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--- pub:about_us:sbk [2022/01/14 08:07] – [Szymon Bobek] sbk
+++ pub:about_us:sbk [2024/12/16 09:34] (current) – [Szymon Bobek] sbk
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 {{:pub:about_us:sbk-face.jpg?200 |Szymon Bobek}}\\
-**Szymon Bobek, PhD** (<szymon.bobek@uj.edu.pl>, [[https://szymon.bobek.re/|www]]) holds a position of an assistant professor at the Jagiellonian University in Krakow, Poland, Faculty of Physics, Astronomy and Applied Computer Science He received his degree PHD at AGH UST in 2016 in the field of Computer Science (Artificial Intelligence) and science then he works as a member of GEIST research team. His work includes most recently hybrid models for explainable AI. He is author of over 70 research papers in international journals, books and conferences and reviewed research papers for a number of international journals. He participated in national and international research projects as an co-investigator and principle investigator, and also cooperated with several companies in applied projects, especially with massive big data processing using machine learning methods. He is in active cooperation with Cambridge University in the area of XAI application in healthcare applications and with AFFCAI (affcai.geist.re) group in the area of application of XAI to processing biomedical signals for Affective computing. Recently, he has been leading a team that developed a series of original tools in the area of eXplainable AI for the applications in industrial AI. He is a co-organizer of Practical Applications of Explainable Artificial Methods special session (https://praxai.geist.re) and Semantic Datas Mining Workshop  (https://sedami.geist.re)
+**Szymon Bobek, PhD** (<szymon.bobek@uj.edu.pl>, [[https://szymon.bobek.re/|www]]) holds a position of an assistant professor at the Jagiellonian University in Krakow, Poland, Faculty of Physics, Astronomy and Applied Computer Science He received his degree PHD at AGH UST in 2016 in the field of Computer Science (Artificial Intelligence) and science then he works as a member of GEIST research team. His work includes most recently hybrid models for explainable AI. He is author of research papers in international journals, books and conferences and reviewed research papers for a number of international journals. He participated in national and international research projects as an co-investigator and principle investigator, and also cooperated with several companies in applied projects, especially with massive big data processing using machine learning methods. He has been leading a team that developed a series of original tools in the area of eXplainable AI for the applications in industrial AI (https://github.com/sbobek). He is a co-organizer of Practical Applications of Explainable Artificial Methods special session (https://praxai.geist.re),  Semantic Datas Mining Workshop  (https://sedami.geist.re) and Tutorial and workshop on Explainable and Robust AI for Industry 4.0 & 5.0 (X-RAI) (https://xrai.geist.re).