| Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 T Vos, SS Lim, C Abbafati, KM Abbas, M Abbasi, M Abbasifard, ... The Lancet 396 (10258), 1204-1222, 2020 | 4199 | 2020 |
| Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 CJL Murray, AY Aravkin, P Zheng, C Abbafati, KM Abbas, ... The lancet 396 (10258), 1223-1249, 2020 | 3415 | 2020 |
| Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis CJL Murray, KS Ikuta, F Sharara, L Swetschinski, GR Aguilar, A Gray, ... The Lancet 399 (10325), 629-655, 2022 | 3049 | 2022 |
| Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic DF Santomauro, AMM Herrera, J Shadid, P Zheng, C Ashbaugh, ... The Lancet 398 (10312), 1700-1712, 2021 | 1817 | 2021 |
| Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic … H Wang, KM Abbas, M Abbasifard, M Abbasi-Kangevari, H Abbastabar, ... The Lancet 396 (10258), 1160-1203, 2020 | 791 | 2020 |
| Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21 H Wang, KR Paulson, SA Pease, S Watson, H Comfort, P Zheng, ... The Lancet 399 (10334), 1513-1536, 2022 | 736 | 2022 |
| Five insights from the global burden of disease study 2019 CJL Murray, C Abbafati, KM Abbas, M Abbasi, M Abbasi-Kangevari, ... The Lancet 396 (10258), 1135-1159, 2020 | 476 | 2020 |
| Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global … R Lozano, N Fullman, JE Mumford, M Knight, CM Barthelemy, C Abbafati, ... The Lancet 396 (10258), 1250-1284, 2020 | 410 | 2020 |
| Modeling COVID-19 scenarios for the United States Nature medicine 27 (1), 94-105, 2021 | 408 | 2021 |
| Pandemic preparedness and COVID-19: an exploratory analysis of infection and fatality rates, and contextual factors associated with preparedness in 177 countries, from Jan 1 … TJ Bollyky, EN Hulland, RM Barber, JK Collins, S Kiernan, M Moses, ... The Lancet 399 (10334), 1489-1512, 2022 | 221 | 2022 |
| Estimating global and regional disruptions to routine childhood vaccine coverage during the COVID-19 pandemic in 2020: a modelling study K Causey, N Fullman, RJD Sorensen, NC Galles, P Zheng, A Aravkin, ... The Lancet 398 (10299), 522-534, 2021 | 194 | 2021 |
| Estimated global proportions of individuals with persistent fatigue, cognitive, and respiratory symptom clusters following symptomatic COVID-19 in 2020 and 2021 SW Hanson, C Abbafati, JG Aerts, Z Al-Aly, C Ashbaugh, T Ballouz, ... JAMA 328 (16), 1604-1615, 2022 | 127 | 2022 |
| Sparse principal component analysis via variable projection NB Erichson, P Zheng, K Manohar, SL Brunton, JN Kutz, AY Aravkin SIAM Journal on Applied Mathematics 80 (2), 977-1002, 2020 | 116 | 2020 |
| A unified framework for sparse relaxed regularized regression: SR3 P Zheng, T Askham, SL Brunton, JN Kutz, AY Aravkin IEEE Access 7, 1404-1423, 2018 | 113 | 2018 |
| Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study KG Burkart, M Brauer, AY Aravkin, WW Godwin, SI Hay, J He, VC Iannucci, ... The Lancet 398 (10301), 685-697, 2021 | 96 | 2021 |
| A unified sparse optimization framework to learn parsimonious physics-informed models from data K Champion, P Zheng, AY Aravkin, SL Brunton, JN Kutz IEEE Access 8, 169259-169271, 2020 | 87 | 2020 |
| Parental education and inequalities in child mortality: a global systematic review and meta-analysis M Balaj, HW York, K Sripada, E Besnier, HD Vonen, A Aravkin, ... The Lancet 398 (10300), 608-620, 2021 | 75 | 2021 |
| Trimmed constrained mixed effects models: formulations and algorithms P Zheng, R Barber, RJD Sorensen, CJL Murray, AY Aravkin Journal of Computational and Graphical Statistics 30 (3), 544-556, 2021 | 71 | 2021 |
| Trimming the Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning J Yun, P Zheng, E Yang, A Lozano, A Aravkin International Conference on Machine Learning, 7242-7251, 2019 | 24* | 2019 |
| Relax-and-split method for nonconvex inverse problems P Zheng, A Aravkin Inverse Problems 36 (9), 095013, 2020 | 23* | 2020 |
Aleksandr AravkinUniversity of WashingtonVerified email at uw.edu
