Machine Learning & Global Health Network

We are researchers in the U.K., Copenhagen and Singapore, founded in 2022. Working on: epi, health, phylo, Bayesian ML, computational stats, and more

[Machine Learning & Global Health Network @MLGlobalHealth]

Level up your forecasting game! 📈 Join the SPHERE-PPL team for the launch of our Forecasting Contest Series. Kick-off webinar details below:
🗓️ Monday, March 31st, 2025 at 3 PM GMT 🔗 [Registration Link]
Details: https://t.co/DTIGBBPb73

#Skills #Learning #ForecastingContest

[Machine Learning & Global Health Network @MLGlobalHealth]

Predict the future of Lyme disease in the UK. Join our forecasting contest and help us better understand incidence rates.
Click here to learn more: https://t.co/DTIGBBPb73
#LymeDiseasePrediction #UKHealth #DataChallenge #GetInvolved

[MRC Centre for Global Infectious Disease Analysis @MRC_Outbreak]

New study published in @Nature Medicine estimates that in 2021, 2.9 million children (4.2%) in the United States had experienced the death of at least one parent or a grandparent caregiver responsible for most of the basic needs of the child
🧵1/3
https://t.co/H3blip3Fa6

[Machine Learning & Global Health Network @MLGlobalHealth]

We’re very excited to be teaching this course in Cape Town. Come and join us!

[AIMS South Africa @AIMSacza]

NEW short course: Modern Stats & ML for Population Health in Africa. Join us @AIMSacza in Cape Town for 1 week of Gaussian processes, compartmental models, phylogenetics, and hands-on Stan sessions with real data. Details: https://t.co/8nVB8AozVG

[Machine Learning & Global Health Network @MLGlobalHealth]

Many members of #MLGH attended IDM 2024 in Bangkok.
It was a great opportunity to share our work on health economics, vector borne diseases, social contacts and to connect with top minds around the world working in infectious disease modeling!

[Elizaveta Semenova @[email protected] @liza_p_semenova]

Big thanks to @alex_andorra & @ChrisWymant for a great #StanCon 2024 panel! We covered epidemiology vs biology, infectious diseases vs NCDs, generative emulators, graph GPs, sequential data collection, and, of course, #ProbabilisticProgramming.

[Machine Learning & Global Health Network @MLGlobalHealth]

Come see @molkjara poster at @ecmtb2024 to learn about non-Markovian Phylodynamics

[Machine Learning & Global Health Network @MLGlobalHealth]

Thanks to all the participants of our second MLGH day! @Imperial_Stats @LondMathSoc

[Machine Learning & Global Health Network @MLGlobalHealth]

Today we're at our second MLGH meetup @imperialcollege. We have Sydney Tucker kicking off talking about crisis methods for crisis settings

[Machine Learning & Global Health Network @MLGlobalHealth]

Next up, Xiaoyue Xi is presenting her work on leveraging node level information in network inference

[Machine Learning & Global Health Network @MLGlobalHealth]

@imperialcollege Here's Leonid Chindelevitch on antimicrobial resistance and ML

[Machine Learning & Global Health Network @MLGlobalHealth]

It's our second in-person MLGH day, today @imperialcollege! First up is Sydney Tucker on Hope groups https://t.co/tzezxwADT6