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lecode-official/README.md

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Hi there 👋

My name is David. I'm a research scientist at Fraunhofer HHI, where I focus on developing efficient machine learning solutions. My research interests involve federated learning, recommender systems, neural network compression, and explainable AI, with a particular focus on developing novel techniques and algorithms.

I have a strong foundation in computer science, having completed my M.Sc. degree from Technical University of Berlin in 2019. Prior to joining the research community, I worked as a software engineer on large-scale projects for various industries.

In addition to machine learning, I'm interested in formal languages, automata, and compiler construction – topics that underpin many modern software systems. As someone with entrepreneurial experience, I value innovation and collaboration in driving technical solutions.

I'm currently pursuing my PhD while working on developing federated learning methods for highly personalized and privacy-focused recommender systems.

My GitHub Stats   My Most Used Languages

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  1. pytorch-federated-learning pytorch-federated-learning Public

    A federated learning simulator written in PyTorch, which supports a virtually unlimited number of clients.

    Python 6 2

  2. pytorch-lottery-ticket-hypothesis pytorch-lottery-ticket-hypothesis Public

    A PyTorch implementation of the Lottery Ticket algorithm introduced by Frankle et al. in "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" and enhanced by Zhou et al. in "D…

    Python 2

  3. virelay/virelay virelay/virelay Public

    ViRelAy is a visualization tool for the analysis of data as generated by CoRelAy.

    Python 27 5

  4. virelay/corelay virelay/corelay Public

    CoRelAy is a tool to compose small-scale (single-machine) analysis pipelines.

    Python 27 2