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)


  • 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


  • 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:

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


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.

Teaching History

  • Spring 2024
  • Summer 2023 / Fall 2023
  • Fall 2022 / Spring 2023
  • Fall 2021 / Spring 2022
  • Spring 2021
  • Fall 2020
  • Spring 2020


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)*
Upper Division:
  • 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)
Lower Division:
  • 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)
Stanford High School Summer Session (Summer 2017):
  • Programming Abstractions (CS 106B)
  • Client-Side Internet Technologies (CS 193C)

Breadth Courses

  • 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)
Other Breadths:
  • 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 CS 184 INFO 159


If you're interested in connecting, feel free to reach out!
Email: brywong@berkeley.edu