About

Dániel Terbe is an AI researcher and developer based in Budapest, Hungary, with a multidisciplinary background bridging physics, neuroscience, finance, and artificial intelligence. He earned a BSc in Physics with a specialization in theoretical physics from Eötvös Loránd University, followed by an MSc in Info-Bionics from Pázmány Péter Catholic University, focusing on the interface between biological systems and computational models. To deepen his expertise in quantitative finance, he is currently pursuing a MSc in Financial Engineering at WorldQuant University.

Dániel’s work at the Institute for Computer Science and Control (HUN-REN SZTAKI) has allowed him to tackle innovative projects, from remote pulse estimation using consumer-grade cameras to designing machine learning systems for digital holographic microscopy. Alongside developing practical AI solutions for applications such as health monitoring and water sample analysis, he actively conducts research in computer vision and deep learning, contributing to the field through publications in peer-reviewed journals.

Beyond research, Dániel maintains a strong interest in creative and physical activities, including snowboarding, skateboarding, hiking, and music, valuing a balanced lifestyle that complements his technical focus.