| Modelling transmission and control of the COVID-19 pandemic in Australia SL Chang, N Harding, C Zachreson, OM Cliff, M Prokopenko Nature Communications 11, 5710, 2020 | 739 | 2020 |
| Online localization of radio-tagged wildlife with an autonomous aerial robot system OM Cliff, R Fitch, S Sukkarieh, D Saunders, R Heinsohn Robotics: Science and Systems, 2015 | 309 | 2015 |
| Dec-MCTS: Decentralized planning for multi-robot active perception G Best, OM Cliff, T Patten, RR Mettu, R Fitch The International Journal of Robotics Research 38 (2-3), 316–337, 2019 | 224 | 2019 |
| Investigating spatiotemporal dynamics and synchrony of influenza epidemics in Australia: an agent-based modelling approach OM Cliff, N Harding, M Piraveenan, EY Erten, M Gambhir, M Prokopenko Simulation Modelling Practice and Theory 87, 412 -- 431, 2018 | 99 | 2018 |
| Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model C Zachreson, KM Fair, OM Cliff, N Harding, M Piraveenan, M Prokopenko Science advances 4 (12), eaau5294, 2018 | 84 | 2018 |
| Robotic ecology: Tracking small dynamic animals with an autonomous aerial vehicle OM Cliff, DL Saunders, R Fitch Science Robotics 3 (23), eaat8409, 2018 | 66 | 2018 |
| How will mass-vaccination change COVID-19 lockdown requirements in Australia? C Zachreson, SL Chang, OM Cliff, M Prokopenko The Lancet Regional Health – Western Pacific 14, 100224, 2021 | 62 | 2021 |
| Decentralised Monte Carlo tree search for active perception G Best, OM Cliff, T Patten, RR Mettu, R Fitch Algorithmic Foundations of Robotics XII 13, 864-879, 2020 | 48 | 2020 |
| Assessing the significance of directed and multivariate measures of linear dependence between time series OM Cliff, L Novelli, BD Fulcher, JM Shine, JT Lizier Physical Review Research 3 (1), 013145, 2021 | 45* | 2021 |
| Simulating transmission scenarios of the Delta variant of SARS-CoV-2 in Australia S Chang, O Cliff, C Zachreson, M Prokopenko Frontiers in Public Health 10, 2022 | 33* | 2022 |
| Minimising the Kullback–Leibler divergence for model selection in distributed nonlinear systems OM Cliff, M Prokopenko, R Fitch Entropy 20 (2), 51, 2018 | 33 | 2018 |
| Quantifying long-range interactions and coherent structure in multi-agent dynamics OM Cliff, JT Lizier, XR Wang, P Wang, O Obst, M Prokopenko Artificial life 23 (1), 34-57, 2017 | 33* | 2017 |
| Unifying pairwise interactions in complex dynamics OM Cliff, JT Lizier, N Tsuchiya, BD Fulcher arXiv preprint arXiv:2201.11941, 2022 | 28 | 2022 |
| Towards quantifying interaction networks in a football match OM Cliff, JT Lizier, XR Wang, P Wang, O Obst, M Prokopenko RoboCup 2013: Robot World Cup XVII 8371, 2014 | 28 | 2014 |
| A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers J Thompson, R McClure, N Scott, M Hellard, R Abeysuriya, ... Health Research Policy and Systems 20 (1), 107, 2022 | 21 | 2022 |
| An information criterion for inferring coupling of distributed dynamical systems OM Cliff, M Prokopenko, R Fitch Frontiers in Robotics and AI 3 (71), 2016 | 17 | 2016 |
| Adversarial patrolling with reactive point processes B Hefferan, OM Cliff, R Fitch Australian Conference on Robotics and Automation (ACRA), 2016 | 16 | 2016 |
| Network properties of salmonella epidemics OM Cliff, V Sintchenko, TC Sorrell, K Vadlamudi, N McLean, ... Scientific reports 9 (1), 6159, 2019 | 15 | 2019 |
| Gliders2013: Tactical analysis with information dynamics M Prokopenko, O Obst, P Wang, D Budden, OM Cliff RoboCup 2013 symposium and competitions: Team description papers, Eindhoven …, 2013 | 14 | 2013 |
| Genome-wide networks reveal emergence of epidemic strains of Salmonella Enteritidis AJ Svahn, SL Chang, RJ Rockett, OM Cliff, Q Wang, A Arnott, ... International Journal of Infectious Diseases 117, 65-73, 2022 | 9 | 2022 |
Mikhail ProkopenkoProfessor, Centre for Complex Systems, University of SydneyVerified email at sydney.edu.au
