At Massachusetts General Hospital, I currently serve as an Associate Investigator, leveraging my expertise in artificial intelligence, data science, and medical physics to drive cutting-edge research and develop innovative solutions for pressing healthcare challenges. Collaborating with a multidisciplinary team of clinicians, researchers, and data scientists, I am dedicated to implementing AI-driven technologies that enhance patient care, streamline clinical workflows, and optimize hospital operations.My work focuses on a range of AI applications, including clinical decision support systems, computer vision for diagnostic medical imaging, biomarker discovery, and telemedicine. By continually pushing the boundaries of AI research in healthcare, I strive to advance Mass General's mission to provide the highest quality patient care, pioneer groundbreaking medical research, and deliver exceptional education to future medical professionals.In addition to my research responsibilities, I am also involved in mentoring and supervising graduate students and postdocs, fostering a dynamic and collaborative environment that encourages innovation, teamwork, and the pursuit of excellence.

During my tenure at Sano Centre for Personalized Computational Medicine (Sano), I held multiple leadership roles, including Director, President of the Management Board, and Leader of the Health Informatics Research Group. In these capacities, I was instrumental in establishing and guiding the strategic vision for this cutting-edge research institute, specializing in the application of Artificial Intelligence (AI) in Medicine.As the director, I was responsible for creating the research program and overseeing the hiring of principal investigators, senior research staff, students, and postdocs. I successfully grew Sano from 11 employees to 70, fostering a culture of innovation and collaboration that has enabled the institute to thrive and expand.Leading the Health Informatics Research Group, I spearheaded research initiatives focused on clinical decision support, new biomarkers, novel approaches to telemedicine/therapy with AI VR/AR technologies, and quality registries/clinical pathways. I was able to establish numerous industry collaborations with major pharmaceutical companies, as well as academic and clinical partners across Poland, the European Union, the United Kingdom, and the United States.Throughout my time at Sano, I also contributed to numerous peer-reviewed papers and conference presentations, advancing the institute's reputation as a leader in the application of AI to medicine. My dedication to driving innovation and fostering strong partnerships has laid the foundation for Sano's continued success in advancing personalized computational medicine.

At IBM Watson Health, I held the position of Senior Data Scientist, where I applied my extensive knowledge in artificial intelligence, machine learning, and healthcare to develop innovative solutions for a range of applications. My work was centered around enhancing diagnostic capabilities, predicting patient outcomes, optimizing therapy selection, improving workflows, and ensuring quality assurance in healthcare.During my tenure at IBM, I gained invaluable experience in all stages of AI product development, starting from conceptualization and collaboration with key opinion leaders, to prototyping, data collection, annotation, testing, and ultimately, deploying cloud-based solutions. I worked closely with a diverse team of professionals, including physicians, software developers, mathematicians, statisticians, and business experts, to bring cutting-edge AI-driven technologies to life.My hands-on experience in deep learning and machine learning methodologies, coupled with my ability to adapt to various types of data, such as computer vision, text processing, and feature-based machine learning, allowed me to make a significant impact on the healthcare solutions developed at IBM Watson Health. My contributions to the team helped advance the organization's mission of leveraging AI and data-driven insights to transform healthcare and improve patient outcomes.

During my tenure at Philips, I focused on applying deep learning and machine learning techniques to a diverse array of data, including image sequences, text, and healthcare-related data analytics. The projects I contributed to spanned a wide range of medical imaging modalities, such as US, X-ray, MRI, and CT, with applications in cardiology, oncology, and neurology.