Dr. Alija Pašić began his studies in Electrical Engineering in German at the Budapest University of Technology and Economics (BME) in 2007, where in 2009 he was awarded the Robert Bosch Scholarship, allowing him to complete part of his studies in Germany at the Karlsruhe Institute of Technology (KIT). In 2012, he won first prize at the BME Scientific Students’ Association Conference, followed by another first prize at the National Scientific Students’ Conference in 2013. In the same year, he obtained his MSc degree in Electrical Engineering with summa cum laude distinction, and in 2019 he earned his PhD in the same field, also with summa cum laude honors. He is currently an Associate Professor at the Department of Networked Systems and Services (HIT), Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics. Since 2013, he has been actively engaged in research on the design of reliable and intelligent networks, as well as machine learning–based network management. He is the author or co-author of more than 27 conference papers, 24 journal articles, and one book chapter, most of which have been published in leading international venues. He places strong emphasis on international collaboration and has worked with researchers from the Massachusetts Institute of Technology (MIT), the University of Waterloo, and Ericsson. He is the co-author of seven patent applications submitted jointly with Ericsson. His scientific achievements have been recognized with numerous fellowships and awards, including the Bolyai János Research Scholarship, the OTKA Postdoctoral Excellence Program, the Scholarship for the Nation’s Young Talents, and the New National Excellence Program (ÚNKP). He has participated in multiple OTKA projects and serves as a principal investigator in industrial and applied research projects, particularly in 5G and artificial intelligence–based network management. He has also contributed to the GÉANT Open Call Project Minerva and a COST Action initiative as an MC substitute. His main research interests include reliable and resilient network design and management, data-driven research (ranging from QoE prediction to biomedical data analysis), and applied artificial intelligence.