Adam Cannon

Adam Cannon is a Teaching Professor in the Department of Computer Science at Columbia University, located at 500 West 120th Street, New York. His primary role involves undergraduate education, teaching courses such as Computing in Economics and Introduction to Information Science. He previously held academic positions in applied mathematics and aerospace engineering.

• Ph.D. and M.A. in Applied Mathematics: Johns Hopkins University
• M.S. and B.S. in Aerospace Engineering: University of California, Los Angeles

His research focuses on Machine Learning, Statistical Pattern Recognition, Approximation Algorithms, and Computer Science Education. Recent work emphasizes curriculum development and pedagogical strategies, including evaluations of programs like the Emerging Scholars initiative aimed at enhancing diversity and retention in STEM.

His publications span topics from debugging tools (e.g., Backstop) to theoretical advancements in classification algorithms and approximation methods. Notable contributions include studies on peer-led team learning (PLTL-CS) and national laboratory collaborations.

No scientific awards are explicitly listed, though his work has impacted both academic and practical domains. He currently advises no named students, and no specific grants are mentioned in the source text.