I’m Miroslava Mačejková, a Master’s student in Machine Intelligence at the University of Basel. My studies and projects revolve around Artificial Intelligence, Machine Learning, and Explainable AI, with a particular interest in how reasoning mechanisms can make AI systems more transparent and trustworthy. I enjoy exploring the intersection of theory and application — from Bayesian inference and Statistical Learning Theory to practical projects that bring AI into real-world contexts. One of my current projects is Anamedi, an AI-powered transcriber for doctors designed to help medical professionals focus more on their patients by automating documentation during appointments. Within the team, I’m responsible for technical development, coordination, and research on data security. I’ve also conducted interviews with specialists to better understand how sensitive data should be handled in healthcare systems. As part of my coursework, I’ve presented research on Neuro-Symbolic AI, exploring how it can enhance the explainability of AI-generated responses through reasoning mechanisms. I’m deeply interested in how human reasoning and symbolic structures can complement deep learning models to make AI more interpretable. Besides my academic work, I’m passionate about design and visual storytelling. I’ve coordinated illustration projects for educational booklets, ensuring a consistent visual identity using SVG graphics. I also enjoy creative projects such as filming and editing — for example, I’ve created a short video about Lauterbrunnen, a place that deeply inspires me and that I plan to revisit to create a longer documentary-style video. Through my studies and projects, I aim to combine my technical background, creativity, and curiosity to contribute to human-centered and ethical AI systems that truly support people in meaningful ways.…I’m Miroslava Mačejková, a Master’s student in Machine Intelligence at the University of Basel. My studies and projects revolve around Artificial Intelligence, Machine Learning, and Explainable AI, with a particular interest in how reasoning mechanisms can make AI systems more transparent and trustworthy. I enjoy exploring the intersection of theory and application — from Bayesian inference and Statistical Learning Theory to practical projects that bring AI into real-world contexts. One of my current projects is Anamedi, an AI-powered transcriber for doctors designed to help medical professionals focus more on their patients by automating documentation during appointments. Within the team, I’m responsible for technical development, coordination, and research on data security. I’ve also conducted interviews with specialists to better understand how sensitive data should be handled in healthcare systems. As part of my coursework, I’ve presented research on Neuro-Symbolic AI, exploring how it can enhance the explainability of AI-generated responses through reasoning mechanisms. I’m deeply interested in how human reasoning and symbolic structures can complement deep learning models to make AI more interpretable. Besides my academic work, I’m passionate about design and visual storytelling. I’ve coordinated illustration projects for educational booklets, ensuring a consistent visual identity using SVG graphics. I also enjoy creative projects such as filming and editing — for example, I’ve created a short video about Lauterbrunnen, a place that deeply inspires me and that I plan to revisit to create a longer documentary-style video. Through my studies and projects, I aim to combine my technical background, creativity, and curiosity to contribute to human-centered and ethical AI systems that truly support people in meaningful ways.WWWW…