Kevin Wayne

Kevin Wayne serves as the Phillip Y. Goldman '86 University Lecturer in the Department of Computer Science at Princeton University's School of Engineering and Applied Science. His teaching responsibilities include foundational courses in data structures, algorithms, optimization, and introductory computer science, specifically COS 126, COS 226, and COS 423.

Dr. Wayne's research interests center on algorithms, data structures, and computer science education. His work emphasizes practical applications across science, engineering, and commerce, with particular focus on making complex computational concepts accessible through interdisciplinary approaches. He has pioneered numerous educational methodologies that bridge theoretical computer science with real-world applications.

His educational materials, particularly the Algorithms textbook series and associated MOOCs, have established new standards in computer science education globally. These resources have demonstrated exceptional impact during the pandemic era, with Algorithms Part I ranking among the top online courses worldwide.

• The textbook Algorithms, 4th Edition was named one of The 25 Best Programming Books of All-Time in 2020
• The MOOC Algorithms, Part I was recognized as one of the Top 25 Most Popular Courses During the Pandemic
• Named the 2019 Outstanding Teacher in Computer Science at a Ph.D. Granting Institution in New Jersey
• Recipient of the 2014 ACM Distinguished Educator award
• Winner of Princeton University's 2013 Phi Beta Kappa Teaching Award

Dr. Wayne has developed numerous innovative educational programs including the Summer Programming Experiences for first-year students and the Course Development Program. His 'Nifty Assignments' collection, designated by ACM SIGCSE, has been adopted by institutions worldwide and includes projects ranging from WordNet analysis to particle collision simulations. He maintains active development of educational software tools including the widely-used algs4 GitHub repository containing Java implementations of fundamental algorithms.