Dóra Viktória Molnár

Dóra Molnár is an ELIZA Master’s Scholarship holder currently studying Machine Learning at the University of Tübingen. She holds a Bachelor’s degree in Mathematics and is passionate about combining computational tools with real-world scientific questions. Her research focuses on developing and applying state-space models to infer neural dynamics from voltage imaging data. She completed an individual research project on this topic in Prof. Jakob Macke’s lab and is currently writing her Master’s thesis in the same group, exploring new methodological directions and extensions.
Beyond neuroscience, Dóra has also contributed to TFpredict, a supervised machine learning-based tool for the identification and structural characterization of transcription factors. This work was presented at the COMBINE 2024 conference, highlighting her interest in interdisciplinary applications of AI across biology. She is particularly driven by projects at the intersection of mathematics, machine learning, neuroscience, and computational biology, and is eager to continue working on impactful, research-oriented challenges..