✏️ Teaching
I am passionate about computer science education and pedagogy, working
to make teaching accessible and engaging for students! Here is some of
the experience I have had with teaching and mentorship.
🐻
University of California, Los Angeles (UCLA)
I have been a part of the teaching staff for a variety of classes at
UCLA, mostly as part of the
UCLA Learning Assistant Program.
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Head Learning Assistant (LA).
COM SCI 35L: Software Construction. Spring 2024.
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Helping teach COM SCI 35L: Software Construction taught by Dr.
Paul Eggert. Responsible for leading course logistics and
pedagogy with a team of Learning Assistants (LAs).
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Lead a team of five LAs to work with TAs to run weekly
discussions, coordinated officer hours, create practice problems
on worksheets, 2x workshops on frontend and backend development,
and 6x assignment guides related to software construction topics
(e.g. Python scripting, Bash scripting, debugging with GDB,
etc). Coordinated responses to student questions on the class
Piazza ensuring that students received an average response time
of 17 mins.
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Received 2x shoutouts from UCLA students for making students
"feel particularly included" in a CS class during the bi-annual
Computer Science Department Spring 2024 Town Hall Survey.
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Teaching Assistant (TA).
EC ENGR 117/COM SCI M138: Computer Systems Security. Winter 2024.
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Teaching Assistant (TA) for EC ENGR 117: Computer Systems
Security taught by Dr. Yuan Tian. Responsible with driving novel
content and facilitating pedagogy through writing new course
assignments, updating content curriculum, developing autograder
scripts, writing course & quiz review problems, and teaching lab
sections. More information soon.
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Recevied a shoutout from UCLA students in a poll for "Best TA
You've Had at UCLA" conducted on the
UCLA Reddit.
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Returning Learning Assistant (LA).
COM SCI 35L: Software Construction.
Winter 2024.
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Helped teach COM SCI 35L: Software Construction taught by Dr.
Paul Eggert.
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Developed activities and practice problems to teach students
about software construction topics (e.g. regular expressions,
Git and version control, etc). More information soon.
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New Learning Assistant (LA).
COM SCI 35L: Software Construction.
Fall 2023.
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Helped teach COM SCI 35L: Software Construction taught by Dr.
Paul Eggert.
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Ran weekly discussions teaching software construction topics
such as Linux, scripting, package management, version control,
etc. More information soon.
⚙️
New Jersey Governor's School of Engineering & Technology
(GSET)
The New Jersey Governor's School of Engineering & Technology
(GSET)
is an intensive residential summer program held at Rutgers University.
I am deeply passionate about the program and have been involved with
teaching some of the top engineering high school students in New
Jersey to engineering and computer science topics.
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Project Mentor.
SeBRUS: Mitigating Data Poisoning Attacks on Crowdsourced
Datasets with Blockchain. Summer 2023.
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Mentored five of the top 72 engineering high school students in
NJ in a computer systems security research project. Taught
security literature, threat modeling, AI security, collaborative
software development, full-stack development, and
blockchain/smart contract development.
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Guided students through developing a solution to address data
poisoning attacks in crowdsourced machine learning datasets by
using Ethereum smart contracts resulting in a research paper,
"SeBRUS: Mitigating Data Poisoning Attacks on Crowdsourced
Datasets with Blockchain", which was accepted to the
2023 MIT IEEE Undergraduate Research Technology Conference.
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Residential Teaching Assistant (RTA).
A Secure and Reliable Mobile Authentication Alternative
Utilizing Hand Structure
&
Modeling the Effects of Engagement Methods in Online
Crowd-sourcing Platforms. Summer 2022.
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Taught the top 71 engineering high school students in NJ through
workshops relating to engineering research, Git/GitHub, machine
learning, and LaTeX/Overleaf.
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Facilitated research as a project liaison for two research
groups who investigated using properties of structure-borne
sounds and machine learning models in MATLAB to identify hand
structure as a biometric mobile authentication system and
developing crowd-sourced engagement features for higher
education through a web application written in React.js.
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Guided both groups through developing research papers resulting
in two publications, "A Secure and Reliable Mobile
Authentication Alternative Utilizing Hand Structure" & "Modeling
the Effects of Engagement Methods in Online Crowd-sourcing
Platforms", at the
2022 MIT IEEE Undergraduate Research Technology Conference.