About Me (David Zollikofer)
Since some of my material might also be useful to others I have decided to create this humble website.
I am a computer science grad student at ETH Zürich with a background in theoretical computer science and machine learning.
My main interest is building robust and interpretable algorithms and AI models for solving real-world problems, believing that explainability and trustworthiness in AI is key for the future of human-AI interaction, as we need to understand and trust these systems.
For this I use methods from different fields:
- Machine Learning
- Trustworthy / Explainable / Interpretable AI
- Self-Supervised Learning
- Adversarial Methods
- Quantitative Social Sciences.
- Econometrics
- Algorithmic Fairness
Though, I have worked on a lot of other topics too.
Programming background
The following is a non-complete list of languages and frameworks I am experienced with:
- Professional: Java, Python
- Advanced: Go, LaTeX, C, PyTorch, Haskell
- Intermediate: C#, SQL, Tensorflow, Assembly (MIPS, x86), C++, Verilog, Scala, OCaml
- Beginner: PHP, JavaScript, R
Contact me
If you have a cool project idea please go ahead and contact me! I'd love to talk to you. For collaborations I have created a small site on what motivates me and how I like to work.
Feel free to reach out to me via any of the two mails below: