I am currently in my third year at UC Berkeley, pursuing a Computer Science and Data Science BA. Because data science is such an evolving field, especially at the level of undergraduate education, I have taken a keen interest in data science pedagogy, becoming heavily involved in the campus's data science ecosystem. I currently work at the UC Berkeley Division of Computing, Data Science, and Society as lead developer on the Infrastructure Team, building and maintaining the open source software that our data science and CS courses run on.


University of California Berkeley

Class of 2021, Majoring in Computer Science and Data Science (Business & Industrial Analytics), Minoring in Demography

I am currently attending UC Berkeley to earn my BA in Computer Science and Data Science, with an anticipated graduation of Spring 2021. I am also trying to take classes that are relevant to my interest in financial systems while working on campus and being active in extra-curriculars. When I came to UC Berkeley, I had intended to major in Chemical Biology; that quickly changed, however, as I realized just how much math interested me and I had the opportunity to begin learning data science. The long and winding path that I took to arrive at my choice of majors has led me into becoming very active on campus within the ecosystem that my majors inhabit.

Some of the projects that I have completed in the course of my studies include an RDBMS built in Java, Gitlet (a functional miniature-version of Git programmed in Java), BearMaps (a mapping and navigation program based on OpenStreetMaps and graph algorithms), and a Spam/Ham classifier based on logistic regression.



Undergraduate Student Instructor, UC Berkeley Electrical Engineering and Computer Science

Since January 2020, I have been a UGSI for Data 100: Principles & Techniques of Data Science (approx. 900 students). My role includes leading a discussion and lab section comprised of about 30 students each, developing teaching materials for these sections, and holding office hours for studens in the course. I also try to write materials for students to review and to use to study, including posting my discussion materials, and post them on my website.

Data Science Curriculum Development, UC Berkeley

As a part of my time at the Division of Data Sciences at UC Berkeley, I participated in curriculum development for some courses that are taught by Division staff and for other “data-enabled” courses (courses outside the Division but which use Division infrastructure). The first course that I worked on, L&S 88, focused on reproducibility and open science. It was a connector course for Data 8 (the foundational course for data science students) and it was my role as a connector assistant that spurred me into working more and more at the Division.

I present here some of the materials that I developed for courses at UC Berkeley as a part of the work I did at the Division, as well as some details on the courses they are for and my role therein. Most of what I present here is work relating to curriculum development, but I also worked as something of a lab assistant on courses, including L&S 88.

Data 88: Economic Models

Spring 2020, Fall 2019. This course is another Data 8 connector course that looks at how to apply the methods and tools of data science to economic questions. Lecture topics include SymPy, supply & demand, utility, the Cobb-Douglas production function, inequality, and other applied topics. I am a connector assistant for this class, and my contribution was the economic demography lecture along with some ipywidgets-backed applets for use in other notebooks.

SW 282: Social Welfare Research

Fall 2019. This is a module (a set of notebooks presented in non-DS courses) that I am building from scratch. It brings the power of data science to students who have no coding experience so that they can leverage the tools we show them to use in research. It covers subjects including data abstractions for rectangular data, creating data visualizations, and estimating population parameters using the boostrap.

MCB 32: Introduction to Human Physiology

Summer 2019. This module brings several physiological concepts into the data science framework. My role on this module as mainly in upkeep and updating the notebook styles and code, but I also worked on Lab 9, which deals with building a k-nearest neighbors classifier for diabetes, by adding a section in which we explain hypothesis testing and run an A/B test on the data used in the notebook.

L&S 88: Reproducibility and Open Science

Spring 2019. This course was a Data 8 connector course that focused on questions of reproducibility and open science within the Data Science community. It featured lectures on things like Project Jupyter, Licensing, and Data Repositories & Archiving. My role in this class was as a connector assistant, which primarily involved curriculum development and lab assisting in class. I developed quite a few labs for this course, including a matplotlib tutorial and a lab on Python vs. R in Jupyter notebooks.


Connector Assistant & Modules Developer

UC Berkeley Data Science Education Program

I started at the Division in January 2019 as a connector assistant for L&S 88: Reproducibility & Open Science (discussed above). As connector assistant, my role was twofold: I attended class and acted as a lab assistant during the lab portion of the class, and I worked with the course instructors to develop assignments that fit with the narrative they had for the course. After L&S 88 ended, I stayed on at the division and worked on a few different modules (sets of notebooks taught in non-DS courses). The modules that I worked on include a wide range of subjects, including human physiology, sociology, social welfare, and French.

Academic Intern

Department of Electrical Engineering & Computer Science, UC Berkeley

I was an AI for two courses: Data 100: Principles & Techniques of Computer Science & CS 88: Computational Structures in Data Science. Being an AI is similar to lab assisting, in that I spend my time in the course lab sections assisting students with completing the assignments, answering theoretical questions, and troubleshooting technical issues with assignments and students' machines.

Eagle Scout

As of October 19, 2016

The highest award in the Boy Scouts of America, I worked my way up through seven ranks and twenty-something merit badges before completing an Eagle Scout Service Project in order to obtain this honor. The Eagle Project involved designing, funding, and completing a project to benefit a local nonprofit; my project involved repainting ceiling tiles in my high school’s MPR. You can see my project notebook (from proposal to conclusion) here.

Work Experience

Lead Developer

UC Berkeley Division of Computing, Data Science, and Society, May 2019 - Present

My work at the division is a kind of hodgepodge of different responsibilities and projects. As a Lead Developer, I am leading the infrastructure team, which creates software to be packaged with the materials that we develop for other institutions. Last semester, the team built a fully-local autograder that requires no Jupyter server integration, unlike many other notebook autograding solutions. It runs on Python and parallelizes notebook/script execution using docker containers. This semester, we will be building an open-source hiring webapp for use at the Division. My original position, as an intern, was focused around the External Pedagogy Team which interacts with other institutions to think about how we teach data science and grow the community since it is such an emergent field in higher learning.

Student Assistant

UC Berkeley Summer Sessions, September 2017 - August 2019

As a student assistant, customer service skills are at the crux of my responsibilities. I interact with all of the students who need assistance from the Student Services team, and so I need to effectively work with others, and be able to help alleviate the concerns of others, give information regarding different aspects of summer courses, and perform basic office tasks. I am also involved in training and developing materials for new student assistants. Most of the training materials that we use now were curated or written by me.

Auditorium Operator

UC Berkeley Educational Technology Services, January 2018 - May 2018

As an auditorium operator, I operated the camera, audio, and other technical equipment in order to facilitate the efficient running of a large (700+ person) lecture. I also interacted with the professors of the courses in order to understand what they need for the lecture and to deliver information about the auditorium if it is needed. This is another position in which customer service skills are essential as most of my interactions with the professors occur when there are technical difficulties. It was in this capacity that I sat in on the Data 8 lectures in Spring 2018 and discovered my interest in the field, which sparked the desire to change my Applied Maths focus to the subject.

Cast Member

Regal Civic Center 16 & IMAX, October 2015 - December 2017

As a cast member at Regal, I developed most of my customer service skills by interacting with many guests (the average attendance on the weekends was 3,500 guests per day). I assisted guests with purchases, directions, and other issues; in fact, I dealt with many power outage issues, including handling guest service (refunds, swaps, etc.) and bringing projection back online after a blackout. During my time at Regal, I took on many responsibilities outside the scope of my job description, routinely handling projects that I volunteered for in order to learn ore about operations; I even learned how to operate projection, normally a function of management. Lastly, I was the person most frequently called upon to train new hires.