researcher profile

dr. Borbála Hunyadi

Assistant Professor

Expertise: Biomedical signal processing

Contact details

Group: Circuits and Systems (CAS)
Department of Microelectronics
Room:VMB 1.W.700
Phone:+31 15 278 1254
Email:B.Hunyadi@tudelft.nl
Personal webpage

List of publications

Google Scholar profile

Borbála (Bori) Hunyadi was born in Budapest, Hungary. She received a MSc degree in electrical and computer engineering from the Pazmany Peter Catholic University in 2009. In the same year she joined Stadius, Department of Electrical Engineering at KU Leuven, where she worked in close collaboration with the Laboratory for Epilepsy Research, and she obtained her PhD degree in 2014. She continued working in Stadius as a postdoctoral researcher on the ERC advanced grant Biotensors, and she served as the research lead on the Imec-ICON project SeizeIT. Between February and May 2016 she was a visiting researcher at the University of Oxford, and in May 2017 she visited the Christian Albrechts University of Kiel. In 2018 she was awarded one of the “Delft Technology Fellowships” for outstanding female academic researchers. In October 2018 she joined the Circuits and Systems group at TU Delft as an assistant professor.

Her research interests include biomedical signal processing and machine learning for biomedical pattern recognition. More specifically, she is interested in multimodal signal processing and fusion, blind source separation, tensor decompositions and wearable signal processing to better understand healthy and pathological physiology, in particular brain activity in epilepsy.

Education

EE-BD Biomedical Devices (BD) profile

A profile in our MSc-EE program dedicated to biomedical devices. Biomedical devices are used for medical diagnosis, monitoring and treatment. They can be fixed, portable, wearable, implantable and injectable. They are active and thus embed electronics, computing and software

EE2S31 Signal processing

Digital signal processing; stochastic processes

EE4530 Applied convex optimization

Applied convex optimization: role of convexity in optimization, convex sets and functions, Canonical convex problems (SDP, LP, QP), second-order methods, first-order methods for large-scale problems.

Projects

Prostate cancer detection using ultrasound

Tensor techniques to improve the analysis of (3D+time) ultrasound images

Delft Tensor AI Lab

Tensor-based AI methods for biomedical signals

Multimodal, multiresolution brain imaging

Developing a novel brain imaging paradigm combining functional ultrasound and EEG

Medical Delta Cardiac Arrhythmia Lab

Part of a larger program (with Erasmus MC) to unravel and target electropathology related to atrial arrhythmia

Last updated: 16 Aug 2021