Emily Liang
Computer Science, Mathematics, and Business
Student at UT Austin
About Me
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