Learning Networking by Reproducing Research Results

Headshop ot Lisa Yan in front of tree

Presentation by Lisa Yan

2020 CROSS Research Symposium Keynote

Tuesday, October 6, 2020


Abstract: Reproducing research is key to continued scientific progress, especially in fields that are engineering- and application-focused. In the past eight years, the graduate computer networking course at Stanford University has asked students to reproduce research results for a different reason: to teach students engineering rigor and critical thinking—qualities that are essential for careers in networking research and industry. In this talk, I share our experience with teaching over 300 students the art of reproducing results from over 70 networking papers. We have observed in many cases that the process of reproducing research can not only teach much-needed technical skills, but also empower students and produce lasting contributions to the networking community.

Bio: Lisa Yan is a Lecturer of Computer Science at Stanford University where she teaches probability and computer systems. She completed her PhD at Stanford, where she studied and implemented tools for understanding students in computer science classrooms. Her research interests are in facilitating teacher understanding of student learning through both in-progress work snapshots and final assignment submissions. Lisa’s teaching interests are in building student confidence in sophomore-level CS courses, as well as training and inspiring the next generation of computer science instructors.