Przemyslaw (Przemek) Porebski

  • Research Scientist
Przemyslaw Porebski headshot
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Bio

Przemek Porebski is a research scientist in the Network Systems Science and Advanced Computing division. Before joining the Biocomplexity Institute at University of Virginia in 2020, he finalized the postdoctoral appointment at University of Virginia School of Medicine where he developed software and algorithms for structural biology.  

As a software developer, structural biologist and bioinformatician he contributed to diverse biomedical research fields such as antibiotic resistance, enzymology, cancer development, allergy and blood physiology. Among others he developed Molstack – a web-based platform for sharing and visualizing macromolecular models and experimental electron density and cryo-EM maps, CheckMyBlob  – a machine learning solution for the recognition and interpretation of electron density fragments and proteindiffraction.org - publicly available repository for raw experimental data for protein crystallography. 

  • Software development, interactive data visualization, data mining, data management 

  • Jagiellonian University, Krakow, Poland; Biotechnology, Structural Biology and Bioinformatics, M.S. 2009  

    Jagiellonian University, Krakow, Poland; Structural Biology and Bioinformatics, Ph.D. 2014  

    University of Virginia, Charlottesville, VA; Structural Biology, Postdoctoral 2015 

    Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences, Krakow, Poland; Biocatalysis, Postdoctoral 2017  

    University of Virginia, Charlottesville, VA; Structural Biology, Data Science, Postdoctoral 2020  

Network Systems Science and Advanced Computing
Article

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

Truelove S; Smith C; Qin M; Mullany L; Borchering R; Lessler J; Shea K; Howerton E; Contamin L; Levander J; Salerno J; Hochheiser H; Kinsey M; Tallaksen K; Wilson S; Shin L; Rainwater-Lovett K; Lemaitrem J; Dent J; Kaminsky J; Lee E; Perez-Saez J; Hill A; Karlen D; Chinazzi M; Davis J; Mu K; Xiong X; Piontti A; Vespignani A; Srivastava A; Porebski P; Venkatramanan S; Adiga Ani; Lewis B; Klahn B; Outten J; Schlitt J; Corbett P; Telionis A; Wang L; Peddireddy A; Hurt B; Chen J; Vullikanti A; Marathe M; Hoops S; Bhattacharya P; Machi D; Janies D; Thill J; Galanti M; Yamana T; Pei S; Shaman J; Reich N; Healy J; Slayton R; Biggerstaff M; Johansson M; Runge M; Viboud C . eLife. 2022; :11
Network Systems Science and Advanced Computing
Conference Proceeding

All models are useful: Bayesian ensembling for robust high resolution covid-19 forecasting

Adiga Ani; Wang L; Hurt B; Peddireddy A; Porebski P; Venkatramanan S; Lewis B; Marathe M . Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. ACM. 2021; :2505-2513
Network Systems Science and Advanced Computing
Report

Modeling of future COVID-19 cases, hospitalizations, and deaths, by vaccination rates and nonpharmaceutical intervention scenarios—United States, April–September 2021

Borchering R; Viboud C; Howerton E; Smith C; Truelove S; Runge M; Reich N; Contamin L; Levander J; Salerno J; van Panhuis W; Kinsey M; Tallaksen K; Obrecht F; Asher L; Costello C; Kelbaugh M; Wilson S; Shin L; Gallagher M; Mullany L; Rainwater-Lovett K; Lemaitre J; Dent J; Grantz K; Kaminsky J; Lauer S; Lee E; Meredith H; Perez-Saez J; Keegan L; Karlen D; Chinazzi M; Davis J; Mu K; Xiong X; Pastore Y Piontti A; Vespignani A; Srivastava A; Porebski P; Venkatramanan S; Adiga Ani; Lewis B; Klahn B; Outten J; Schlitt J; Corbett P; Telionis A; Wang L; Peddireddy A; Hurt B; Chen J; Vullikanti A; Marathe M; Healy J; Slayton R; Biggerstaff M; Johansson M; Shea K; Lessler J . Morbidity and Mortality Weekly Report. Centers for Disease Control and Prevention. 2021; 70(19):719-724
Network Systems Science and Advanced Computing
Conference Proceeding

From 5Vs to 6Cs: Operationalizing Epidemic Data Management with COVID-19 Surveillance

Peddireddy A; Xie D; Patil P; Wilson M; Machi D; Venkatramanan S; Klahn B; Porebski P; Bhattacharya P; Dumbre S; Raymond E; Marathe M . Proceedings of the 2020 IEEE International Conference on Big Data (Big Data). IEEE. 2020; :1380-1387