Jonathan S

[Jonathan S @JonStie]

@svpino Can I still join if I miss the first lecture?

[Jonathan S @JonStie]

🎮 Check out the demo – train on three clients using the BCSS dataset! 📈 Integrated AIM support makes logging and visualizing results super easy.

🔜 Theoden is evolving! Stay tuned for regular updates as we continue to push the boundaries! 🚀👩‍🔬👨‍💻 #FederatedLearning

[Jonathan S @JonStie]

🚀 Exciting news! Introducing #Theoden 🧠🌐 - The Open Distributed Learning Environment! 🏥🔬

With @NBabendererde, @mofuchs1, @anirbanakash #MECLabTUDA, @CS_TUDarmstadt

🐙https://t.co/lnK61RiiTQ

[Jonathan S @JonStie]

Tackling the intricate world of cross-silo federated learning in medical data 🩺💻, Theoden is your go-to research framework!

✨ Flexible: Easily incorporate new data, models, and methods without framework tweaks! 🛠️

Thank you @BMBF_Bund for the support.

[Anirban Mukhopadhyay @anirbanakash]

𝙁𝙀𝘿-𝙋𝘼𝙏𝙃 Kick-off: a nation-wide🇩🇪 federated learning infrastructure for privacy-preserving computational #oncopathology. Joint effort across 4 pathology depts (@UKKoeln, @unimedhal, @UKL_Leipzig @UniklinikEssen) & @CS_TUDarmstadt, @Hessian_AI.🙏@BMBF_Bund for the support.

[Jonathan S @JonStie]

I am happy to announce that I have graduated with honors from the @TUDarmstadt with a Master's degree in Computer Science and am now starting my #PhD at #MECLabTUDA of @anirbanakash.
I will be researching in the field of #digitalpathology and decentralized learning.

[Yuri Tolkach @y_tolkach]

We have just started a large computational challenge: SemiCOL Challenge. https://t.co/avcbmYqAhP

@ESDIPatho #DigitalPathology #ComputationalPathology @MICCAI_Society @TIAwarwick @jnkath @twittlabs @AI4Pathology @nmrajpoot @anirbanakash @DGPatho @ViktorKoelzer #ECDP2023

[Moritz Fuchs @mofuchs1]

It is in great fear, not knowing what mighty artefact may appear, wield FrOoDo and evaluate artefacts in an easy and adaptable way.🔬🧫

So if you are in London at @The_CBIAS:
Let's meet and chat.

#MECLabTUDA #CBIAS2022 #microscopy
🧩https://t.co/fHczBAOiQg

[Anirban Mukhopadhyay @anirbanakash]

Thank you @ElckeVels for writing such a balanced feature about our research on #Medical #AI @CS_TUDarmstadt & @Hessian_AI. A super team effort of many including @le_hekr, @kueglerd, @camgbus, @kalkjo, @mofuchs1, @JonStie, @amin_ranem et al.

[Moritz Fuchs @mofuchs1]

Speak friend and clone the github repo for the latest feature update.
To detect untrained creatures from a different age FrOoDo now supports classification and many more.

@JonStie, @anirbanakash, @CS_TUDarmstadt
#MECLabTUDA
🧩https://t.co/fHczBAwHYI
📄 https://t.co/CvwMM2M6PL

[Camila González @camgbus]

It was great to see to much traffic for both our posters! 😁 Reach out if you have any further questions

[Anirban Mukhopadhyay @anirbanakash]

Thank you to the Hoch3 team to cover our research on #surgical #ai in such a balanced fashion!
A team effort from #MECLAbTUDA @CS_TUDarmstadt members: @le_hekr, @kueglerd, @mofuchs1, Johannes Fauser, @DhritimaanDas1 and many more.

[Moritz Fuchs @mofuchs1]

🔥The shire is burning silently. So FrOoDo goes to MOOrDor.🔥
FrOoDo is a Framework for Out-of-Distribution Detection. We demonstrate its usefulness for computational pathology.
With @JonStie, @y_tolkach & @anirbanakash #MECLabTUDA, @CS_TUDarmstadt
🧩https://t.co/fHczBAwHYI