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stes Goto Github PK

followers: 224.0 following: 109.0 repos: 112.0 gists: 10.0

Name: Steffen Schneider

Type: User

Company: @dynamical-inference @ki-macht-schule @kinematik-ai

Bio: PI @dynamical-inference lab | AI for life sciences | Co-Founder @ki-macht-schule & @kinematik-ai | ex-@google PhD fellow, ex- @facebookresearch &@aws

Twitter: stes_io

Location: Munich

Blog: stes.io

Hi, I'm Steffen πŸ‘‹

My goal is to build machine learning tools and statistical methods for decompiling intelligent behavior. In my research group at Helmholtz Munich, we develop machine learning algorithms for representation learning and inference of nonlinear system dynamics, study how large and multi-modal biological datasets can be compressed into foundation models, and study their mechanistic interpretability.

If you are looking for opportunities for a position as a PhD student, postdoc, research engineer, research assistant, or an internship, Bachelor or Master’s thesis, please have a look at our current openings and ping me if you’re interested in working with us.

For science outreach, I co-founded KI macht Schule, a non-profit organization teaching ML basics to high-school students. We provide teachers with modern teaching materials, AI tools and infrastructure in our open teaching hub, and offer courses on AI for students and teachers in Germany, Switzerland and Austria.

I am also co-founder and CTO of Kinematik AI, a company offering customized machine intelligence solutions in the biopharma and animal healthcare sector.

Here are some pointers to my work:

  • πŸ§‘β€πŸŽ“ Interested in my research? Have a look at stes.io or my google scholar profile.
  • πŸ¦“ Check out cebra, our new representation learning algorithm to obtain embeddings of jointly recorded behavioral & neural data.
  • β˜• Check out robusta, our library for robustness & adaptation.
  • πŸŽ’ Check out how we teach ML & AI to highschool students at KI macht Schule.
  • πŸ’Ό Get in touch if you are interested in what we are building at Kinematik AI.
  • 🐦 Follow me on X: @stes_io
  • 🐘 ... and mastodon: @[email protected]

Steffen Schneider's Projects

acquisition icon acquisition

Code for implementing the Image Acquisition Pipeline

appmode icon appmode

A Jupyter extensions that turns notebooks into web applications.

arch-deepspeech icon arch-deepspeech

Arch Linux packages to install CPU versions of Mozilla's Deep Speech implementation

assembled-cnn icon assembled-cnn

Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"

audio icon audio

simple audio I/O for pytorch

awesome-pytorch-list icon awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

bci icon bci

Brain Computer Interfaces

beyondpagerank icon beyondpagerank

Studienstiftung Winterakademie 2017: Supplementary Material for talk about PageRank

biomodels icon biomodels

Website and Material for the Biomodels Retreat 2017

blog icon blog

Github Pages Repo for blog entries on stes.github.io

caiman icon caiman

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

ccc icon ccc

Code for Continuously Changing Corruptions (CCC) benchmark + evaluation

cebra-fork icon cebra-fork

Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA

clip icon clip

Contrastive Language-Image Pretraining

datasets icon datasets

A curated list of datasets and pre-trained deep learning models useful for machine learning research

deeplabcut icon deeplabcut

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals

deepml icon deepml

Collection of snippets related to deep learning

deepspeech icon deepspeech

A TensorFlow implementation of Baidu's DeepSpeech architecture

delpy icon delpy

Blockly on Jupyter Notebook with Python

dino-1 icon dino-1

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

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