Leo Porter is a Teaching Professor in the Computer Science and Engineering Department at UC San Diego. He is best known for his research on the impact of Peer Instruction in computing courses, the use of clicker data to predict student outcomes, and the development of the Basic Data Structures Concept Inventory. Leo co-founded the Computing Education Research Laboratory dedicated to better understanding how students learn computing and creating instructional environments where a diverse group of students can succeed. Most recently, he and Dan Zingaro wrote Learn AI-Assisted Python Programming (Manning, 2024) to teach essential skills of writing software with an AI-Assistant, including code reading, code testing, code debugging, and problem decomposition.
He co-teaches the popular Coursera Specialization "Object-Oriented Java Programming: Data Structures and Beyond" with over 300,000 enrolled learners and the first course in the edX MicroMasters in Data Science, "Python for Data Science", with over 200,000 enrolled learners. He has received six Best Paper Awards, SIGCSEs 50th Year Anniversary Top Ten Symposium Papers of All Time Award, an Outstanding Teaching Award from Warren College, and the Academic Senate Distinguished Teaching Award at UC San Diego. He is a Distinguished Member of the ACM and previously served as Secretary of the ACM SIGCSE Board.
