Geoffrey Liu

Undergraduate at Stanford University studying Computer Science and Symbolic Systems, building software where neuroscience, cognition, and AI meet.

Research

A Gamified Go/No-Go Paradigm for the Epilepsy Monitoring Unit

BAYLOR COLLEGE OF MEDICINE · UNITY / C#

At Baylor College of Medicine, I developed a gamified inhibitory control task in Unity and C# for neuroscience research with epilepsy patients. Because patients in clinical settings have different abilities, I developed adaptive difficulty that adjusted in real time to each participant's performance. I also added a points-and-lives system and score display to keep participants engaged. Watching patients lean in and grin as they earned points made the work feel real: something I had coded was now an experience people wanted to participate in. The project led to a first-author Society for Neuroscience abstract and contributed to my recognition as a Regeneron STS Scholar and ISEF Finalist.

First page of Geoffrey Liu's Society for Neuroscience poster, 'A Gamified Go/No-Go Paradigm for the Epilepsy Monitoring Unit'
Society for Neuroscience poster, first-author abstract (2025). Click to open the full PDF.

Publications

A gamified go/no-go paradigm for the epilepsy monitoring unit.

Society for Neuroscience (SfN) 2025

Show publication

Neural signatures and personalized neuromodulation in a subject experiencing context-dependent inhibitory control deficits.

NeuroImage

Show publication

Experience & leadership

Research Intern, Baylor College of Medicine, Houston, TX

Mar 2024 – Jul 2026
  • Independently designed, developed, and tested a real-time C#/Unity software platform with an interactive GUI across 10+ features, writing 30,000+ lines of production code deployed in a hospital clinical environment.
  • Built automated MATLAB pipelines processing 60+ GB of behavioral and neural data across 5,000+ trials; applied statistical analysis and machine learning methods and presented results at the Society for Neuroscience annual meeting.

Instructor, iCode School Franchise, Pearland, TX

Apr 2023 – Jul 2026
  • Taught programming and software development to 200+ students across Game Development, Robotics, Competitive Programming, Web Development, and Mobile App Design, demonstrating strong verbal communication and technical instruction skills.
  • Developed curriculum, recruited and mentored 17 new instructors, and earned 6 performance-based promotions.

Team Leader, NASA App Development Challenge

Oct 2023 – Dec 2023
  • Led a team of 9 developing an interactive application in Java and Unity/C# to visualize lunar terrain, building GUI controls and processing thousands of data points into dynamically rendered 3D meshes.

Co-Founder & Co-President, High School Computer Science Club

Aug 2024 – Mar 2026
  • Organized and led 6 teams for HPE CodeWars and UIL competitions; mentored 20+ members and ran weekly technical workshops.

Education

Stanford University, Stanford, CA

Expected Jun 2030
  • B.S., Computer Science and Symbolic Systems
  • Relevant coursework: Programming Abstractions; Thinking with AI; Great Ideas in Graphics; Linear Algebra, Multivariable Calculus, and Modern Applications; Coding for Social Good

Technical skills

Languages

C++PythonJavaC#JavaScriptMATLABSQL

Areas

Data StructuresAlgorithmsObject-Oriented ProgrammingMachine LearningGenerative AIAI AgentsComputer GraphicsReal-Time SystemsData AnalysisWeb DevelopmentAI-Assisted Development

Tools & environments

GitWindowsLinuxUnity

Off the clock

The gym, the arena, and a new rabbit hole.

7 / 7

In the gym, daily

I train every day. It is the one non-negotiable on my calendar, and the most reliable reset I know between classes, code, and research.

Top 1,000

Clash Royale

I started in the beginner arenas and climbed to the top 1,000 players in the world, out of millions. It looks like a card game; it plays like real-time chess with elixir.

EV+

Poker, lately

My newest interest, and I am excited to keep learning it. The strategy, the probability, the decision-making under uncertainty: every hand is a small exercise in expected value.