Elizaveta Semenova

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Lecturer

Imperial College London

United Kingdom

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About

Elizaveta Semenova is a Lecturer at Imperial College London, United Kingdom. Her research focuses on the application of artificial intelligence in modeling infectious disease epidemics, Bayesian methods for transmission dynamics, and health inequities as they relate to COVID-19. She has contributed to various studies examining global trends in physical activity and genomic surveillance related to SARS-CoV-2.

Recent Grants

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Schmidt Futures AI2050 Early Career Fellowship

Open Date: 2023-03-01

Close Date: 2024-12-01

Articles (16)

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Collaborators (15)

Jacob Curran-Sebastian

Københavns Universitet

DENMARK

Elizaveta Semenova

Research Interests

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About

Recent Grants

Articles (16)

Artificial intelligence for modelling infectious disease epidemics

Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models

National, regional, and global trends in insufficient physical activity among adults from 2000 to 2022: a pooled analysis of 507 population-based surveys with 5·7 million participants

SGLT2 inhibition improves coronary flow velocity reserve and contractility: role of glucagon signaling

The impact of health inequity on spatial variation of COVID-19 transmission in England

Assessment of COVID-19 as the Underlying Cause of Death Among Children and Young People Aged 0 to 19 Years in the US

PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation

Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Author Correction: Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Global disparities in SARS-CoV-2 genomic surveillance

The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity

Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England

Flexible Fitting of PROTAC Concentration–Response Curves with Changepoint Gaussian Processes

Asymptotic Equations of Gas Dynamics: Qualitative Analysis, Construction of Solutions, and Applications

Bayesian workflow for disease transmission modeling in Stan

Track Omicron's spread with molecular data

Collaborators (15)

Jacob Curran-Sebastian

Christopher Dye

Judith Bouman

Samir Bhatt

Seth Flaxman

Deepti Gurdasani

William Souza

Anthony Hauser

Gavin Leech

Andreza Aruska de Souza Santos

Samantha Vanderslott

Mark Poulsen Khurana

S. L. Grimm

Neil Alexandre Scheidwasser

Swapnil Mishra

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