Fizza Hussain

463 total citations · 1 hit paper
16 papers, 279 citations indexed

About

Fizza Hussain is a scholar working on Safety, Risk, Reliability and Quality, Civil and Structural Engineering and Building and Construction. According to data from OpenAlex, Fizza Hussain has authored 16 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Safety, Risk, Reliability and Quality, 4 papers in Civil and Structural Engineering and 4 papers in Building and Construction. Recurrent topics in Fizza Hussain's work include Traffic and Road Safety (7 papers), Traffic Prediction and Management Techniques (4 papers) and Asphalt Pavement Performance Evaluation (4 papers). Fizza Hussain is often cited by papers focused on Traffic and Road Safety (7 papers), Traffic Prediction and Management Techniques (4 papers) and Asphalt Pavement Performance Evaluation (4 papers). Fizza Hussain collaborates with scholars based in Pakistan, Australia and United Kingdom. Fizza Hussain's co-authors include Yasir Ali, Md. Mazharul Haque, Yuefeng Li, Muhammad Irfan, Ashutosh Arun, Michiel C.J. Bliemer, Zuduo Zheng, Abdullah Alamri, Yuefeng Li and Mohammed A. Alqarni and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Construction and Building Materials.

In The Last Decade

Fizza Hussain

15 papers receiving 266 citations

Hit Papers

align trajectories

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.

Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review

2023 75 citations Yasir Ali, Fizza Hussain et al. Accident Analysis & Prevention profile →

Peers

Fizza Hussain

SRRQ

CSE

Qi Shi United States

Junhua Wang China

Lukuman Wahab China

Seyedmirsajad Mokhtarimousavi United States

Laura Garach Spain

John McFadden United States

Amirfarrokh Iranitalab United States

Essam Dabbour Canada

Metin Mutlu Aydın Türkiye

Qi Shi United States

Fizza Hussain

173 ×1.3

SRRQ

117 ×1.2

63 ×0.8

33 ×0.4

CSE

85 ×2.2

CSE

Citations per year, relative to Fizza Hussain Fizza Hussain (= 1×) peers Qi Shi

Countries citing papers authored by Fizza Hussain

Since Specialization

Citations

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

Fields of papers citing papers by Fizza Hussain

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fizza Hussain

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

All Works

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16 of 16 papers shown

Hussain, Fizza, et al.. (2025). Effects of Virtual Rehabilitation on Upper Extremity Motor Learning in Hemiplegic Cerebral Palsy. 5(2). 88–92.

Hussain, Fizza, Yuefeng Li, & Md. Mazharul Haque. (2024). Integrating machine learning and extreme value theory for estimating crash frequency-by-severity via AI-based video analytics. SHILAP Revista de lepidopterología. 4. 100147–100147. 5 indexed citations

Hussain, Fizza, Yasir Ali, Yuefeng Li, & Md. Mazharul Haque. (2024). A bi-level framework for real-time crash risk forecasting using artificial intelligence-based video analytics. Scientific Reports. 14(1). 4121–4121. 5 indexed citations

Hussain, Fizza, Yasir Ali, Yuefeng Li, & Md. Mazharul Haque. (2024). Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics. Accident Analysis & Prevention. 199. 107517–107517. 13 indexed citations

Ali, Yasir, Fizza Hussain, & Md. Mazharul Haque. (2023). Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review. Accident Analysis & Prevention. 194. 107378–107378. 75 indexed citations breakdown →

Hussain, Fizza, Yasir Ali, Yuefeng Li, & Md. Mazharul Haque. (2023). Real-time crash risk forecasting using Artificial-Intelligence based video analytics: A unified framework of generalised extreme value theory and autoregressive integrated moving average model. Analytic Methods in Accident Research. 40. 100302–100302. 21 indexed citations

Hussain, Fizza, Rizwan Hasan Khan, Amgad Mentias, et al.. (2022). In-hospital and Readmission Outcomes With Percutaneous Balloon Mitral Valvuloplasty. Current Problems in Cardiology. 47(12). 101367–101367. 2 indexed citations

Hussain, Fizza, et al.. (2022). Diabetic Foot Ulcers: Prevalence and Associated Risk Factors Among Diabetic Patients. Pakistan Journal of Health Sciences. 86–90. 1 indexed citations

Hussain, Fizza, Yuefeng Li, Ashutosh Arun, & Md. Mazharul Haque. (2022). A hybrid modelling framework of machine learning and extreme value theory for crash risk estimation using traffic conflicts. Analytic Methods in Accident Research. 36. 100248–100248. 49 indexed citations

10.

Ali, Yasir, Fizza Hussain, Michiel C.J. Bliemer, Zuduo Zheng, & Md. Mazharul Haque. (2022). Predicting and explaining lane-changing behaviour using machine learning: A comparative study. Transportation Research Part C Emerging Technologies. 145. 103931–103931. 33 indexed citations

11.

Hussain, Fizza, et al.. (2021). The Mediating Role of Electronic Performance Monitoring in the relationship between Personality Traits and Work Passion. Asian Journal of Business Research. 11(2). 2 indexed citations

12.

Hussain, Fizza, Yasir Ali, & Muhammad Irfan. (2021). Alternative Approach for Predicting the Phase Angle Characteristics of Asphalt Concrete Mixtures Based on Recurrent Neural Networks. Journal of Materials in Civil Engineering. 33(9). 4 indexed citations

13.

Hussain, Fizza, Yasir Ali, & Muhammad Irfan. (2021). Quantifying the Differential Phase Angle Behaviour of Asphalt Concrete Mixtures Using Artificial Neural Networks. International Journal of Pavement Research and Technology. 15(3). 640–658. 9 indexed citations

14.

Ali, Yasir, et al.. (2021). An eXtreme Gradient Boosting model for predicting dynamic modulus of asphalt concrete mixtures. Construction and Building Materials. 295. 123642–123642. 38 indexed citations

15.

Hussain, Fizza, et al.. (2020). A data-driven model for phase angle behaviour of asphalt concrete mixtures based on convolutional neural network. Construction and Building Materials. 269. 121235–121235. 19 indexed citations

16.

Hussain, Fizza, et al.. (2017). Fault-tolerance analyzer: A middle layer for pre-provision testing in OpenStack. Computers & Electrical Engineering. 66. 64–79. 3 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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