By Scientia Professor Matthew Heathcote England

Preprints

Aguiar W; Sohail T; Morrison AK; Ong EQY; Dias FB; Huneke WGC; Spence P; England MH, 2026, Reassessing the role of the Antarctic Slope Current in poleward ocean heat transport, http://dx.doi.org/10.22541/essoar.175700056.62702833/v2

Narayanan A; Ayres H; England M; Haumann A; Mazloff M; Silvano A; Spira T; Zhou S; Naveira Garabato A, 2026, Compound Drivers of Antarctic Sea Ice Loss, http://dx.doi.org/10.31223/x51v0b

Schmidt C; Morrison AK; England MH; Silvano A, 2025, Reduced West Antarctic melt rates and winds drive salinity rebound in the Ross Sea via baroclinic waves, http://dx.doi.org/10.22541/essoar.173870875.51711851/v2

Aguiar W; Sohail T; Morrison AK; Ong EQY; Dias FB; Huneke WGC; Spence P; England MH, 2025, Reassessing the role of the Antarctic Slope Current in poleward ocean heat transport, http://dx.doi.org/10.22541/essoar.175700056.62702833/v1

Flood D; England M; Grawemeyer B, 2025, Predicting At-Risk Programming Students in Small Imbalanced Datasets using Synthetic Data, https://arxiv.org/abs/2505.17128v1

Schmidt C; Morrison AK; England MH; Aguiar W; Gibson AH, 2025, Sensitivity of Antarctic Bottom Water formation and export to horizontal model resolution, http://dx.doi.org/10.22541/essoar.172469193.39598080/v2

Boeira Dias F; England MH; Morrison AK; Galton-Fenzi B, 2025, On the seasonal variability of ocean heat transport and ice shelf melt around Antarctica, http://dx.doi.org/10.5194/egusphere-2024-3905

Schmidt C; Morrison AK; England MH; Silvano A, 2025, West Antarctic melt variability and wind anomalies contribute to Ross Sea salinity rebound, http://dx.doi.org/10.22541/essoar.173870875.51711851/v1

Ong EQY; Doddridge E; Hogg AM; England MH, 2024, Seasonal sea-ice and eddy variability around the Antarctic margin, http://dx.doi.org/10.22541/essoar.173532505.52665007/v1

Ong EQY; England MH; Doddridge E; Constantinou NC, 2024, Transient Antarctic Slope Current Response to Climate Change including Meltwater, http://dx.doi.org/10.22541/essoar.173386140.05935937/v1

Michel L; Nalbach J; Mathonet P; Zénaïdi N; Brown CW; Ábrahám E; Davenport JH; England M, 2024, On Projective Delineability, https://doi.org/10.1109/SYNASC65383.2024.00015

Barket R; Shafiq U; England M; Gerhard J, 2024, Transformers to Predict the Applicability of Symbolic Integration Routines, https://arxiv.org/abs/2410.23948v1

Schmidt C; Morrison AK; England MH; Aguiar W; Gibson AH, 2024, Sensitivity of Antarctic Bottom Water formation and export to horizontal model resolution, http://dx.doi.org/10.22541/essoar.172469193.39598080/v1

England M, 2024, Recent Developments in Real Quantifier Elimination and Cylindrical Algebraic Decomposition, https://doi.org/10.1007/978-3-031-69070-9_1

Yao S; Sadeghimanesh A; England M, 2024, Understanding Multistationarity of Fully Open Reaction Networks, https://doi.org/10.1007/s11538-025-01537-8

Barket R; England M; Gerhard J, 2024, The Liouville Generator for Producing Integrable Expressions, https://doi.org/10.1007/978-3-031-69070-9_4

Sohail T; Gayen B; Klocker A; li Q; England MH, 2024, Future decline of Antarctic Circumpolar Current due to polar ocean freshening, http://dx.doi.org/10.22541/essoar.170294047.79411138/v3

Florescu D; England M, 2024, Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems, https://arxiv.org/abs/2404.17508v1

Barket R; England M; Gerhard J, 2024, Symbolic Integration Algorithm Selection with Machine Learning: LSTMs vs Tree LSTMs, https://arxiv.org/abs/2404.14973v1

Ong EQY; Doddridge E; Constantinou NC; Hogg AM; England MH, 2024, Intrinsically episodic Antarctic shelf intrusions of circumpolar deep water via canyons, http://dx.doi.org/10.48550/arxiv.2304.13225

Río TD; England M, 2024, Lessons on Datasets and Paradigms in Machine Learning for Symbolic Computation: A Case Study on CAD, https://doi.org/10.1007/s11786-024-00591-0

Davenport JH; England M; McCallum S; Uncu AK, 2023, Iterated Resultants and Rational Functions in Real Quantifier Elimination, https://doi.org/10.1007/s11786-025-00606-4

Davenport JH; England M, 2023, Iterated Resultants in CAD, https://arxiv.org/abs/2307.16750v1

Uncu AK; Davenport JH; England M, 2023, SMT-Solving Induction Proofs of Inequalities, https://arxiv.org/abs/2307.16761v1

Rio TD; England M, 2023, Data Augmentation for Mathematical Objects, https://arxiv.org/abs/2307.06984v1

Barket R; England M; Gerhard J, 2023, Generating Elementary Integrable Expressions, https://doi.org/10.1007/978-3-031-41724-5_2

Pickering L; Almajano TDR; England M; Cohen K, 2023, Explainable AI Insights for Symbolic Computation: A case study on selecting the variable ordering for cylindrical algebraic decomposition, https://doi.org/10.1016/j.jsc.2023.102276

Nalbach J; Ábrahám E; Specht P; Brown CW; Davenport JH; England M, 2022, Levelwise construction of a single cylindrical algebraic cell, https://doi.org/10.1016/j.jsc.2023.102288

England M, 2022, SC-Square: Future Progress with Machine Learning?, https://arxiv.org/abs/2209.04361v1

England M, 2022, SC-Square: Overview to 2021, https://arxiv.org/abs/2209.04359v1

Río TD; England M, 2022, New heuristic to choose a cylindrical algebraic decomposition variable ordering motivated by complexity analysis, https://doi.org/10.1007/978-3-031-14788-3_17

Sadeghimanesh A; England M, 2022, Resultant Tools for Parametric Polynomial Systems with Application to Population Models, https://arxiv.org/abs/2201.13189v2

Grawemeyer B; Halloran J; England M; Croft D, 2022, Feedback and Engagement on an Introductory Programming Module, https://arxiv.org/abs/2201.01240v1

Menviel L; Waugh DW; Spence P; Chamberlain M; Lago V; Li Z; England MH, 2021, Natural carbon release compensates for anthropogenic carbon uptake when Southern Hemispheric westerlies strengthen, http://dx.doi.org/10.1002/essoar.10508109.1

Abraham E; Davenport JH; England M; Kremer G, 2021, Proving UNSAT in SMT: The Case of Quantifier Free Non-Linear Real Arithmetic, https://arxiv.org/abs/2108.05320v1

Bradford R; Davenport JH; England M; Sadeghimanesh A; Uncu A, 2021, The DEWCAD Project: Pushing Back the Doubly Exponential Wall of Cylindrical Algebraic Decomposition, https://doi.org/10.1145/3511528.3511538

Florescu D; England M, 2020, A machine learning based software pipeline to pick the variable ordering for algorithms with polynomial inputs, https://doi.org/10.1007/978-3-030-52200-1_30

brahám EÁ; Davenport J; England M; Kremer G; Tonks Z, 2020, New Opportunities for the Formal Proof of Computational Real Geometry?, https://arxiv.org/abs/2004.04034v1

Sadeghimanesh A; England M, 2020, Polynomial Superlevel Set Representation of the Multistationarity Region of Chemical Reaction Networks, https://doi.org/10.1186/s12859-022-04921-6

Ábrahám E; Davenport JH; England M; Kremer G, 2020, Deciding the Consistency of Non-Linear Real Arithmetic Constraints with a Conflict Driven Search Using Cylindrical Algebraic Coverings, https://doi.org/10.1016/j.jlamp.2020.100633

Florescu D; England M, 2019, Improved cross-validation for classifiers that make algorithmic choices to minimise runtime without compromising output correctness, https://doi.org/10.1007/978-3-030-43120-4_27

Croft D; England M, 2019, Computing with CodeRunner at Coventry University: Automated summative assessment of Python and C++ code, https://doi.org/10.1145/3372356.3372357

Billings S; England M, 2019, First Year Computer Science Projects at Coventry University: Activity-led integrative team projects with continuous assessment, https://doi.org/10.1145/3372356.3372358

Florescu D; England M, 2019, Algorithmically generating new algebraic features of polynomial systems for machine learning, https://arxiv.org/abs/1906.01455v1

England M; Florescu D, 2019, Comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition, https://doi.org/10.1007/978-3-030-23250-4_7

England M; Bradford R; Davenport JH, 2019, Cylindrical Algebraic Decomposition with Equational Constraints, https://doi.org/10.1016/j.jsc.2019.07.019

Bradford R; Davenport JH; England M; Errami H; Gerdt V; Grigoriev D; Hoyt C; Kosta M; Radulescu O; Sturm T; Weber A, 2019, Identifying the Parametric Occurrence of Multiple Steady States for some Biological Networks, https://doi.org/10.1016/j.jsc.2019.07.008

Deshpande S; Shuttleworth J; Yang J; Taramonli S; England M, 2019, PLIT: An alignment-free computational tool for identification of long non-coding RNAs in plant transcriptomic datasets, https://doi.org/10.1016/j.compbiomed.2018.12.014

Croft D; England M, 2018, Computing with Codio at Coventry University: Online virtual Linux boxes and automated formative feedback, https://doi.org/10.1145/3294016.3294018

Alayba AM; Palade V; England M; Iqbal R, 2018, A Combined CNN and LSTM Model for Arabic Sentiment Analysis, https://doi.org/10.1007/978-3-319-99740-7_12

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