Faculty Candidate Seminar

Teaching Demonstration (Hashtables)

Daniel AndersonPh.D. CandidateCarnegie Mellon University
3725 Beyster BuildingMap

Zoom link for remote participants, passcode:  211928

Teaching Faculty Candidate Seminar


Abstract: This teaching demonstration will cover hashtables, aimed at an undergraduate introductory algorithms and data structures course. Familiarity with arrays, asymptotic analysis (big O), simple probability, and linked data structures (e.g. linked lists) are assumed. After this class, students will understand the motivation of hashtables as a solution to the dictionary problem, and be able to explain the advantages (e.g., locality, fast lookup) and challenges (e.g., collision resolution, good hash functions) of hashing and hashtables as a fundamental algorithmic tool.

Bio: Daniel is a fifth-year PhD candidate at CMU. His main passion is teaching undergraduate computer science. He has been teaching college-level algorithms and programming courses as a TA and instructor for over seven years, with a focus on creating resources and materials that enable everyone to succeed regardless of their backgrounds. His efforts have been recognized by CMU’s Alan J. Perlis Graduate Student Teaching Award. He is currently an instructor for 15-451 / 15-651, Algorithm Design and Analysis at CMU. When he is not too busy teaching, he also likes creating tools that make parallel programming easier and more accessible for non-experts, and understanding the theory of parallel algorithms. His research on the minimum cut problem has been recognized with a best paper award from the ACM Symposium on Parallelism in Algorithms and Architectures conference.


Cindy Estell

Faculty Host

Atul Prakash