Andrew Hines

2.2k total citations · 1 hit paper
87 papers, 1.2k citations indexed

About

Andrew Hines is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Andrew Hines has authored 87 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Signal Processing, 33 papers in Computer Vision and Pattern Recognition and 24 papers in Cognitive Neuroscience. Recurrent topics in Andrew Hines's work include Speech and Audio Processing (44 papers), Hearing Loss and Rehabilitation (21 papers) and Image and Video Quality Assessment (20 papers). Andrew Hines is often cited by papers focused on Speech and Audio Processing (44 papers), Hearing Loss and Rehabilitation (21 papers) and Image and Video Quality Assessment (20 papers). Andrew Hines collaborates with scholars based in Ireland, United States and United Kingdom. Andrew Hines's co-authors include Alcardo Alex Barakabitze, Arslan Ahmad, Rashid Mijumbi, Naomi Harte, Jan Skoglund, Anil Kokaram, Damien P. Kelly, Declan Delaney, Andrew S. Allen and Francisco Gortázar and has published in prestigious journals such as Scientific Reports, The Journal of the Acoustical Society of America and IEEE Access.

In The Last Decade

Andrew Hines

77 papers receiving 1.2k 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.

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

2019 521 citations Alcardo Alex Barakabitze, Andrew Hines et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew Hines Ireland	15	524	427	272	257	186	87	1.2k
Ahsan Adeel United Kingdom	15	292 0.6×	229 0.5×	113 0.4×	115 0.4×	441 2.4×	35	808
Kyu-Han Kim United States	16	700 1.3×	166 0.4×	149 0.5×	568 2.2×	82 0.4×	43	1.1k
Zhanyong Tang China	18	348 0.7×	553 1.3×	212 0.8×	565 2.2×	250 1.3×	82	1.4k
Nirupam Roy United States	12	127 0.2×	471 1.1×	238 0.9×	375 1.5×	267 1.4×	40	959
Shahriar Nirjon United States	16	315 0.6×	181 0.4×	286 1.1×	427 1.7×	178 1.0×	75	1.0k
Bo Cao China	15	166 0.3×	364 0.9×	1.1k 4.2×	98 0.4×	279 1.5×	36	1.7k
Huajie Shao United States	18	315 0.6×	118 0.3×	325 1.2×	367 1.4×	436 2.3×	53	1.1k
Anfu Zhou China	21	478 0.9×	280 0.7×	487 1.8×	822 3.2×	124 0.7×	81	1.7k
Maria Torres Vega Belgium	16	260 0.5×	221 0.5×	574 2.1×	149 0.6×	75 0.4×	72	948
Yongpan Zou China	11	233 0.4×	306 0.7×	230 0.8×	611 2.4×	75 0.4×	37	928

Countries citing papers authored by Andrew Hines

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Hines

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Hines

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

All Works

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20 of 20 papers shown

1.

Hines, Andrew, et al.. (2025). Beyond Correlation: Evaluating Multimedia Quality Models With the Constrained Concordance Index. IEEE Transactions on Multimedia. 27. 5604–5616. 1 indexed citations

2.

Cisek, Katryna, et al.. (2024). Predictors of social risk for post-ischemic stroke reintegration. Scientific Reports. 14(1). 10110–10110.

3.

Ullah, Asad, et al.. (2024). Naturalness and the Utility of Synthetic Speech in Model Pre-training. 101–105.

4.

Skoglund, Jan, et al.. (2024). NOMAD: Unsupervised Learning of Perceptual Embeddings For Speech Enhancement and Non-Matching Reference Audio Quality Assessment. 1011–1015. 3 indexed citations

5.

Anwar, Muhammad Shahid, Ahyoung Choi, Sadique Ahmad, et al.. (2024). A Moving Metaverse: QoE challenges and standards requirements for immersive media consumption in autonomous vehicles. Applied Soft Computing. 159. 111577–111577. 27 indexed citations

6.

Barakabitze, Alcardo Alex, Is-Haka Mkwawa, Andrew Hines, & Ray Walshe. (2023). QoE-Aware Dynamic Resource Management in Future Softwarized and Virtualized Networks. IEEE Access. 11. 93310–93330. 2 indexed citations

7.

Jassim, Wissam A., et al.. (2022). Speech quality assessment with WARP‐Q: From similarity to subsequence dynamic time warp cost. IET Signal Processing. 16(9). 1050–1070. 1 indexed citations

8.

Hines, Andrew, et al.. (2022). An audio processing pipeline for acquiring diagnostic quality heart sounds via mobile phone. Computers in Biology and Medicine. 145. 105415–105415. 11 indexed citations

9.

Hines, Andrew, et al.. (2022). Multimedia Streaming in SDN/NFV and 5G Networks. 2 indexed citations

10.

Flynn, Ronan, et al.. (2021). The Role of Physiological Responses in a VR-Based Sound Localization Task. IEEE Access. 9. 122082–122091. 6 indexed citations

11.

Hines, Andrew, et al.. (2020). Exploring Composite Dataset Biases for Heart Sound Classification.. Research Repository UCD (University College Dublin). 145–156. 1 indexed citations

12.

Hines, Andrew, et al.. (2019). A Psychologist Chatbot Developing Experience.. 200–211. 2 indexed citations

13.

Parker, Matthew W., et al.. (2019). Perception Deception: Audio-Visual Mismatch in Virtual Reality Using The McGurk Effect.. 176–187. 5 indexed citations

14.

Hines, Andrew, et al.. (2018). Exploring a Perceptually-Weighted DNN-based Fusion Model for Speech Separation.. 21–32. 1 indexed citations

15.

Harte, Naomi, et al.. (2017). Objective Assessment of Perceptual Audio Quality Using ViSQOLAudio. IEEE Transactions on Broadcasting. 63(4). 693–705. 25 indexed citations

16.

Hines, Andrew, Jan Skoglund, Anil Kokaram, & Naomi Harte. (2016). Monitoring Voip Speech Quality for Chopped and Clipped Speech. Communications - Scientific letters of the University of Zilina. 18(1). 3–10. 1 indexed citations

17.

Harte, Naomi, et al.. (2015). TCD-VoIP, a research database of degraded speech for assessing quality in VoIP applications. Arrow - TU Dublin (Technological University Dublin). 1–6. 22 indexed citations

18.

Hines, Andrew, et al.. (2015). Measuring and monitoring speech quality for voice over IP with POLQA, viSQOL and p.563. 438–442. 3 indexed citations

19.

Hines, Andrew, et al.. (2014). Perceived Audio Quality for Streaming Stereo Music. ARROW@Dublin Institute of Technology (Dublin Institute of Technology). 1173–1176. 11 indexed citations

20.

Hines, Andrew & Naomi Harte. (2011). Simulated performance intensity functions. PubMed. 9. 7139–7142.

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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