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blog/blog_gsoc_2025.md

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@@ -30,15 +30,16 @@ Implementing Integrated Nested Laplace Approximations (INLA)
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![photo of Michael Novomestsky](../_static/gsoc_2025/michael-novomestsky.jpeg)
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![photo of Michael Novomestsky](../_static/gsoc_2025/michal-v2.png)
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**Bio**
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>I am a 4th year undergraduate BEng (Bachelor of Aerospace Engineering) (Honours) student at Monash University in Australia. My research interests can be summed up as “how can we embed priors/known information into AI/ML models?” and “how can we provide guarantees about their output?”. Bayesian ML is a promising direction to address these questions and is a key interest of mine.
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>I am a 4th year undergraduate student at Monash University in Australia, studying Aerospace Engineering (Honours). Although I come from a physics/engineering background in fluids, I have since shifted toward ML/AI as I have found some of the research directions in this space very exciting. My research interests can be summed up as “how can we embed priors/known information into AI/ML models?” and “how can we get them to reason and provide guarantees about their output?”. Bayesian ML is a promising direction to address these questions and is a key interest of mine.
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**Connecting**
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- Website: [michal-novomestsky.github.io/](https://michal-novomestsky.github.io/)
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- LinkedIn: [@michal-novomestsky](https://linkedin.com/in/michal-novomestsky)
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- GitHub: [@Michal-Novomestsky](https://github.com/Michal-Novomestsky)
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