Prof. Anna Fabijańska holds the academic title of Professor of Engineering and Technical Sciences in the scientific discipline of Information and Communication Technology, which she obtained in 2022.
She is a graduate of the Master's degree program in computer science at the Faculty of Electrical, Electronic, Computer and Control Engineering of the Lodz University of Technology. She earned a doctoral degree (2007) and a doctor habilitated (2013) in technical sciences, specializing in computer science. She works at the Institute of Applied Computer Science of the Lodz University of Technology. She is also a member of the Committee on Informatics of the Polish Academy of Sciences and a former member of the Polish Young Academy (2016-2021). Her research expertise encompasses machine learning (including deep learning), artificial intelligence, and pattern recognition, focusing primarily on computer vision and image analysis. Her works contribute to advancing artificial intelligence across various domains, including medical image analysis for computer-aided diagnosis systems, agriculture, earth sciences (geology), and industry. She authored or co-authored more than 120 research papers and conference reports in computer vision and AI-related journals. In multiple years, including 2022 and 2020, she gained a recognition as one of the World's Top 2% Scientists in AI and Image Processing. She also has led and contributed to several cross-disciplinary research projects that directly apply artificial intelligence and machine learning techniques to solve real-world challenges. She actively participates in the Editorial Boards of journals focused on computer science and AI, including Artificial Intelligence in Medicine (AIIM) and Engineering Applications of Artificial Intelligence (EAAI). She also reviews for prestigious computer vision and AI-related journals and funding agencies. Her programming skills encompass implementation, training, and evaluation of supervised and unsupervised models using state-of-the-art AI/ML, Deep Learning, and Data Science libraries, demonstrating her hands-on expertise in applying the latest AI tools and technologies. She has taught courses in programming, machine learning, image processing, and related subjects, in addition to supervising PhD, Master, and Bachelor of Engineering candidates.
