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Studying Computer Science at KTH Royal Institute of Technology
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Studying Computer Science at KTH Royal Institute of Technology
  • Student at KTH Royal Institute of Technology
  • Stockholm, Sweden
  • 03:55 (UTC +01:00)
  • LinkedIn in/emil-ståhl-6bb423b7

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emilstahl97/README.md

Emil Ståhl

hello

Full-Stack Engineer

As an M.Sc.Eng. student in Software Engineering of Distributed Systems at KTH Royal Institute of Technology, I have specialized in the areas of networking and automation. I am dedicated to leveraging technology as a deflationary tool, empowering people and organizations to drive innovation and progress. My passion lies in developing cutting-edge technology that propels humanity towards a brighter future and promotes global economic growth for the benefit of all. With a firm belief in the power of technology to transform the world, I am committed to creating solutions that make a positive impact on society.

For a comprehensive overview of the courses I have completed at KTH, please refer to my complete course list available here.

  • 🌍 I'm based in Stockholm
  • ✉️ You can contact me at emilstah@kth.se
  • 🚀 I'm currently working on Verbalizer
  • 🧠 I'm currently learning Swift and iOS Development

Skills

My Skills

Socials

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  1. Open-vSwitch-with-Coflow-Aware-Prediction Open-vSwitch-with-Coflow-Aware-Prediction Public

    Performance benchmark of Open vSwitch with perfect knowledge of future flows

    C

  2. Performance-analysis-of-the-FRRouting-Route-Server Performance-analysis-of-the-FRRouting-Route-Server Public archive

    Degree project researching the performance of FRRouting with a set of experiments using ExaBGP and Wireshark

    Shell

  3. Data-Intensive-Computing-ID2221 Data-Intensive-Computing-ID2221 Public archive

    The course complements distributed systems courses, with a focus on processing, storing and analyzing massive data.

    Jupyter Notebook 2 1

  4. Scalable-Machine-Learning-and-Deep-Learning-ID2223 Scalable-Machine-Learning-and-Deep-Learning-ID2223 Public archive

    The course studies fundamentals of distributed machine learning algorithms and the fundamentals of deep learning. We will cover the basics of machine learning and introduce techniques and systems t…

    Jupyter Notebook 1 2

  5. Operating-Systems-ID1206 Operating-Systems-ID1206 Public archive

    The course provides knowledge of the principles of and how one can implement abstractions of hardware virtualisation of resources and timetabling of assignments; mainly as regards execution, memory…

    C 1

  6. Distributed-Systems-ID2201 Distributed-Systems-ID2201 Public archive

    The course covers fundamental models for distributed systems, inter process communication and how to handle synchronization, consistency, replication, fault tolerance and security in a distributed …

    Erlang 2 3