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https://github.com/lukashedegaard/lukashedegaard

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https://github.com/lukashedegaard/lukashedegaard

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## 👋 Hi, I'm Lukas Hedegaard

ML Engineer at InCommodities, with a research background in __Deep Learning__, __network acceleration__ and __Transfer Learning__. Academic works include:
- [![Paper](http://img.shields.io/badge/paper-arxiv.2211.10155-B31B1B.svg)](https://arxiv.org/abs/2211.10155) [Hedegaard et al.: "Structured Pruning Adapters"](https://github.com/LukasHedegaard/structured-pruning-adapters) (Pattern Recognition, 2024)
- [![Paper](http://img.shields.io/badge/paper-arxiv.2203.11009-B31B1B.svg)](https://arxiv.org/abs/2203.11009) [Hedegaard et al.: "Continual Spatio-Temporal Graph Convolutional Networks](https://github.com/LukasHedegaard/continual-skeletons) (Pattern Recognition, 2023)
- [![Paper](http://img.shields.io/badge/paper-arxiv.2201.06268-B31B1B.svg)](http://arxiv.org/abs/2201.06268) [Hedegaard et al.: "Continual Transformers: Redundancy-Free Attention for Online Inference"](https://github.com/LukasHedegaard/continual-transformers) (ICLR, 2023)
- [![Paper](http://img.shields.io/badge/paper-arxiv.2106.00050-B31B1B.svg)](https://arxiv.org/abs/2106.00050) [Hedegaard & Iosifidis: "Continual 3D Convolutional Neural Networks for Real-time Processing of Videos"](https://github.com/LukasHedegaard/co3d) (ECCV, 2022)
- [![Paper](http://img.shields.io/badge/paper-arxiv.2204.03418-B31B1B.svg)](https://arxiv.org/abs/2204.03418) [Hedegaard & Iosifidis: "Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch"](https://github.com/LukasHedegaard/continual-inference) (ECCV workshop, 2022)
- [![Paper](http://img.shields.io/badge/paper-arxiv.2004.11262-B31B1B.svg)](https://arxiv.org/abs/2004.11262) [Hedegaard et al.: "Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol"](https://github.com/LukasHedegaard/dage) (Transactions on Image Processing, 2021)
- [![Paper](http://img.shields.io/badge/paper-arxiv.2003.04063-B31B1B.svg)](https://arxiv.org/abs/2003.04063) [Hedegaard et al.: "Supervised Domain Adaptation using Graph Embedding"](https://github.com/LukasHedegaard/dage) (ICPR, 2021)
- [![Paper](http://img.shields.io/badge/Elsevier-Chapter4-FE6C02.svg)](https://www.sciencedirect.com/book/9780323857871/deep-learning-for-robot-perception-and-cognition) [Heidari et al.: "Graph Convolutional Networks"](https://www.sciencedirect.com/science/article/pii/B9780323857871000099) (Deep Learning for Robot Perception and Cognition, 2022)
- [![Paper](http://img.shields.io/badge/Elsevier-Chapter14-FE6C02.svg)](https://www.sciencedirect.com/book/9780323857871/deep-learning-for-robot-perception-and-cognition) [Hedegaard et al.: "Human Activity Recognition"](https://www.sciencedirect.com/science/article/pii/B9780323857871000191) (Deep Learning for Robot Perception and Cognition, 2022)



Apart from doing ML research projects (like real-time Human Activity Recognition using [CoX3D](https://github.com/LukasHedegaard/co3d) ☝️), I like to package code up nicely and open-source whenever it may be of value.
__Open-source__ libraries include:
- [Continual Inference](https://github.com/LukasHedegaard/continual-inference) [🐍, C++] ![downloads](https://static.pepy.tech/badge/continual-inference) - _Building blocks for Continual Inference Networks in PyTorch._
- [Ride](https://github.com/LukasHedegaard/ride) [🐍] ![downloads](https://static.pepy.tech/badge/ride) - _Training wheels, side rails, and helicopter parent for your Deep Learning projects in PyTorch._
- [OpenDR](https://github.com/opendr-eu/opendr) [🐍, C++] ![downloads](https://static.pepy.tech/badge/opendr) - _A modular, open and non-proprietary toolkit for core robotic functionalities by harnessing deep learning._
- [DatasetOps](https://github.com/LukasHedegaard/datasetops) [🐍] ![downloads](https://static.pepy.tech/badge/datasetops) - _Fluent dataset operations, compatible with your favorite libraries._
- [PyTorch Benchmark](https://github.com/LukasHedegaard/pytorch-benchmark) [🐍] ![downloads](https://static.pepy.tech/badge/pytorch-benchmark) - _Easily benchmark PyTorch model FLOPs, latency, throughput, allocated gpu memory and energy consumption._
- [Co-Rider](https://github.com/LukasHedegaard/co-rider) [🐍] ![downloads](https://static.pepy.tech/badge/corider) - _Tiny configuration library tailored for the Ride ecosystem._
- [Supers](https://github.com/LukasHedegaard/supers) [🐍] ![downloads](https://static.pepy.tech/badge/supers) - _Call a function in all superclasses using supers(self).foo(42)._
- [react-native-svg-pan-zoom](https://github.com/garblovians/react-native-svg-pan-zoom) [JS] ![downloads](https://img.shields.io/npm/dt/react-native-svg-pan-zoom.svg) - _Pan-zoom via two-finger "Google Maps"-style pinch and drag gestures._
- [redux-maybe](https://github.com/garblovians/redux-maybe) [JS] ![downloads](https://img.shields.io/npm/dt/redux-maybe.svg) - _Nodejs Package for attaching callback functions to redux messages._
- [redux-blabber](https://github.com/garblovians/redux-blabber) [JS] ![downloads](https://img.shields.io/npm/dt/redux-blabber.svg) - _Redux store enhancer for synchronizing states and actions across store instances._

## Find me 🌐
- ![LinkedIn](https://i.stack.imgur.com/gVE0j.png) [LinkedIn](https://www.linkedin.com/in/lukashedegaard/)
- 🎓 [Google Scholar](https://scholar.google.com/citations?user=15ovcOoAAAAJ&hl=en)
- 📫 [Email](mailto:[email protected])
- 🌍 [Aarhus, Denmark](https://www.google.com/maps?q=Aarhus,+Denmark)