Welcome!
I'm Bryce, a masters student at UC Berkeley majoring in EECS. Recently, I graduated from UC Berkeley in Computer Science and Data Science with a domain emphasis in Economics.
Currently, my main interests lie in computer security, specifically in decentralized systems and AI safety in Large Language Models (LLMs).
I also work on full-stack development, though my recent projects focus on frontend engineering. In my free time, I enjoy reading webcomics,
watching (e)sports, and competing on Berkeley's collegiate osu! team (VOD).
Interested in reaching out? Contact me here: brywong@berkeley.edu
Research Experience
CoLink - Feb 2022 - Current
Advisor: Prof. Dawn Song (UC Berkeley EECS)
Program: URAP (Undergraduate Research Apprentice Program)
Tasks:
-
Designing and implementing a React frontend application to interact with CoLink, a secure Rust gRPC backend server that supports decentralized data collaboration
- Customized user login with JWT or MetaMask
- Entry creation within CoLink Datastore
- Execute decentralized tasks (i.e. federated learning, privacy-preserving inference) within the user framework
- Developing a JS-application SDK to provide developers with an easy-to-use API to build their own Javascript CoLink applications
- Skills: React, gRPC, Typescript, Node.js, Rust
Greater Good in Education (GGIE) - Feb 2021 - Aug 2021
Advisor: Dr. Valerie Shapiro (UC Berkeley School of Social Welfare)
Program: Data Science Discovery
Tasks:
- Main Tasks:
- Perfomed geospatial analysis + web-scraping to analyze how Social-Emotional Learning (SEL) resources were utilized by educators
- Explored the impact GGIE's website had on educators' teaching methodologies in different California counties
- Secondary Tasks:
- Curated Jupyter notebook templates for performing exploratory data analysis (EDA) on cleaned datasets
- Designed bash scripts to automate cleaning and aggregation of SQL data from GGIE website into formatted flatmaps
- Skills: SciPy (Python), SQL, Beautiful Soup, Bash
Presented Work:
- GGIE: Helping Educators Use Research Evidence (Video • Spring 2021 Data Science Discovery Showcase)
Industry Experience
Quantcast | Software Engineering Intern - Summer 2022
- Developed a distributed tracing tool to visualize requests made by Quantcast's Report Builder application
- Improved debugging efficiency for oncall tickets and identified bottlenecks within their microservice pipeline
- Skills: OpenTelemetry (Java), Jaeger, Spring Boot, Guice, Jenkins, Docker
Hashmap Inc. | Intern - Spring 2022
- Developed ML models with SciPy and InterpretML to predict performance of popular stocks (AAPL, GOOGL, etc.) given time series data
- Explored data labeling/augmentation (i.e. triple barrier method) and backtesting methods to analyze model performance
- Skills: SciPy (Python), Machine Learning
Lam Research Corporation | Software Engineering Intern 1 - Summer 2020
- Designed and documented a flexible editor application to create and modify encrypted macro scripts for Lam semiconductor wafer processing equipment
- Utilized an Angular/Electron.js framework to modernize pre-existing editor and improve overall user experience
- Skills: Angular, Typescript, Node.js, Electron.js
Teaching
Spring 2024 Resources: https://tinyurl.com/bryce-168-sp24
At Berkeley, I've enjoyed serving as a EECS TA/Tutor, a volunteer mentor for Berkeley's Computer Science Mentors
(CSM) organization, and an academic intern (AI).
To access my teaching resources from previous semesters, click here.
Academics
Below is a summary of the classes I have taken and a couple of class projects that I'm allowed to make public.
Technical Courses
Graduate Level:- Graduate Computer Security (CS 261)
- Deep Reinforcement Learning (CS 285)
- Graduate NLP (CS 288)
- LLM Foundations and Safety (CS 294-267)*
- Individual Research (CS 299)*
- Computer Security (CS 161)
- Operating Systems (CS 162)
- Internet Architecture and Protocols (CS 168)
- Efficient Algorithms and Intractable Problems (CS 170)
- Computer Vision and Computational Photography (CS 180)
- Foundations of Computer Graphics (CS 184)
- Introduction to Database Systems (CS 186)
- Introduction to Artificial Intelligence (CS 188)
- Introduction to Machine Learning (CS 189)
- Special Topics on Decentralized Systems (CS 194-196)
- Special Topics on Zero Knowledge Proofs (CS 194-238)
- Codebreaking DeCal (CS 198-118)
- Principles & Techniques of Data Science (DATA C100)
- Probability and Random Processes (EECS 126)
- Natural Language Processing (INFO 159)
- Introduction to Computer Programs (CS 61A)
- Foundations of Data Science (DATA C8)
- Data Structures (CS 61B)
- Machine Structures (CS 61C)
- Multivariable Calculus (MATH 53)
- Linear Algebra and Differential Equations (MATH N54)
- Discrete Mathematics and Probability Theory (CS 70)
- Designing Information Devices and Systems I (EECS 16A)
- Designing Information Devices and Systems II (EECS 16B)
- Programming Abstractions (CS 106B)
- Client-Side Internet Technologies (CS 193C)
Breadth Courses
Economics:- Introduction to Economics (ECON 2)
- Microeconomics (ECON 100A)
- Game Theory (ECON C110)
- Econometrics (ECON 140)
- Personal Finance (MBA 296-006)*
- Social Implications of Computer Technology (CS 195)
- Teaching Techniques for Computer Science (CS 375)
- Human Contexts and Ethics of Data (DATA C104)
- Human Biological Variation (INTEGBI 35AC)
- The Nature of Mind (XPHILOS 3)
- Introduction to Comparative Politics (XPOLSCI 2)
- General Psychology (XPSYCH 1)
- Psych Research and Data Analysis (PSYCH 101)*
- The Legacies of J.S. Bach (MUSIC 128)
- Speedcubing (Math 198-002)*
- The Perennial Heroic Struggle (XENGLIS R1A)
- Writing About Performance (COLWRIT R4B)
Selected Projects
CS 180- Project 1: Colorizing the Prokudin-Gorskii Photo Collection
- Project 2: Fun with Filters and Frequencies
- Project 3: Face Morphing
- Project 4: Auto-Stitching Photo Mosaics
- Project 5: Facial Keypoint Detection with Neural Networks
- Final Project: Lightfield Camera and Gradient Domain Fusion
Contact
If you're interested in connecting, feel free to reach out!
Email: brywong@berkeley.edu