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 majoring in theoretical computer science and minoring in machine learning.
From making a simple phone call to airlines scheduling thousands of flights, without modern algorithms such as probabilistic primality tests, the fast fourier transform or interior point methods our society would look vastly different. Solving hard real world problems with algorithmic tools is something that absolutely fascinates me.
I am an algorithms person who is especially interested in taking ideas from theoretical computer science and machine learning and applying them to real world problems. My two focus areas are:
- Understanding the Inner Machinery of Machine Learning.
- Self-Supervised Representation Learning
- Explainable AI
- Combining Machine Learning with Quantitative Social Sciences.
- e.g. Algorithmic Fairness
Though, I work on a lot of other topics too.
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
Startup / Industry
If you are in need of an AI fairness audit or would like to collaborate please do not hesitate and 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: