Sondre Engebråten Developer, Scientist and Tinkerer

About Me Projects

My Expertise

Full stack should not just be about backend and frontend. Full stack should include everything from the hardware to the user experience. With a background in Computer Science and a passion for hardware, I am a developer, scientist and tinkerer. Exploring the world of evolutionary computing and artificial intelligence, I am always looking for new problems to solve.

AI and robotics

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ROS seamlessly links disparate system components, while evolutionary methods untangle the most complex challenges. Furthermore, it's the local interplay between elements that enables the emergence and operation of swarm intelligence.

Code

Python for fast prototyping and data analysis. C++ for high performance, low level and hardware near programming. Golang for fun!

Tools

Everything in Git. Docker lets you move fast. Amazon lets you scale to infinity.

Featured Projects

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A multi-tasking drone swarm

  • Control theory
  • Unmanned aerial vehicles
  • Distributed systems

Together several drones can solve tasks that are too big or complex for any single drone. In this project a multi-function drone swarm capable of solving multiple tasks concurrently was created. The drone swarm was capable of creating a communication network, exploring an area, and geolocating radio frequency emitters at the same time.

Check it out
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Mountable cloud storage (B2Fuse)

  • Linux low level coding
  • Cloud storage

Bucket like storage like Backblaze B2 and Amazon S3 is great, but wouldn't it be even better if you could use it as just another folder? B2Fuse enables you to mount a bucket as if it was just another network share and use all your favourite tools.

Check it out
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Evolutionary optimization

  • Heuristic optimization
  • Open-ended evolutionary methods
  • Emergent behaviors

How do humans learn? We usually harness our past experiences and employ heuristics as a guide, adopting a trial-and-error method to navigate through uncharted problems. This approach not only yields solutions but also generates new knowledge. Evolutionary methods mirror this learning paradigm in artificial intelligence. By simulating the processes of natural selection within computational models, they equip computers to address and solve intricate issues that are intractable for standard algorithms.

Check it out