Alana FergusonGet in touch
Portfolio2021 — 2026

Alana Ferguson

I'm a Computer Science and Neuroscience student at Princeton building products at the intersection of AI, design, and human behavior.

FocusProduct management, product design, software engineering
BasedPrinceton, NJ
Contactaf9139@princeton.edu
01

Experience

13 roles
02

Projects

Self-directed
03

Apps

25 · Adaptive.ai

AI apps I designed and shipped at Adaptive.ai, taking each from idea to a working, installable product. Open any one to read how I approached it.

04

Education

Princeton

Princeton University

B.A. Computer Science, expected May 2027

Minors in Neuroscience, Global Health & Health Policy, Entrepreneurship

Recognition

2025
McKnight Endowment Fund for Neuroscience, Pecot Fellow

A year of funded independent research.

2025
McKnight Neuroscience Conference, Aspen

Presented findings, with faculty feedback on model refinement and pipeline scalability.

2025
Princeton Neuroscience Institute Showcase

First author.

2023

Jaepel, Satterfield, Shultz, Mody, Ferguson, Urban and Fitzpatrick.

Relevant coursework

  • COS 398Junior Independent Work
  • COS 432Information Security
  • COS 480Doctors and Digits, Computer Science in Clinical Medicine
  • COS IW 07Technology Design for Sports, Health and Assistive Applications
  • COS 360Computational Models of Cognition
  • COS 324Introduction to Machine Learning
  • COS 316Principles of Computer System Design
  • COS 226Algorithms and Data Structures
  • COS 240Reasoning About Computation
  • COS 217Introduction to Programming Systems
  • COS 126Computer Science, An Interdisciplinary Approach
05

About

I build products at the intersection of AI, design, and engineering. What I care about most is the moment an idea becomes something people can actually use, so I work end to end: designing in Figma, building the backend and the app, and shipping fast against real feedback.

My foundation is in neuroscience, and it's the lens I bring to everything I build. Studying how the brain takes in information and turns it into behavior trained me to start from the person, not the feature: what they are actually trying to do, where they get stuck, and why. I'm most excited when I get to use that understanding of people to solve real problems for them.

That's taken me across research labs, startups, and consumer products, from training machine learning models for behavioral analysis to shipping 30+ mobile apps and full-stack marketplace features. I like taking vague, ambiguous problems and turning them into products that are both technically solid and genuinely intuitive.

Outside of academics and product work, I played Division I rugby for several years and I'm a Pilates instructor. I enjoy designing experiences that bring together movement, wellness, and community.

ProductRoadmapping Requirements definition Success metrics A/B testing and rollout Dark launching and feature flags User research Prioritization Cross-functional delivery Competitive analysis
LanguagesPython TypeScript JavaScript Java C Go Swift / SwiftUI R SQL MATLAB Bash ARMv8 Assembly
Frontend & mobileReact React Native Expo Next.js Reanimated Skia React Query WebGL CSS
Backend & infrastructureFalcon PostgreSQL pgvector Redis ClickHouse Typesense Alembic Hatchet AWS S3 Stripe Stytch
Machine learningPyTorch NumPy LLM APIs (GPT-4o, GPT-2) CLIP embeddings Transformer interpretability Vendi Score CNNs K-means and clustering Hidden Markov Models Reinforcement learning Anomaly detection Fairness-aware ML EEG signal processing (CSP)
Research & labSLEAP DeepLabCut Keypoint MoSeq OpenCV NWB Jupyter HPC / SLURM Raspberry Pi Arduino STED & two-photon imaging ImageJ Git
DesignFigma Design systems Information architecture Prototyping User research Squarespace
Data & analyticsPostHog Mixpanel Tableau Metabase R + Google Sheets API Experiment design Offline evaluation Backtesting
06

Get in touch

Open to full-time product roles across AI, design, and engineering.

af9139@princeton.eduLinkedIn ↗