Teaching

Below is the list detailing the classes that I have served as an undergraduate/graduate teaching assistant for at UCSD. Instructors are listed in the order in which I worked with them. Instructor evaluations are attached if available.

Data Science

	Data Structures and Algorithms for Data Science Prof. Suh Young Choi UCSD DSC 30 SU24 evaluation website Programming techniques including encapsulation, abstract data types, interfaces, algorithms and complexity, and data structures such as stacks, queues, priority queues, heaps, linked lists, binary trees, binary search trees, and hash tables with Java.
	Theoretical Foundations of Data Science I Prof. Kyle Shannon UCSD DSC 40A SU24 WI25 evaluation website DSC 40A will introduce fundamental topics in machine learning, statistics, and linear algebra with applications to data analysis.
	Theoretical Foundations of Data Science II Prof. Justin Elderidge and Dr. Akbar Rafiey UCSD DSC 40B FA23 SP24 evaluation website DSC 40B, the second course in the sequence, introduces fundamental topics in combinatorics, graph theory, probability, and continuous and discrete algorithms with applications to data analysis.
	Tutor Apprenticeship in Data Science Prof. Colin Jemmott UCSD DSC 95 WI24 website Guide new DSC tutors through their first quarter as a tutor.
	Intro to Data Management Prof. Kyle Shannon UCSD DSC 100 FA24 evaluation website This course is an introduction to storage and management of large-scale data using classical relational (SQL) systems, with an eye toward applications in data science. The course covers topics including the SQL data model and query language, relational data modeling and schema design, elements of cost-based query optimizations, relational data base architecture, and database-backed applications.

Cognitive Science

	Modeling and Data Analysis Prof. Lucy Lai UCSD COGS 109 FA25 website Exposure to the basic computational methods useful throughout cognitive science. Computing basic statistics, modeling learning individuals, evolving populations, communicating agents, and corpus-based linguistics will be considered.
	Introduction to Data Science Prof. Kyle Shannon UCSD COGS 9 FA22, WI23, SP24 website The course provides a comprehensive overview of core data science concepts and their applications. Students will delve into data privacy and ethical concerns, illustrated with real-world examples. The course emphasizes identifying pertinent data science questions and selecting the appropriate analytical approaches to address them. Communication skills for data-related topics and projects are honed, along with developing a critical mindset for approaching problems with a 'data-first' perspective. Additionally, the course highlights potential pitfalls in data analyses, teaching students how to identify and avoid them.
	Hands-on Computing Prof. Kyle Shannon UCSD COGS 8 FA23 evaluation website The class explores the fundamental concepts of computing and its applications. Using Python and small microprocessors, students learn to build robotic systems equipped with sensory mechanisms to perform complex tasks. Along the way, the course introduces key concepts within Cognitive Science, particularly embodied, embedded, and distributed cognition.