Computational Imaging Research

• Clinical Research
• Machine Learning Research
  • Hrvoje Bogunovic
  • Teresa Finisterra Araújo
  • Guilherme Moirera Aresta
  • Arunava Chakravarty
  • Taha Emre
  • Meltem Esengönül
  • Botond Fazekas
  • Hana Jebril
  • Dmitrii Lachinov
  • Marzieh Oghbaie
  • Antoine Rivail
  • José Morano Sánchez
  • Emese Sükei
  • Markus Unterdechler
• Software Development
• Administrative
• Reading Team
• Former Team Members

Emese Sükei, PhD

Postdoctoral Researcher
Department of Ophthalmology and Optometry
Medical University of Vienna
Email:  emese.suekei(at)meduniwien.ac.at
Phone: +43 1 40400 66146
Office: BT72, 17. floor, room 72.17.16

Bio:

Emese Sükei completed her bachelor’s degree in Computer Science Engineering at the Sapientia University in Romania, after which she received an M.Sc. degree in Mathematical Engineering at the Catholic University of Leuven (KUL), Belgium. She later pursued her PhD in Multimedia and Communications at the Universidad Carlos III de Madrid, within the Marie Curie Innovative Training Network entitled “Machine Learning Frontiers in Precision Medicine”. Her research focused on digital phenotyping, modelling mental health outcomes from passively collected mobile and wearable data. During her PhD, she collaborated with psychiatric researchers from Icahn School of Medicine at Mount Sinai, NY. She also did two 3-months long internships at the University of Liège and Siemens Healthineers, respectively. Since November 2022, she has joined Optima as a postdoc researcher.

Research Interests:
Her research interests lie in applying machine learning to the field of medicine for computer-aided diagnosis and preventive treatment.

Selected Publications:

Sükei E, Norbury A, Perez-Rodriguez M, Olmos P, Artés A. Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach. JMIR Mhealth Uhealth 2021;9(3):e24465. DOI: 10.2196/24465 

Ryu J, Sükei E, Norbury A, H Liu S, Campaña-Montes J, Baca-Garcia E, Artés A, Perez-Rodriguez M. Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study. JMIR Ment Health 2021;8(9):e30833. DOI: 10.2196/30833