Stuart Lacy

878 total citations · 1 hit paper
16 papers, 423 citations indexed

About

Stuart Lacy is a scholar working on Artificial Intelligence, Environmental Engineering and Pathology and Forensic Medicine. According to data from OpenAlex, Stuart Lacy has authored 16 papers receiving a total of 423 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Environmental Engineering and 3 papers in Pathology and Forensic Medicine. Recurrent topics in Stuart Lacy's work include Air Quality and Health Impacts (3 papers), Air Quality Monitoring and Forecasting (3 papers) and Lymphoma Diagnosis and Treatment (3 papers). Stuart Lacy is often cited by papers focused on Air Quality and Health Impacts (3 papers), Air Quality Monitoring and Forecasting (3 papers) and Lymphoma Diagnosis and Treatment (3 papers). Stuart Lacy collaborates with scholars based in United Kingdom, United States and Chile. Stuart Lacy's co-authors include Stephen L. Smith, Michael A. Lones, Peter J. Campbell, Eve Roman, Philip Beer, Daniel J. Hodson, Camilo Ruiz, Susanna L. Cooke, Daniel Painter and Alexandra Smith and has published in prestigious journals such as Nature Communications, Blood and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Stuart Lacy

12 papers receiving 417 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.

Targeted sequencing in DLBCL, molecular subtypes, and outcomes: a Haematological Malignancy Research Network report

2020 260 citations Stuart Lacy, Sharon Barrans et al. Blood profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stuart Lacy United Kingdom	8	238	151	111	78	73	16	423
Xufeng Jiang China	13	92 0.4×	103 0.7×	30 0.3×	65 0.8×	123 1.7×	44	480
Lauren C. Chong Canada	12	213 0.9×	259 1.7×	67 0.6×	55 0.7×	193 2.6×	29	578
Noha Lim United States	15	135 0.6×	86 0.6×	73 0.7×	58 0.7×	172 2.4×	33	860
Saud H. AlDubayan United States	14	123 0.5×	185 1.2×	22 0.2×	25 0.3×	348 4.8×	32	786
Wojciech Kozłowski Poland	15	70 0.3×	219 1.5×	64 0.6×	18 0.2×	224 3.1×	41	673
Yongqiang Tang United States	16	80 0.3×	102 0.7×	28 0.3×	19 0.2×	77 1.1×	44	567
Simon Papillon‐Cavanagh United States	10	35 0.1×	223 1.5×	47 0.4×	18 0.2×	314 4.3×	14	734
Lluís E. Pons Spain	8	223 0.9×	202 1.3×	59 0.5×	28 0.4×	66 0.9×	8	439
Alexander Arnold Germany	13	98 0.4×	177 1.2×	16 0.1×	78 1.0×	124 1.7×	24	572
Roman Ludwig Switzerland	9	50 0.2×	108 0.7×	137 1.2×	78 1.0×	124 1.7×	21	518

Countries citing papers authored by Stuart Lacy

Since Specialization

Citations

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

Fields of papers citing papers by Stuart Lacy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stuart Lacy

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

Wiggins, L. F., Stuart Lacy, Joanne Marrison, et al.. (2025). CellPhePy: A python implementation of the CellPhe toolkit for automated cell phenotyping from microscopy time‐lapse videos. Journal of Microscopy. 300(2). 250–259.

Lee, James, Shona E. Wilde, Will Drysdale, et al.. (2025). SO ₂ and NO _x emissions from ships in North-East Atlantic waters: in situ measurements and comparison with an emission model. Environmental Science Atmospheres. 5(12). 1282–1296.

Lacy, Stuart, et al.. (2025). P1 Predicting EQ-5D Index Scores: A Comparison Study of Machine Learning and Statistical Methods on Health Survey for England Data. Value in Health. 28(12). S26–S26.

Lacy, Stuart, Hugh Coe, Max Priestman, et al.. (2024). Long-term evaluation of commercial air quality sensors: an overview from the QUANT (Quantification of Utility of Atmospheric Network Technologies) study. Atmospheric measurement techniques. 17(12). 3809–3827. 11 indexed citations

Lacy, Stuart, et al.. (2024). QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation. Scientific Data. 11(1). 904–904. 3 indexed citations

Wiggins, L. F., et al.. (2023). The CellPhe toolkit for cell phenotyping using time-lapse imaging and pattern recognition. Nature Communications. 14(1). 1854–1854. 16 indexed citations

Crouch, Simon, Daniel Painter, Sharon Barrans, et al.. (2022). Molecular subclusters of follicular lymphoma: a report from the United Kingdom’s Haematological Malignancy Research Network. Blood Advances. 6(21). 5716–5731. 17 indexed citations

Lacy, Stuart, Thomas J. Bannan, Michael Flynn, et al.. (2022). Air pollution measurement errors: is your data fit for purpose?. Atmospheric measurement techniques. 15(13). 4091–4105. 11 indexed citations

Crouch, Simon, Daniel Painter, Sharon Barrans, et al.. (2021). MOLECULAR SUBCLUSTERS OF FOLLICULAR LYMPHOMA: A REPORT FROM THE UK'S HAEMATOLOGICAL MALIGNANCY RESEARCH NETWORK. Hematological Oncology. 39(S2).

10.

Lacy, Stuart, Sharon Barrans, Philip Beer, et al.. (2020). Targeted sequencing in DLBCL, molecular subtypes, and outcomes: a Haematological Malignancy Research Network report. Blood. 135(20). 1759–1771. 260 indexed citations breakdown →

11.

Lacy, Stuart, Stephen L. Smith, & Michael A. Lones. (2018). Using echo state networks for classification: A case study in Parkinson's disease diagnosis. Artificial Intelligence in Medicine. 86. 53–59. 40 indexed citations

12.

Lacy, Stuart, Michael A. Lones, & Stephen L. Smith. (2015). A comparison of evolved linear and non-linear ensemble vote aggregators. 758–763. 10 indexed citations

13.

Lacy, Stuart, Michael A. Lones, & Stephen L. Smith. (2015). Forming classifier ensembles with multimodal evolutionary algorithms. 2. 723–729. 5 indexed citations

14.

Lones, Michael A., Jane Alty, Stuart Lacy, et al.. (2013). Evolving classifiers to inform clinical assessment of Parkinson's disease. 76–82. 5 indexed citations

15.

Lacy, Stuart, Michael A. Lones, Stephen L. Smith, et al.. (2013). Characterisation of movement disorder in parkinson's disease using evolutionary algorithms. 1479–1486. 3 indexed citations

16.

Lones, Michael A., Stephen L. Smith, Jane Alty, et al.. (2013). Evolving Classifiers to Recognize the Movement Characteristics of Parkinson's Disease Patients. IEEE Transactions on Evolutionary Computation. 18(4). 559–576. 42 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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