Hi, my name is

Jayden Udall.

I'm a Computer Engineering and Statistics & Data Science student at UC Santa Barbara, passionate about using data to uncover new insights, make predictions, and solve problems. I'm always looking for new challenges and opportunities to grow my skills.

Check out some of my projects below!

Jayden Udall

01.About Me

I'm a senior at UC Santa Barbara graduating in June 2027 and pursuing Bachelor's degrees in Computer Engineering and Statistics & Data Science. Throughout my academic and professional journey, I've built a range of projects spanning fields like data science, business intelligence, and software/AI development. I've found through this experience that I'm most passionate about utilizing technology and AI to improve operational decicion-making, make predictions, and solve complex business problems.

02.Projects

Dynamic Portfolio Allocation with Reinforcement Learning

June 2026

Designed and implemented a reinforcement learning framework for dynamic portfolio optimization. Built a custom trading simulator, trained multiple RL agents, and evaluated their investment performance against traditional buy-and-hold strategies using historical market data.
NumPyPyTorchYahooFinanceMatplotlib
E-Commerce Pricing Optimization With Machine Learning

PSTAT 135, Spring 2026

Built a cloud-based pricing analytics pipeline in Google BigQuery to analyze 181K+ e-commerce transactions. Applied SQL, K-Means clustering, PCA, and supervised machine learning to forecast demand, identify product segments, and develop a pricing optimization framework for 20k+ unique products.
PythonBigQueryVertexAIscikit-learn
Target-Dependent Relevancy Classifier

Unwrap.ai x ACM.Industry, Jan–May 2026

Led a team of 6 to develop a cloud-native classiciation pipeline for Unwrap.ai to ingest and classify Reddit posts into multiple target-dependent company feedback categories using NLP embeddings and a single fine-tuned roBERTa model, achieving 95% accuracy.
PythonPyTorchHuggingFaceGoogle Cloud PlatformBigQuery
Ice Melting Experiment with ANOVA

PSTAT 122, Winter 2026

Designed and analyzed a 2³ factorial experiment to quantify the effects of airflow, container material, and light exposure on ice melting time using ANOVA and statistical modeling.
Rdplyrggplot2
Project BALANCE

Data4Good Hackathon, Feb 2026

Developed a data-driven site selection framework for sustainable data centers by modeling water usage efficiency from climate variables and integrating it with renewable energy and geographic data to identify optimal locations.
PythonNumPyGeoPandasMatplotlibOpen-meteo API
EEG Brain-Body Coupling Analysis

UCSB META Lab, Jan-Feb 2026

Developed a signal processing pipeline for UCSB's neuroscience lab to detect and quantify brain-body oscillatory coupling in EEG time series using multitaper spectral analysis and statistical peak detection.
MATLABRggplot2EEG Analysis
Meal2Macros with Neural Networks

ECE 180, Fall 2025

Built and evaluated deep learning models to predict carbohydrate content from meal descriptions using NLP embeddings and architectures including MLPs, RNNs, and LSTMs, achieving stronger performance with optimized sequence models.
PythonPyTorchMLPsRNNsLSTMs
Global Happiness Predictor

PSTAT 100, Summer 2025

Data-driven modeling system to analyze and predict global happiness using socioeconomic indicators through multiple linear regression and statistical evaluation.
Rdplyrggplot2

03.Skills

Languages

  • ▸Python
  • ▸R
  • ▸SQL
  • ▸C++
  • ▸TypeScript

Libraries

  • ▸Pandas
  • ▸NumPy
  • ▸Scikit-learn
  • ▸PyTorch
  • ▸Matplotlib
  • ▸dplyr

Web Development

  • ▸React
  • ▸Next.js
  • ▸HTML
  • ▸RESTful API
  • ▸PostgreSQL

Tools & Platforms

  • ▸Power BI
  • ▸Git
  • ▸Cursor
  • ▸Google Cloud Platform
  • ▸Google Colab
  • ▸Jupyter