I'm Scott, a Bay Area native, tea connoisseur, and turtle enthusiast. Currently, I'm an intern on the Adaptive Pricing team at Lyft, and I'll be returning to UC Berkeley to complete my Master's. In the past, I've also worked at Rubrik and Brilliant. I'm also pretty involved in teaching data science at Berkeley. In addition, I am advised by Joseph Gonzalez at RISELab, where I study computer vision (specifically human 3D reconstruction).
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.
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
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
Programming
Python (PyTorch, TensorFlow, Sklearn, Pandas, Spark)
SQL, R, Java, Go, C
Web Development
HTML, CSS/LESS, Javascript, jQuery, Bootstrap
Computer Science
Machine Learning (CS 189)
Computer Vision (CS 280)
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)
Introduction to Financial Engineering (IEOR 221)
Theoretical Statistics (STAT 135)
Linear Modeling (STAT 151A)
Discrete Math (CS 70)
Linear Algebra & Information Systems
(MATH 54, EE 16A)
Multivariate Calculus (MATH 53)
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.
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.
Graduate Researcher, 2018 - Present
Currently studying computer vision techniques, advised by Joseph Gonzalez. Previously worked on EKG classification at UCSF School of Nursing.
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.
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.
Python, PyTorch
A lightweight PyTorch implementation of ResNet with essential configurable parameters.
Python, TensorFlow
Created 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.
HTML, CSS, JS, Django, MySQL...
BerkeleyTime is 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.
HTML, CSS, JS, Python, C, AppleScript...
Created gesture detection application with the Synaptics touchpad; implemented API for Spotify, Slack, Facebook, and more, then linked to a sleek web UI.
