Software Engineer

Hi, I'm Scott.

M.S. EECS @ UC Berkeley (2020)

SWE @ Lyft, Rubrik; Data Science @ Brilliant

Head Teaching Assistant @ DATA 8 / DATA 100

Computer Vision Research @ RISELab


Berkeley / San Francisco, CA

scott.lee@berkeley.edu

Resume

About Me

I'm Scott, a Bay Area native, tea connoisseur, and turtle enthusiast. Currently, I'm completing my Master's at UC Berkeley. In the past, I've had the pleasure of working at some amazing companies: Lyft, Rubrik and Brilliant. I'm also pretty involved in teaching data science at Berkeley. I am currently advised by Joseph Gonzalez at RISELab, working on vision-related problems.

I'm passionate about designing solutions to complex problems. More specifically, my academic and industry interests include artificial intelligence, machine learning, computer vision, and automation. I'm also deeply interested in the intersection of technology and education, including large-scale course logistics and infrastructure platforms. I fill my free hours by climbing rocks, baking bread, drinking matcha, and obsessing over music.

Education & Skills

Education
University of California, Berkeley 🐻

M.S. EECS

Concentration: AI & Computer Vision
Advisor: Joseph Gonzalez
2019 - 2020

B.A. Computer Science

3.86 / 4.00, High Distinction
2016 - 2019

Teaching

Spring 2020: DATA 8 Head TA
Fall 2019: DATA 8 Head TA, PH 196 Teaching Fellow
Spring 2019: DATA 8 Head TA
Fall 2018: DATA 100 Head TA
Spring 2018: DATA 8 Head TA
Fall 2017: DATA 8 TA

Skills

Python (PyTorch, TensorFlow, sklearn, Pandas, Spark)
SQL, R, Java, Go, C

HTML, CSS/LESS, Javascript, jQuery, Bootstrap

Relevant Coursework

Computer Science

Machine Learning (CS 189)
Computer Vision (CS 280)
AI & Natural Language Processing (CS 288)
Artificial Intelligence (CS 188)
Advanced Robotics (CS 287)
AI in Healthcare & Medicine (PH 196)
Algorithms & Complexity (CS 170)
Database Systems (CS 186)
Data Structures (CS 61B)
Computer Architecture (CS 61C)

Statistics & Mathematics

Probability & Random Processes
(EECS 126, STAT 134)
Optimization Models (EECS 127)
Theoretical Statistics (STAT 135)
Linear Modeling (STAT 151A)
Game Theory (STAT 155)
Introduction to Financial Engineering (IEOR 221)
Discrete Math (CS 70)
Linear Algebra & Information Systems
(MATH 54, EE 16A)
Multivariate Calculus (MATH 53)

Experience

Lyft

SWE Intern, Summer 2019

Dual project between infrastructure (generalized pricing API) and modeling (MVP of new pricing model). Conducted extensive data analysis and feature engineering, created robust endpoints to fetch features, and ran pricing experiments.

Rubrik

SWE Intern, Summer 2018

Designed and implemented a robust cloud database system compatible with various cloud providers as part of Rubrik's first SaaS product, Office 365.

RISELab

Graduate Researcher, 2018 - Present

Currently studying computer vision techniques, advised by Joseph Gonzalez. Previously worked on EKG classification at UCSF School of Nursing.



Brilliant

Data Science / Education Intern, Summer 2017

Conducted data analysis using SQL and Python on millions of emails to evaluate email algorithm effectiveness. Contributed to curricula for CS Fundamentals and Artificial Neural Networks courses.

Projects

Fido

Python

A Slackbot that has a variety of features to assist teaching staff members, including roster lookup, Piazza paging, and groupshouts.

BerkeleyTime

HTML, CSS, JS, Django, MySQL...

An augmented course catalog that provides data on courses, enrollment trends, grade distributions, and more. I have filled both Product Manager and Lead Engineer roles in the past.

Jesture

HTML, CSS, JS, Python, C, AppleScript...

A gesture detection application created with the Synaptics touchpad; implemented API for Spotify, Slack, Facebook, and more, then linked to a sleek web UI.

Object-Focused Edge Detection [Paper]

Python, PyTorch

A general method for altering general algorithms for edge detection in order to produce edge mappings that focus on one or few individual objects in an image.

Light ResNet

Python, PyTorch

A lightweight PyTorch implementation of ResNet with essential configurable parameters.


Song Classifier

Python, TensorFlow

A deep learning classifier that categorizes songs as either country or hip-hop. Achieved an accuracy rate of 89% and was selected as one of 10 winners of a 200-member Kaggle contest.

Contact Me

I'm currently located in Berkeley, CA. If you want to get in touch or grab a cup of tea, email is the best way to reach me. For current students, you might get an answer faster from Piazza rather than emailing me.