dr. C. Varon

Guest Assistant Professor
Signal Processing Systems (SPS), Department of Microelectronics

Expertise: Machine learning; Biomedical signal processing;

Themes: Biomedical signal processing/wavefield imaging


Carolina Varon was born in Ibagué, Colombia. She received the electrical engineering degree from the Universidad de Ibagué, Colombia, in 2005. After her studies, she joined Security Solutions, Bogotá, Colombia, where she was a Technical Support engineer for Latin America until 2007. In 2007 she moved to Leuven, Belgium, where two years later she received the M.Sc. degree in astronomy and astrophysics and in 2010 the M.Sc. degree magna cum laude in artificial intelligence, both from KU Leuven. She received her Ph.D. degree from the Department of Electrical Engineering (ESAT-STADIUS) of KU Leuven in 2015. In 2015 she got a KU Leuven postdoctoral mandate and in 2016 a postdoctoral fellowship from the Research Foundation – Flanders (FWO), Belgium. During spring 2016, she was a visiting researcher at the University of California, San Francisco (UCSF), and in spring 2017 she was an invited researcher at the University of Zaragoza, Spain.

She was a visiting assistant professor in the Signal Processing Systems group (SPS) of the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. Her research interests include machine learning, (biomedical) signal processing, wearable technology, and network physiology. Carolina Varon has been the project leader of an IMEC SBO (type B-project), and the sub-project leader of an STW-IWT bilateral agreement project. She is a review Editor on the Editorial Board of Autonomic Neuroscience, part of the journal Frontiers in Neurology, Frontiers in Neuroscience and Frontiers in Physiology. She has been a member of the program committee of the Computing in Cardiology conference since 2017, and she is a member of the scientific committee of the 11th conference of the European Study Group on Cardiovascular Oscillations (ESGCO) 2020.


  1. Exploring the Use of Granger Causality for the Identification of Chemical Exposure Based on Physiological Data
    S. Difrancesco ; J. U. Van Baardewijk; A. S. Cornelissen; C. Varon; R. C. Hendriks; A. M. Brouwer;
    Frontiers in Network Physiology,
    Volume 3, 2023. DOI: 10.3389/fnetp.2023.1106650

  2. Quantifying Interactions between Physiological Signals to Identify Exposure to Different Chemicals
    J. U. van Baardewijk; S. Agarwal; A.S. Cornelissen; C. Varon; R.C. Hendriks; J. Kentrop; M.J.A. Joosen; A.-M. Brouwer;
    In Proceedings of Measuring Behavior 2022,

  3. Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning
    Thomas De Cooman; Kaat Vandecasteele; Carolina Varon; Borbala Hunyadi; Evy Cleeren; Wim Van Paesschen; Sabine Van Huffel;
    Frontiers in Neurology,
    Volume 11, pp. 145, 2020. DOI: 10.3389/fneur.2020.00145

  4. Multilevel Interval Coded Scoring to Assess the Cardiovascular Status of Sleep Apnea Patients using Oxygen Saturation Markers
    Margot Deviaene; Pascal Borzee; Merel Van Gilst; Johannes Van Dijk; Sebastiaan Overeem; Bertien Buyse; Dries Testelmans; Sabine Van Huffel; Carolina Varon;
    IEEE Transactions on Biomedical Engineering,
    2020. DOI: 10.1109/TBME.2020.2972126

  5. A Comparative Study of ECG-derived Respiration in Ambulatory Monitoring using the Single-lead ECG
    C. Varon; J. Morales; J. Lazaro; M. Orini; M. Deviaene; S. Kontaxis; D. Testelmans; B. Buyse; P. Borzee; L. Sornmo; P. Laguna; E. Gil; R. Bailon;
    Scientific Reports,
    Volume 10, 2020. DOI: 10.1038/s41598-020-62624-5

  6. Using Biosensors and Digital Biomarkers to Assess Response to Cardiac Rehabilitation: Observational Study
    Helene De Canniere; Christophe Smeets; Melanie Schoutteten; Carolina Varon; Chris Van Hoof; Sabine Van Huffel; Willemijn Groenendaal; Pieter Vandervoort;
    J Med Internet Res,
    Volume 22, Issue 5, pp. e17326, 2020. DOI: 10.2196/17326

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Last updated: 21 Mar 2024