Pitt AI Summer School organized by the Pitt HexAI Research Laboratory aims to provide a stimulating and unique opportunity for high school (grades 11 and 12) and community college students to dive into the fascinating world of artificial intelligence (AI) and its application in medical imaging informatics. This is a program designed for advanced high school students (grades 11–12) and early college learners, including community college students. We launched the AI Summer School in the summer of 2023, and it has been conducted annually since its inception. This year, our AI Summer School will be held between Monday, June 9 to Friday, June 13, 2025; 9:00 AM to 3:00 PM EDT, at the University of Pittsburgh, in collaboration with the Computational Pathology & AI Center of Excellence (CPACE), the School of Health and Rehabilitation Sciences, and IEEE Computer Society and IEEE Education Society in Pittsburgh, Pennsylvania.

Medical imaging informatics leverages AI-driven computer vision to analyze and interpret medical images for better diagnosis and treatment. A key area of focus is object detection and localization, where AI systems identify and locate relevant features within medical images. This summer school will dive into these techniques, teaching participants how to apply them using Python programming. Through lectures, hands-on exercises, and collaborative projects, attendees will gain practical skills in AI-powered medical image analysis, preparing them to tackle real-world challenges in the field.

The AI Summer School offers a comprehensive one week program designed to introduce high school and community college students to artificial intelligence and its applications in medical imaging. The program begins with foundational concepts, including an introduction to AI, computer vision, and digital image operations, followed by hands-on practice with Python and Google Colab. As the week progresses, students explore advanced topics such as deep learning, convolutional neural networks (CNNs), and object detection techniques like YOLO and SSD. Each day includes lectures from esteemed faculty, hands-on coding exercises, and guest talks from AI researchers in academia and industry. Students will gain practical experience in medical image annotation, image filtering, and object localization, utilizing tools like PyTorch, ITK-SNAP, and Liner.ai. The program culminates in a collaborative team project, where participants apply their knowledge to real-world challenges, followed by team presentations. The summer school concludes with a certificate ceremony, recognizing students’ achievements and their participation in this immersive AI learning experience.