| EpiFast: a fast algorithm for large scale realistic epidemic simulations on distributed memory systems KR Bisset, J Chen, X Feng, VSA Kumar, MV Marathe Proceedings of the 23rd international conference on Supercomputing, 430-439, 2009 | 279 | 2009 |
| Using data-driven agent-based models for forecasting emerging infectious diseases S Venkatramanan, B Lewis, J Chen, D Higdon, A Vullikanti, M Marathe Epidemics 22, 43-49, 2018 | 246 | 2018 |
| Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates and nonpharmaceutical intervention scenarios—United States, April–September 2021 RK Borchering, C Viboud, E Howerton, CP Smith, S Truelove, MC Runge, ... Morbidity and Mortality Weekly Report 70 (19), 719, 2021 | 181 | 2021 |
| Causalgnn: Causal-based graph neural networks for spatio-temporal epidemic forecasting L Wang, A Adiga, J Chen, A Sadilek, S Venkatramanan, M Marathe Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12191 …, 2022 | 160 | 2022 |
| Forecasting a moving target: Ensemble models for ILI case count predictions P Chakraborty, P Khadivi, B Lewis, A Mahendiran, J Chen, P Butler, ... Proceedings of the 2014 SIAM international conference on data mining, 262-270, 2014 | 115 | 2014 |
| Epidemiological and economic impact of COVID-19 in the US J Chen, A Vullikanti, J Santos, S Venkatramanan, S Hoops, H Mortveit, ... Scientific reports 11 (1), 1-12, 2021 | 108 | 2021 |
| DEFSI: Deep learning based epidemic forecasting with synthetic information L Wang, J Chen, M Marathe Proceedings of the AAAI Conference on Artificial Intelligence 33, 9607-9612, 2019 | 103 | 2019 |
| Simnest: Social media nested epidemic simulation via online semi-supervised deep learning L Zhao, J Chen, F Chen, W Wang, CT Lu, N Ramakrishnan 2015 IEEE International Conference on Data Mining, 639-648, 2015 | 93 | 2015 |
| Forecasting influenza activity using machine-learned mobility map S Venkatramanan, A Sadilek, A Fadikar, CL Barrett, M Biggerstaff, J Chen, ... Nature Communications 12 (1), 1-12, 2021 | 82 | 2021 |
| Learning everywhere: Pervasive machine learning for effective high-performance computation G Fox, J Glazier, JCS Kadupitiya, V Jadhao, M Kim, J Qiu, JP Sluka, ... 2019 IEEE International Parallel and Distributed Processing Symposium …, 2019 | 77 | 2019 |
| Understanding the coevolution of mask wearing and epidemics: A network perspective Z Qiu, B Espinoza, VV Vasconcelos, C Chen, SM Constantino, ... Proceedings of the National Academy of Sciences 119 (26), e2123355119, 2022 | 75 | 2022 |
| Calibrating a stochastic, agent-based model using quantile-based emulation A Fadikar, D Higdon, J Chen, B Lewis, S Venkatramanan, M Marathe SIAM/ASA Journal on Uncertainty Quantification 6 (4), 1685-1706, 2018 | 74 | 2018 |
| A framework for evaluating epidemic forecasts FS Tabataba, P Chakraborty, N Ramakrishnan, S Venkatramanan, ... BMC infectious diseases 17 (1), 345, 2017 | 74 | 2017 |
| Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints S Venkatramanan, J Chen, A Fadikar, S Gupta, D Higdon, B Lewis, ... PLoS computational biology 15 (9), e1007111, 2019 | 69 | 2019 |
| Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness J Chen, S Hoops, A Marathe, H Mortveit, B Lewis, S Venkatramanan, ... medRxiv, 2021 | 63 | 2021 |
| Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty E Howerton, L Contamin, LC Mullany, M Qin, NG Reich, S Bents, ... Nature communications 14 (1), 7260, 2023 | 56 | 2023 |
| Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination S Truelove, CP Smith, M Qin, LC Mullany, RK Borchering, J Lessler, ... Elife 11, e73584, 2022 | 50 | 2022 |
| Indemics An interactive high-performance computing framework for data-intensive epidemic modeling KR Bisset, J Chen, S Deodhar, X Feng, Y Ma, MV Marathe ACM Transactions on Modeling and Computer Simulation (TOMACS) 24 (1), 1-32, 2014 | 49 | 2014 |
| Meet and merge: Approximation algorithms for confluent flows J Chen, R Rajaraman, R Sundaram Journal of Computer and System Sciences 72 (3), 468-489, 2006 | 49 | 2006 |
| Minimum energy accumulative routing in wireless networks J Chen, L Jia, X Liu, G Noubir, R Sundaram Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and …, 2005 | 49 | 2005 |
Madhav MaratheDistinguished Professor, Biocomplexity-Institute, Dept. Computer Science, University of VirginiaVerified email at virginia.edu
