SCS Teaching Track Candidate - Maryam Hedayati

— 2:00pm

Location:
In Person and Virtual - ET - ASA Conference Room, Gates Hillman 6115 and Zoom

Speaker:
MARYAM HEDAYATI, Ph.D. Candidate, Center for Computer Science and Learning Sciences, Northwestern University
https://maryamhed.github.io/


Teaching Demonstration: Binary search trees

Binary search trees (BSTs) provide an efficient way to manage and search through data. In this teaching demonstration, I will explore the motivation for using BSTs and introduce students to BST operations. I will also talk about how BSTs can be used to implement sets. This teaching demonstration will target students who are familiar with some Python programming and are just beginning to learn about data structures. 

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Maryam Hedayati is a PhD candidate in Computer Science and Learning Sciences at Northwestern University, working with Matthew Kay in the MU Collective lab. My current research primarily focuses on trying to better understand data visualization literacy. I have taught two courses at Northwestern as instructor of record: an introductory computer science course taught in Racket, and an introduction to computer science research for undergraduates. I have also TAed six classes at Northwestern: CS1 (x2), CS1.5, CS2, and data visualization (x2). Before my PhD, I received a B.A. from Carleton College in computer science and psychology. I also spent some time working as a tech consultant at Pariveda Solutions in New York, and was a staff member on two iterations of a computer science study abroad program in the UK. Before coming to Northwestern, I received a B.A. from Carleton College in computer science and psychology, where I was a member of the Carleton Perception Lab. I also spent time working as a tech consultant at Pariveda Solutions in New York, and was a staff member on two iterations of a computer science study abroad program in the UK. Outside of work, I enjoy watching musicals, sending postcards, drinking tea, sewing, and hanging out with my cat. 

In Person and Zoom Participation.  See announcement.


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