Emily Liang

Computer Science, Mathematics, and Business
Student at UT Austin

About Me

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Emily Liang

Turing Scholar (Computer Science Honors)

I am pursuing a BS in Computer Science and Mathematics as well as a Minor in Business as a Turing Scholar at the University of Texas at Austin.

Location

Austin, TX

Education

UT Austin

Experience

3 years

Interests

Rock Climbing, Hiking, and Photography

As a Turing Scholar at UT Austin, I am passionate about bridging the gap between theoretical computer science and practical applications. My journey in technology began with a curiosity about how computers work at their core. My interests span from low-level systems programming to AI/ML.

Beyond coding, I am an avid rock climber and hiker, finding that the problem-solving skills I develop on the wall often translate to my technical work. I believe in creating technology that is not just innovative, but also accessible and impactful.

Skills

My technical expertise spans from front-end frameworks to systems programming, with a strong foundation in computer science principles.

Languages

  • Python
  • JavaScript/TypeScript
  • Java
  • C/C++
  • Verilog
  • x86 and ARM Assembly

Frontend

  • React/Next.js
  • HTML5/CSS3
  • Tailwind CSS
  • Responsive Design

Backend

  • Node.js
  • Express.js
  • SQL/NoSQL
  • RESTful APIs

Libraries

  • pandas
  • NumPy
  • Matplotlib
  • Scikit-learn
  • Keras
  • TensorFlow

Coursework

  • Honors Operating Systems
  • Honors Computer Architecture
  • Honors Data Structures
  • Honors Discrete Mathematics
  • Artificial Intelligence
  • Software Engineering

Tools & Others

  • Git/GitHub
  • Docker
  • Jupyter Notebook
  • IntelliJ IDEA
  • VS Code

Experience

Undergraduate Research Assistant

The University of Texas at Austin • Jan 2025-present

  • Assist with ROS (Robot Operating System) implementation and testing.
  • Conduct experiments with AugRE (Augmented Robot Environment to Facilitate Human-Robot Teaming).
  • Standardized data collection procedures, ensuring consistent data formatting, and accelerated experimental analysis by 15% through enhanced data usability.

Simulation and Validation Engineer

Longhorn Racing Internal Combustion • September 2024-present

  • Collaborated on LapSim (vehicular simulation) to drive 10+ engineering design choices.
  • Built an automated graph generation tool, decreasing the time spent on creating visualizations by 60% and enabling faster identification of key trends from collected datasets.

First-Year Trading and Technology Program (FTTP)

Jane Street • March 2025

  • Jane Street's First Year Trading and Technology 3-day program in NYC.
  • Chosen as one of 100 students across the US and Canada to attend.
  • Used a game theoretic and mathematical approach while competing in an Estimathon to determine an appropriate range of values for trivia questions.

Software Engineering Intern

Lockheed Martin Aeronautics • September 2023 – May 2024

  • Developed a version compatibility lookup tool, reducing software mismatch by 70% and streamlining coordination.
  • Collaborated the Air Force Research Laboratory, L3 Harris, and Raytheon on research effort.

Technology Project Manager

Keller Independent School District • September 2023 – September 2024

  • Led a team of 10 to support district-wide technology deployment for 35,000 students and 4,000 faculty members.
  • Delivered training to 100+ educators on EdTech platforms, reducing software onboarding issues by 50% and ensuring seamless technology adoption across 40+ campuses.

Summer Swim Instructor

Lakeside Aquatics Club • May 2023 – September 2024

  • Demonstrated expertise in various swim strokes, techniques, and water safety protocols.
  • Conducted assessments to evaluate participants' swimming abilities and designed customized lesson plans to meet their specific needs and goals.
  • Created a safe and supportive learning environment, ensuring the well-being and comfort of participants, ages 3-15 at all times.

Projects

JPEB: 16-bit Computer

Custom 16-bit computer from scratch, including a custom ISA inspired by Dr. Bruce Jacob's RiSC-16, compiler, assembler, processor, and emulator.

Stock Market Prediction

This project explores the use of deep learning—specifically Long Short-Term Memory (LSTM) networks—to analyze and forecast stock market trends.

Vision Guardian

Built a video-based glaucoma and cataract detection system using OpenCV, MediaPipe, and TensorFlow for accessible healthcare technology.

Resume

View my detailed resume to learn more about my experience and qualifications.

View Resume