Roni Rosenfeld – MIDAS

Roni Rosenfeld

Professor

Education

Affiliations

Machine Learning Department, School of Computer Science, Carnegie Mellon University

Projects

DELPHI INFLUENZA FORECASTING CENTER OF EXCELLENCE

Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases
People: Roni Rosenfeld
2019 – 2024

MODELS & FORECASTS, COMPUTATIONAL MODELS OF INFECTIOUS DISEASE THREATS

National Institutes of Health, National Institute of General Medical Sciences
People: Roni Rosenfeld, Donald Burke
2009 – 2020

COMPUTATIONAL MODELS OF INFECTIOUS DISEASE THREATS

National Institutes of Health, National Institute of General Medical Sciences
People: Roni Rosenfeld, Derek Cummings, Mark Roberts, Donald Burke, Hasan Guclu, Jeanine Buchanich
2009 – 2020

Papers

Feder A, Vainstein D, Rosenfeld R, Hartman T, Hassidim A, Matias Y. (2020). Active Deep Learning to Detect Demographic Traits in Free-Form Clinical Notes. Journal of biomedical informatics

Reich NG, McGowan CJ, Yamana TK, Tushar A, Ray EL, Osthus D, Kandula S, Brooks LC, Crawford-Crudell W, Gibson GC, Moore E, Silva R, Biggerstaff M, Johansson MA, Rosenfeld R, Shaman J. (2019). Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S. PLoS computational biology, 15(11)

Reich NG, Osthus D, Ray EL, Yamana TK, Biggerstaff M, Johansson MA, Rosenfeld R, Shaman J. (2019). Reply to Bracher: Scoring probabilistic forecasts to maximize public health interpretability. Proceedings of the National Academy of Sciences of the United States of America, 116(42)

Reich NG, Brooks LC, Fox SJ, Kandula S, McGowan CJ, Moore E, Osthus D, Ray EL, Tushar A, Yamana TK, Biggerstaff M, Johansson MA, Rosenfeld R, Shaman J. (2019). A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States. Proceedings of the National Academy of Sciences of the United States of America, 116(8)

Baltrusaitis K, Vespignani A, Rosenfeld R, Gray J, Raymond D, Santillana M. (2019). Differences in Regional Patterns of Influenza Activity Across Surveillance Systems in the United States: Comparative Evaluation. JMIR public health and surveillance, 5(4)

Johansson MA, Apfeldorf KM, Dobson S, Devita J, Buczak AL, Baugher B, Moniz LJ, Bagley T, Babin SM, Guven E, Yamana TK, Shaman J, Moschou T, Lothian N, Lane A, Osborne G, Jiang G, Brooks LC, Farrow DC, Hyun S, Tibshirani RJ, Rosenfeld R, Lessler J, Reich NG, Cummings DAT, Lauer SA, Moore SM, Clapham HE, Lowe R, Bailey TC, García-Díez M, Carvalho MS, Rodó X, Sardar T, Paul R, Ray EL, Sakrejda K, Brown AC, Meng X, Osoba O, Vardavas R, Manheim D, Moore M, Rao DM, Porco TC, Ackley S, Liu F, Worden L, Convertino M, Liu Y, Reddy A, Ortiz E, Rivero J, Brito H, Juarrero A, Johnson LR, Gramacy RB, Cohen JM, Mordecai EA, Murdock CC, Rohr JR, Ryan SJ, Stewart-Ibarra AM, Weikel DP, Jutla A, Khan R, Poultney M, Colwell RR, Rivera-García B, Barker CM, Bell JE, Biggerstaff M, Swerdlow D, Mier-Y-Teran-Romero L, Forshey BM, Trtanj J, Asher J, Clay M, Margolis HS, Hebbeler AM, George D, Chretien JP. (2019). An open challenge to advance probabilistic forecasting for dengue epidemics. Proceedings of the National Academy of Sciences of the United States of America, 116(48)

Brooks LC, Farrow DC, Hyun S, Tibshirani RJ, Rosenfeld R. (2018). Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions. PLoS computational biology, 14(6)

Biggerstaff M, Johansson M, Alper D, Brooks LC, Chakraborty P, Farrow DC, Hyun S, Kandula S, McGowan C, Ramakrishnan N, Rosenfeld R, Shaman J, Tibshirani R, Tibshirani RJ, Vespignani A, Yang W, Zhang Q, Reed C. (2018). Results from the second year of a collaborative effort to forecast influenza seasons in the United States. Epidemics, (24)

Farrow DC, Brooks LC, Hyun S, Tibshirani RJ, Burke DS, Rosenfeld R. (2017). A human judgment approach to epidemiological forecasting. PLoS computational biology, 13(3)

Biggerstaff M, Alper D, Dredze M, Fox S, Fung IC, Hickmann KS, Lewis B, Rosenfeld R, Shaman J, Tsou MH, Velardi P, Vespignani A, Finelli L, . (2016). Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge. BMC infectious diseases, (16)

Poon LL, Song T, Rosenfeld R, Lin X, Rogers MB, Zhou B, Sebra R, Halpin RA, Guan Y, Twaddle A, DePasse JV, Stockwell TB, Wentworth DE, Holmes EC, Greenbaum B, Peiris JS, Cowling BJ, Ghedin E. (2016). Quantifying influenza virus diversity and transmission in humans. Nature genetics, 48(2)

Brooks LC, Farrow DC, Hyun S, Tibshirani RJ, Rosenfeld R. (2015). Flexible Modeling of Epidemics with an Empirical Bayes Framework. PLoS computational biology, 11(8)

Farrow DC, Burke DS, Rosenfeld R. (2015). Computational Characterization of Transient Strain-Transcending Immunity against Influenza A. PloS one, 10(5)

van Panhuis WG, Hyun S, Blaney K, Marques ET Jr., Coelho GE, Siqueira JB Jr., Tibshirani R, da Silva JB Jr., Rosenfeld R. (2014). Risk of dengue for tourists and teams during the World Cup 2014 in Brazil. PLoS neglected tropical diseases, 8(7)

Lukens S, DePasse J, Rosenfeld R, Ghedin E, Mochan E, Brown ST, Grefenstette J, Burke DS, Swigon D, Clermont G. (2014). A large-scale immuno-epidemiological simulation of influenza A epidemics. BMC public health, (14)

Grefenstette JJ, Brown ST, Rosenfeld R, DePasse J, Stone NT, Cooley PC, Wheaton WD, Fyshe A, Galloway DD, Sriram A, Guclu H, Abraham T, Burke DS. (2013). FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC Public Health, (13)

Lee BY, Brown ST, Cooley P, Grefenstette JJ, Zimmerman RK, Zimmer SM, Potter MA, Rosenfeld R, Wheaton WD, Wiringa AE, Bacon KM, Burke DS. (2010). Vaccination deep into a pandemic wave potential mechanisms for a "third wave" and the impact of vaccination. American journal of preventive medicine, 39(5)

Dreisigmeyer DW, Rosenfeld R, DePasse JV, Ghedin E, Price I, Clermont G. (2009). A multi-reservoir model of influenza evolution. Journal of critical care, 24(3)

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