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 									I am a <b>postdoctoral researcher</b> at <a href="https://www.ukbonn.de/" style="font-size:16px; font-weight:bold">Universitätsklinikum Bonn</a>, with <a href="https://albarqouni.github.io/" style="font-size:16px; font-weight:bold">Pr. Shadi Albarqouni</a>. Previously, I obtained my <b>Ph.D. in Computer Sciences</b> from <a href="https://www.irisa.fr/en" style="font-size:16px; font-weight:bold">Université de Rennes</a>, under the supervision of Dr. <a href="http://camillemaumet.com" style="font-size:16px; font-weight:bold">Camille Maumet</a> and Pr. <a href="http://people.irisa.fr/Elisa.Fromont/" style="font-size:16px; font-weight:bold">Elisa Fromont</a>. 
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-									My research focuses on exploring, modelling and building solutions to take into account <b>data variability in medical imaging</b>, in particular in machine learning studies. During my PhD, my goal was to facilitate the <b>re-use of shared data from public databases</b> by taking into account the different sources of variability. In the future, I would like to focus more in the use of real-world data and on the robustness of machine learning models to <b>dataset shifts and privacy attacks</b>. I am also interested in building <b>affordable</b> and <b>adaptable</b> solutions for an universal utility.
+									My research focuses on <b>AI for Medical Imaging</b>, in particular:<br>
+									💪 <b>Robust & trustworthy</b> AI in healthcare; <br>
+									🩻 Medical image analysis; <br>
+									🌍 Data variability & <b>Fairness</b>; <br>
+									🔐 Federated learning, <b>privacy & security</b>; <br>
+									🤝 <b>Affordable</b> & adaptable AI. <br>
+									<br>
+									🩷 I am involved in several actions for <b>Women in Science</b>. <br> 
+									🏆 L'Oreal-UNESCO <b>For Women In Science Young Talent Award 2024</b>.
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