sadiqa, et al.. (2023). Accurate remaining useful life estimation of lithium-ion batteries in electric vehicles based on a measurable feature-based approach with explainable AI. The Journal of Supercomputing. 80(4). 4707–4732. 22 indexed citations
12.
Jafari, Sadiqa, Zeinab Shahbazi, & Yung-Cheol Byun. (2022). Designing the Controller-Based Urban Traffic Evaluation and Prediction Using Model Predictive Approach. Applied Sciences. 12(4). 1992–1992. 12 indexed citations
13.
Jafari, Sadiqa, Zeinab Shahbazi, Yung-Cheol Byun, & Sang-Joon Lee. (2022). Lithium-Ion Battery Estimation in Online Framework Using Extreme Gradient Boosting Machine Learning Approach. Mathematics. 10(6). 888–888. 45 indexed citations
14.
Jafari, Sadiqa, Zeinab Shahbazi, & Yung-Cheol Byun. (2022). Lithium-Ion Battery Health Prediction on Hybrid Vehicles Using Machine Learning Approach. Energies. 15(13). 4753–4753. 29 indexed citations
15.
Jafari, Sadiqa & Yung-Cheol Byun. (2022). XGBoost-Based Remaining Useful Life Estimation Model with Extended Kalman Particle Filter for Lithium-Ion Batteries. Sensors. 22(23). 9522–9522. 28 indexed citations
16.
Jafari, Sadiqa, Zeinab Shahbazi, & Yung-Cheol Byun. (2022). Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections. Mathematics. 10(16). 2832–2832. 17 indexed citations
17.
Jafari, Sadiqa & Yung-Cheol Byun. (2022). Prediction of the Battery State Using the Digital Twin Framework Based on the Battery Management System. IEEE Access. 10. 124685–124696. 45 indexed citations
18.
Jafari, Sadiqa, Zeinab Shahbazi, & Yung-Cheol Byun. (2021). Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection. Processes. 9(12). 2205–2205. 13 indexed citations
19.
Jafari, Sadiqa, Zeinab Shahbazi, & Yung-Cheol Byun. (2021). Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller. Sustainability. 13(10). 5630–5630. 16 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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