About Me
I'm Evan Maus, a student at UC Berkeley pursuing a dual Bachelor of Arts in Data Science & Economics, graduating December 2026. I'm a full-stack engineer building fast, reliable applications with TypeScript, Next.js, Python, and PostgreSQL. I founded breakouts.trade, shipped it to 458 signups, and run the trading robot behind it on a real-money account.
Education
University of California, Berkeley
Dual B.A. Data Science & Economics
Relevant Coursework
- Data Structures (CS 61B)
- Structure and Interpretation of Computer Programs (CS 61A)
- Artificial Intelligence (CS 188)
- Principles & Techniques of Data Science (Data C100)
- Probability for Data Science (Data C140)
- Linear Algebra (Math 56)
- Econometrics (Econ 140)
- Econometrics: Advanced Methods (Econ 143)
- Behavioral Finance (UGBA 136F)
- Microeconomics (Econ 100A) and Macroeconomics (Econ 100B)
- In progress, Fall 2026: Data, Inference and Decisions (Data C102); Data Mining and Analytics (Data 144); Time Series (Stat 153); Asset Pricing and Portfolio Choice (Econ 139); Macroeconomic Policy (Econ 134)
Coursework Projects & Self-Study
Build Your Own World (CS 61B, Java)
A three-person course project: I wrote the procedural world generator, the main menu, the state management and the save-and-replay feature, with JUnit tests. Course labs covered balanced binary search trees, union-find (percolation with the backwash fix), hashing, heaps and graph search.
Artificial Intelligence projects (CS 188, Python and PyTorch)
Five course projects on a provided skeleton: graph search, adversarial search with alpha-beta pruning, value iteration and Q-learning, Bayes-net and hidden-Markov inference with particle filtering, and PyTorch models including a recurrent language classifier and a hand-written causal self-attention block.
Pre-registered quantile-regression study (Econ 143)
Locked the hypothesis in a timestamped commit before the estimator ran, then reported the null as it came, with a bootstrap interval and a shuffled-label placebo. Code and write-up at github.com/evwillow/econ143-project.
Self-Directed AI/ML Coursework
Completed practical courses covering tensors & autograd, nn.Module, DataLoaders, training/evaluation loops, overfitting control (regularization/early stopping), and basic model types (MLP/CNN); used NumPy/Pandas for preprocessing and small applied exercises.
Supplemental Online Study
Python & backend fundamentals, plus quantitative topics (stochastic processes, numerical optimization, introductory quantitative finance) with small practice projects.
Technical Skills
Languages
Frameworks & Libraries
Tools & Platforms
Languages
- English: Native
- Spanish: Advanced (near-fluent) — speaking, reading, writing
- Chinese: Conversational; actively studying for professional use
Leadership & Activities
President, Student Climate Action Team
Oct 2022 - Sep 2023- Led a student-run environmental group, coordinating strategy, events, and community partnerships
- Started the organization and grew it to 20 active members through outreach and leadership
- Built the website from scratch to centralize events, announcements, and volunteer sign-ups
- Eagle Scout: led 100 volunteers on a community trail expansion project
My Mission
I am building a career at the intersection of AI, finance, and sustainability, leveraging data-driven methods to create scalable solutions with global impact. My interests span full-stack engineering, data pipelines, applied ML (PyTorch/TensorFlow), market-data tools, climate software, and product-led entrepreneurship.
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