What are the main topics or questions that drive your research?

My research topics are mainly located in the field of information-theoretic security, particularly in the design of secure coding schemes using deep learning techniques. Additionally, I investigate means of making neural network-based communications systems more efficient and interpretable.

What inspired you to pursue your current field of work ?

The problem of communicating information is as old as humankind. Thanks to the discoveries in the field of Information Theory in the last century, we have some tools available to describe and quantify these processes in a mathematical manner, which can be challenging, yet beautiful. My goal is to expand on these tools and make use of them to shed some light on some recent issues such as secure communications and the interpretability of machine learning algorithms.

What excites you most about being part of CeTI?

I look forward to interesting cross-domain collaborations, learning what problems my peers are trying to solve and looking at my own research questions from a different angle.

Which challenge or question has recently sparked your curiosity?

I recently encountered training algorithms for neural networks that are more biologically plausible and thus could be implemented more efficiently than the current state-of-the-art. As energy consumption poses a crucial challenge for the broader adoption of machine learning solutions, this research direction holds great potential.

How do you like to recharge or spend your time outside of work?

I spend a lot of my free time listening to and making music. Moreover, I enjoy reading and doing sports such as running, badminton and yoga.