About

Hi! I’m Richard and I am a Quantitative Technologist at Radix Trading in Chicago.

Before that, I completed my BS in Electrical Engineering and Computer Science at UC Berkeley where I taught CS 70 for 7 semesters and lead a research group exploring federated learning, advised by James Demmel.

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Employment History

Radix Trading Chicago, IL
Quantitative Technologist August 2023 - Present

I work on the Automation Team, where I’ve worked on alpha development, exchange order entry, reconciliation, dev tools, metrics monitoring, order sizing, and US trading hours oncall.

Python • C++

The Voleon Group Berkeley, CA
Software Engineer Intern May 2022 - August 2022

I worked on the Infrastructure Engineering Team, where I developed APIs and created a dashboard to collect test metrics and identify flaky tests. I also profiled and analyzed Airflow DAGs to search for sources of slowdown in production jobs.

Python • Docker • Groovy • Elasticsearch • Kibana • Airflow

Amazon Bellevue, WA
Software Development Engineer Intern May 2021 - August 2021

I worked on the On-Road Execution Team, where I developed an internal debugging tool to rapidly retrieve transporter itineraries by transporter ID and time stamp.

Java • Typescript • AWS S3 • AWS Glue • AWS Kinesis • AWS CDK

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Academic History

University of California, Berkeley (08/2019 - 05/2023)

B.S., Electrical Engineering and Computer Sciences - GPA: 3.93/4.0

Technical Coursework

• CS 61A - The Structure and Interpretation of Computer Programs
• CS 61B - Data Structures
• CS 61C - Great Ideas in Computer Architecture
• CS 70 - Discrete Mathematics and Probability Theory
• CS 162 - Operating Systems and System Programming
• CS 170 - Efficient Algorithms and Intractable Problems
• CS 188 - Introduction to Artificial Intelligence
• CS 189 - Introduction to Machine Learning
• CS C267 - Applications of Parallel Computers (Graduate)

• CS 294-220 - Computational Learning Theory (Graduate)

• EE 16A - Designing Information Devices and Systems I
• EECS 16B - Designing Information Devices and Systems II
• EE 120 - Signals and Systems
• EECS 126 - Probability and Random Processes

• EECS 127 - Optimization Models in Engineering

• MATH 53 - Multivariable Calculus

• MATH 110 - Linear Algebra

• STAT 150 - Stochastic Processes
• STAT 157 - Forecasting

Honors

• Dean’s List
• EECS Honor Society
• Eta Kappa Nu (HKN) Honor Society
• Outstanding Graduate Student Instructor Award

Teaching

• CS 70 - Discrete Mathematics and Probability Theory
  • Head TA: Spring 2023, Fall 2022, Spring 2022, Fall 2021, Spring 2021
  • TA: Fall 2020, Summer 2020

Redlands High School (08/2015 - 05/2019)

• AIME Qualifier: 2018, 2019

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Misc.

I like movies, the Sierras, Jane Austen, and Liverpool Football Club.

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