Simona Turco, PhD

<p>Simona Turco is an Associate Professor within the Signal Processing Systems group (Department of Electrical Engineering) at Eindhoven University of Technology (TU/e), and a member of the <a href="https://www.tue.nl/en/research/research-groups/signal-processing-systems/biomedical-diagnostics">Biomedical Diagnostics (BM/d) lab</a> and the <a href="https://www.tue.nl/en/research/research-groups/eaisi/eaisi-business-operations/eindhoven-medtech-innovation-center">Eindhoven Medtech Innovation Center (e/MTIC)</a>. Her research focuses on quantitative, model-driven analysis of medical images and biosignals, bridging physics-based models with data-driven artificial intelligence to advance oncology and patient monitoring.</p> <p>In cancer diagnostics, her work specializes in assessing tumor angiogenesis and vascular health. By leveraging dynamic contrast-enhanced ultrasound (CEUS) and MRI—alongside advanced techniques like Ultrasound Localization Microscopy (ULM), nanobubble modeling, and shear-wave elastography—she aims to extract multi-scale structural and functional information to evaluate tissue and vascular abnormalities in cancer and beyond. In perioperative and intensive care settings, her research translates complex biosignals into predictive insights, utilizing deep learning and mathematical modeling for mechanical ventilation monitoring, patient-ventilator asynchrony detection, and hemodynamic tracking. By combining model-based feature extraction with machine learning, she develops interpretable risk-prediction models designed for clinical decision-support. Driven by industrial and clinical needs, she collaborates closely with top healthcare partners to facilitate the direct translation of these research innovations into patient care. <br/>More information on her research can be found on her <a href="https://simonaturco.github.io/">personal webpage</a>.</p>

<p>Simona Turco obtained her MSc in Biomedical Engineering from the University of Pisa (Italy) in 2012 <em>summa cum laude</em>. In 2015, she earned a Professional Doctorate in Engineering (PDEng) in Healthcare System Design from the Stan Ackermans Institute at Eindhoven University of Technology (TU/e), where she subsequently completed her PhD in 2018 with a thesis entitled "Pharmacokinetic modeling in cancer: from functional to molecular imaging of angiogenesis." Currently, she is an Associate Professor at the Biomedical Diagnostics (BM/d) research lab, focusing on quantitative model-driven analysis of bio-signals. Beyond her research, she is actively involved in the academic community; she serves as a member of the <a href="https://www.tue.nl/en/our-university/community/tue-young-academy-of-engineering">Eindhoven Young Academy of Engineering (EYAE)</a>, chairs the <a href="https://r8.ieee.org/benelux-embs/">IEEE Engineering in Medicine and Biology Benelux Chapter</a>, and was previously a board member of the <a href="https://www.tue.nl/en/our-university/community/women-in-science-eindhoven-wise-network">Women in Science Eindhoven (WISE)</a> network.</p>

<ul><li>5CTA0 Statistical signal processing (responsible teacher)</li><li>5LSN0 Techonology for Care and Cure (guest lecturer)</li></ul>