Hi there

I'm a passionate AI Researcher, Mathematician and Data Scientist. I love to learn and contribute in any and every possible way.

🔭 I’m currently working on ... DNA diffusion, Gene expression and Geometric DL.
🌱 I’m currently learning ... MOJO🔥, LangChain and primitive colaborative AGI agents (#LearnToMine).
👯 I’m looking to collaborate on ... Anything where AI intercepts with Biology (Aging, DD...), Climat Change and Farming.
🤔 I’m looking for help with ... LINUX and VIM
💬 Ask me about ... anything and everythink, happy to have a chat.
📫 How to reach me: ... or
😄 Pronouns: ... all the way!
⚡ Fun fact: ... Fig trees eat bugs:bangbang: So don't be FEIGE and let's branch off into a grove of glitch-free greenery:heavy_exclamation_mark:

Top Technologies:

Jonas 's Projects

diffdock

Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

diffdock-pp

Implementation of DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models in PyTorch (ICLR 2023 - MLDD Workshop)

dna-diffusion

🧬 Understanding the code of life: Generative modeling of regulatory DNA sequences with diffusion probabilistic models 💨

equibind

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

This repository contains the implementation of a protein function prediction model, which harnesses the power of geometric deep learning (GeoDL) to predict protein functions. The project aims to address the protein function prediction problem by using GeoDL

gradientdecentonmanifolds

This project focuses on the exploration and implementation of the algorithmic approach of stochastic gradient descent on Riemannian manifolds. We aim to extend the classical gradient descent algorithm, traditionally applied in Euclidean space, to the context of Riemannian manifolds.