| Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation MJ Vassey, GP Figueredo, D Scurr, AS Vasilevich, S Vermeulen, A Carlier, ... Advanced Science, 2020 | 99 | 2020 |
| Deep Learning With Dynamically Weighted Loss Function for Sensor-Based Prognostics and Health Management D Rengasamy, M Jafari, B Rothwell, X Chen, GP Figueredo Sensors, 2020 | 83 | 2020 |
| Comparing stochastic differential equations and agent-based modelling and simulation for early-stage cancer GP Figueredo, PO Siebers, MR Owen, J Reps, U Aickelin PloS one 9 (4), e95150, 2014 | 80 | 2014 |
| Students’ views towards Sars-Cov-2 mass asymptomatic testing, social distancing and self-isolation in a university setting during the COVID-19 pandemic: A qualitative study H Blake, H Knight, R Jia, J Corner, JR Morling, C Denning, JK Ball, ... International journal of environmental research and public health 18 (8), 4182, 2021 | 79 | 2021 |
| Immune-instructive polymers control macrophage phenotype and modulate the foreign body response in vivo HM Rostam, LE Fisher, AL Hook, L Burroughs, JC Luckett, GP Figueredo, ... Matter 2 (6), 1564-1581, 2020 | 69 | 2020 |
| A Hybrid Deep Learning Approach for Driver Distraction Detection JM Mase, P Chapman, GP Figueredo, MT Torres The 11th International Conference on ICT Convergence, 2020 | 61 | 2020 |
| Evolving deep CNN-LSTMs for inventory time series prediction N Xue, I Triguero, GP Figueredo, D Landa-Silva 2019 IEEE Congress on Evolutionary Computation (CEC), 1517-1524, 2019 | 55 | 2019 |
| Short and Long term predictions of Hospital emergency department attendances T Jilani, G Housley, G Figueredo, PS Tang, J Hatton, D Shaw International journal of medical informatics 129, 167-174, 2019 | 50 | 2019 |
| Deep learning approaches to aircraft maintenance, repair and overhaul: A review D Rengasamy, HP Morvan, GP Figueredo 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 41 | 2018 |
| Discovery of (meth) acrylate polymers that resist colonization by fungi associated with pathogenesis and biodeterioration C Vallieres, AL Hook, Y He, VC Crucitti, G Figueredo, CR Davies, ... Science advances 6 (23), eaba6574, 2020 | 38 | 2020 |
| Evaluating the Impact of Heavy Goods Vehicle Driver Monitoring and Coaching to Reduce Risky Behaviour JM Mase, S Majid, M Mesgarpour, MT Torres, GP Figueredo, P Chapman Accident Analysis and Prevention 146, 2020 | 37 | 2020 |
| Benchmarking Deep Learning Models for Driver Distraction Detection JM Mase, P Chapman, GP Figueredo, MT Torres The Sixth International Conference on Machine Learning, Optimization, and …, 2020 | 31* | 2020 |
| Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom GP Figueredo, U Agrawal, JM Mase, M Mesgarpour, C Wagner, D Soria, ... IEEE Trans. Intell. Transp. Syst, 2018 | 31 | 2018 |
| On-lattice agent-based simulation of populations of cells within the open-source chaste framework GP Figueredo, TV Joshi, JM Osborne, HM Byrne, MR Owen Interface focus 3 (2), 20120081, 2013 | 30 | 2013 |
| Novel in vitro diagnosis of equine allergies using a protein array and mathematical modelling approach: a proof of concept using insect bite hypersensitivity E Marti, X Wang, NN Jambari, C Rhyner, J Olzhausen, JJ Pérez-Barea, ... Veterinary immunology and immunopathology 167 (3-4), 171-177, 2015 | 29 | 2015 |
| Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective GP Figueredo, PO Siebers, U Aickelin BMC bioinformatics 14 (6), 1-20, 2013 | 28 | 2013 |
| Comparing system dynamics and agent-based simulation for tumour growth and its interactions with effector cells GP Figueredo, U Aickelin arXiv preprint arXiv:1108.3235, 2011 | 23 | 2011 |
| Discovery of Synergistic Material-Topography Combinations to Achieve Immunomodulatory Osteoinductive Biomaterials using a novel in vitro screening method: the ChemoTopoChip L Burroughs, MH Amer, M Vassey, B Koch, GP Figueredo, ... Biomaterials, 120740, 2021 | 22 | 2021 |
| Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion D Rengasamy, BC Rothwell, GP Figueredo Applied Sciences 11 (24), 11854, 2021 | 21 | 2021 |
| Machine learning to determine the main factors affecting creep rates in laser powder bed fusion S Sanchez, D Rengasamy, CJ Hyde, GP Figueredo, B Rothwell Journal of Intelligent Manufacturing, 2021 | 18 | 2021 |
Winkler, D*CSIRO or Monash or La Trobe or Defence or Nottingham or PharmacyVerified email at latrobe.edu.au
