Filip Skogh ML Intern
IBM Research Z├╝rich

B

Filip
Skogh

I wish to understand why the world looks like it does, especially phenomena that stays with us over time, e.g. democracy, capitalism, patience, etc. We can understand why some phenomena come and go and why some stay with us by understanding stable distributions, fixed-points, the Nash equilibrium and eigenfunctions. Right now I'm studying machine learning to understand the differences in capability between human and machine, and with the goal to close the gap and conclude that no magic sauce is nessecary for HLI. Considering the progress so far (image recognition, text summarization, game playing, thought construction, grammar, etc.) I believe this is more likely than not.

Experience

IBM Research Zürich
2024
Machine Learning Intern

NLP in the AI for Scientific Discovery Lab

LOGIBLOX
2023
Machine Learning Intern

Building a LLM powered no-code platform.

ETH Computer Vision Lab
2023
Master's Thesis Student

Enabling large-scale video object segmentation models by reducing annotation requirements. Paper coming soon!

University of Massachusetts
2022
Distributed Systems Research Intern

Our paper received the Best Paper runner-up award on the 14th IEEE IGSC 2023 in Toronto, Canada.

We introduce a carbon aware scheduler that schedule tasks at data centers with low carbon intensity whilst minimizing the latency. Paper coming soon.

Orange Cyberdefense
2019 - 2021
Security Analyst

Threat response automation for 50.000+ endpoints in Python

SecureLink
2018
SecOps Intern

Kerberos and email security (Azure, DMARC, DKIM, SPF)