Attila Zoltán Jenei

Attila Zoltán Jenei

Conduct research at the Doctoral School of Informatics (institution of Budapest University of Technology and Economics). The PhD research focuses on the multimodal recognition of the Parkinson's disease.

Core skills:
Python, Matlab, RapidMiner
Areas of interest:
Signal Processing, Machine Learning, Data Science, Statistics, Biomedical Engineering, Health Care

Contact information:

Room: IB157
E-mail: jenei.attila.zoltan [@] vik.bme.hu

Current projects

OTKA-K program - Diagnostic possibilities of speech disorders caused by abnormal speech-forming organ lesions, neurological and psychiatric disorders using artificial intelligence (participation between 2021-2022)
OTKA-FK program - FORENSICspeech: Forensic Voice analysis using Hungarian follow-up voice database (participation between 2021-2024)
OTKA-K program - Automatic transcription and medical application of dysfluent and abnormal speech (participation from 2024)

Teaching activity

Holding practical and laboratory sessions, writing and correcting class assignments:

Basics of Programming in Python (BMEVIEEBA01)
Basics of Programming in C (BMEVIEEAA00)
Speech Information Systems (BMEVITMAD00)

Review and evaluation of professional reports and presentations:

Project Laboratory 1 (BMEVITMML00)
Project Laboratory 2 (BMEVITMML01)

Publication List

PhD Thesis

MSc Thesis

Possibilities of automatic speech-based separation of Parkinson's disease, depression and voice disorders with 2D convolutional neural networks (2020, in Hungarian)

Scientific Students’ Associations Conference

Automatic speech-based recognition of depression with 2D convolutional networks;
Section: Signal Processing (2019, in Hungarian)
Analysis of sampling number based on PDA measurements of air-assested atomizer;
Section: Energy systems modeling (2017, in Hungarian)

Hobbies

Reading psychology
Playing guitar
Hiking
Swimming