MrFernando Guntoro

I am a PhD student in the Epidemiology, Evolution and Control of Infectious Diseases Programme funded by the MRC Centre for Global Infectious Disease Analysis. My research focuses on the epidemiology and aetiology of COVID-19 through analysis of multi-omics data. I am particularly interested in the use of statistical computing and machine learning methods for analysing large data.

My previous work includes bayesian inference of SARS-CoV-2 prevalence using particle/sequential MCMC methods (Imperial); development of antimicrobial resistance prediction pipeline (Imperial); differential analysis and prediction of human prion diseases based on epigenomic profile (UCL); and heuristics methods for phylogenetic reconstruction (Edinburgh).

Publications
Guntoro, F. et al. “DNA methylation analysis of archival lymphoreticular tissues in Creutzfeldt–Jakob disease.” Acta Neuropathologica 144.4 (2022): 785-787.

Guntoro, F. et al. "Altered DNA methylation profiles in blood from patients with sporadic Creutzfeldt–Jakob disease." Acta neuropathologica 140.6 (2020): 863-879.

Stotzem, N., Guntoro, F. et al. "BenchmarkDR: A modular and expandable benchmarking pipeline for machine learning based antimicrobial resistance prediction.” Machine Learning for Microbial Genomics Conference (2022).

FitzJohn, R.G., Guntoro, F. et al. “Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate.” Wellcome Open Research 5 (2021).

Norsworthy, P., Guntoro, F. et al. "A blood miRNA signature associates with sporadic Creutzfeldt-Jakob disease diagnosis." Nature communications 11.1 (2020): 1-11.