Amir Joudaki

I’m a doctoral candidate in the Biomedical Informatics (BMI) group at ETH, where I work on mathematical foundations of neural networks, and biomedical applications of AI. Before joining ETH, I earned a BSc in Computer Engineering from Sharif University, an MPhil in Cognitive Neuroscience at SISSA, Italy, and an MSc in Computer Science from ETH Zurich. You can find my CV here.

Research vision

We stand at the dawn of a technological and scientific revolution, with AI as its center. Despite its potential, our understanding of advanced AI systems is still very limited, as revealed by the following fact: the human brain, the inspiration behind modern neural networks, operates on a mere 12 watts, in stark contrast to the megawatts consumed by advanced neural networks. Therefore, state-of-the-art neural networks burn millions of times more power and data than a biological brain while coming short of simple reasoning and common sense tasks. Perhaps more importantly, the collective carbon footprint of AI has been increasing exponentially, rendering it unsustainable in the long term. This observation points to an urgent need for a deeper, fundamental understanding of neural networks to build models that are not just efficient but also sustainably intelligent. As a doctoral researcher, my broad research vision is to move towards such a fundamental understanding of neural networks to pave the way for their wider adoption, including their biomedical applications.

Research collaboration. I’m very open to collaborative research efforts and mentoring future MSc students. Please have a look here if you find something interesting.