kla-s

Joined 4 years ago

Karma
43
Submissions
36
Member since
Nov 4
Interested in the world, looking for meaningful and impactful ml problems to solve. Intrigued bylarge action models for robotics/ interaction with reality. One dream of mine was/is to build a flight controller for an IMOCA which (due to the class rules) indirectly controls pitch -> ride height, bc the rules allow no elevator.

Want to talk about anything? -> [email protected]

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Recent submissions

Comment · 11 months ago
I wonder how routinely wearing compression socks interacts with this proposed mechanism.

Always thought it interesting that for certain diagnosis wearing them until end of life is indicated according to current guidelines and we don’t expect maladoption (weakening of the connective tissue). Id kind of prefer/would be interested in a workout based approach, also interesting what knock on effects such workout would have on the larger system

Comment · 1 year ago
Id also add that 5) We need some sense of truth.

Im not quite sure if the current paradigm of LLMs are robust enough given the recent Anthropic Paper about the effect of data quality or rather the lack thereof, that a small bad sample can poison the well and that this doesn’t get better with more data. Especially in conjunction with 4) some sense of truth becomes crucial in my eyes (Question in my eyes is how does this work? Something verifiable and understandable like lean would be great but how does this work with more fuzzy topics…).

Comment · 1 year ago
Stiction
Comment · 1 year ago
Do you care to explain more, id be interested :)
Comment · 1 year ago
I guess bioelectricity. Michael Levin is the guy to look at afaik.

Thanks @missedthecue, i wasn't aware this was productized and tested (though hoped it was)

Comment · 1 year ago
Any serious ideas for a recently removed glioblastom?
Comment · 1 year ago
Whats your view on Cum-Ex?

And maybe as a Bonus what do you make of the smaller (relative) taxrate the bigger fish (companies/wealthier individuals) pay?

Comment · 1 year ago
Location: Munich, Germany

Remote: Yes

Willing to relocate: Yes

Technologies: Python (PyTorch, TensorFlow), Reinforcement Learning, Medical Imaging, Machine Unlearning, Physics-informed ML, Quantum Computing, Protein Structure Prediction, NLP, Java, SQL

Résumé/CV: https://drive.google.com/file/d/1b9UfeqFvEu0t4sTGNd8yiJ1m60x...

Email: [email protected]

Hi, Kilian here :) ML engineer / research-minded generalist with a recent M.Sc. in Informatics from TUM, including a thesis on machine unlearning in medical imaging (@Harvard Medical School). I’ve worked on problems like reinforcement learning for tumor landmark detection in MRI, and deep learning for physical systems and protein structure prediction.

I like forming own ideas and following them through — from literature review to implementation, evaluation, and iteration. I can reproduce papers, fine-tune models, explore new methods, and design experiments that actually test hypotheses. I’m especially motivated by early-stage work that blends research thinking with practical engineering.

In team settings, I tend to gravitate toward coordination and planning roles, and outside of work, I’ve led a 300+ member volleyball department for several years — which taught me how to manage people, not just models.

I'm looking for roles at the intersection of research and engineering, eg early-stage AI projects where curiosity, ownership, technical depth matter and impact-driven development are valued.

Comment · 1 year ago
Wow that video is awesome, thanks for sharing
Comment · 1 year ago
To add some nuance, unused/unnecessary sugar will cause diabetes. If you are in high cardiovascular load consuming more than you can take in as eg with long distance triathlon, to my knowledge you will not increase your diabetes risk. It's more a matching supply and demand thing.
Comment · 1 year ago
Genuine question, how does multi step reasoning work for you then? Like eg if you have some math problem that's trivially to solve individually but needs multiple steps, lets say 16 * 3 + 5? How does 16 * 3 = 48 land in some 'register' of your brain (short term memory), so that you can then add 5 to get to 53? Maybe 16 * 3 + 5 is to easy for you and you'll just 'see' it but the question still stands, just choose a more complex problem.

Isn't the same meta process at play when thinking about more fuzzy topics?

Comment · 1 year ago
Thank you, for making the effort of making this so accessible! Danke :)
Comment · 1 year ago
Well then thats „Volksabstimmungen“ as Switzerland has it for you.

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