Hi, I'm Didier.

A Computer Science junior at Northwestern University, passionate about applying technology to achieve social impact. I've contributed to projects like Flogram (a web-based compiler) and Tunepad (an ed-tech platform combining music and coding). I also enjoy music and mentoring, always looking for ways to use code to empower others.

Projects

Flogram Web Compiler

Built a secure and scalable backend with SpringBoot + PostgreSQL for a web-based compiler. Implemented user authentication, project compilation, and code execution services.

Stack: Web Assembly, Spring Boot, PostgreSQL, REST API
View Project

89Transfers Booking Platform

Full-stack app for booking bus transfers with Google Maps routing, online payments via Stripe, and live driver notifications via WhatsApp, Email, and Slack.

Stack: NestJS, Prisma, Stripe, Google Maps
View Project

TunePad Drum Logger

Embedded Python + C system for recording and replaying drum sequences to improve music education. Admin dashboard built with React + Flask.

Stack: Python, C, React, Flask
View Project

Income Predictor ML

Trained Random Forest and Logistic Regression models on Kaggle census data to predict income brackets. Evaluated using KNN and confusion matrix; visualized with Tableau.

Stack: Python, Scikit-learn, Tableau
View Project

Racket Test Generator

Developed an AI-powered test generator for Racket code using GPT-3.5. Integrated with DrRacket and CLI to streamline debugging.

Stack: GPT-3.5, DrRacket

LLMTyped DT

Research project investigating LLM-generated TypeScript types for JavaScript libraries. Built a tool that converts JS libraries to TypeScript, compares generated types to DefinitelyTyped definitions, and identifies mismatches to compile comprehensive reports.

Stack: Python, JavaScript, TypeScript, HTML, CSS

Experience

Teaching Assistant (DSA & Programming Languages)

Northwestern University · September 2024 – Present
  • Guided 120+ students in mastering data structures (AVL trees, heaps, graphs) through labs and code reviews, fostering algorithmic thinking and contributing to a 20% improvement in weekly lab completion rates.
  • Created and delivered real-world algorithm demos (e.g., O(n log n) sorting), tailoring instruction to diverse learners and improving in-class application accuracy by 25% on post-lab assessments.
  • Assessed 20+ assignments weekly and provided personalized feedback, contributing to a 15% class-wide performance increase and more profound comprehension of core concepts.

CPS GenAI Specialist Intern

Chicago Public Schools · June 2025 – September 2025
  • Led cross-functional coordination with curriculum, IT, and admin teams to design a scalable GenAI rollout pipeline across 600+ schools, aligning training priorities and cutting approval delays by 35%
  • Developed custom GenAI solutions using Python and JavaScript to automate educator workflows, including lesson plan generation and student assessment tools, cutting repetitive administrative workflows by an estimated 25%.

Tunepad – Software Engineering Intern

Northwestern University · June 2024 – September 2024
  • Built an embedded system (Python + C) to log and replay drum sequences, enriching music pedagogy and increasing student engagement by 30%.
  • Led UI design and implementation for a real-time React + Flask dashboard, integrating visual task tracking and admin alerts, streamlining oversight and clarifying cross-team responsibilities, leading to a 40% rise in operational transparency.
  • Refactored browser-based coding lesson pipeline in collaboration with education leads, resolving async errors and elevating session completion rates by 20% for 200+ K–12 students.

Research Student – Programming Languages

Northwestern University · May 2024 – August 2024
  • Under mentorship of Prof. Christos Dimoulas, I developed an automated test-generation tool for Racket programs, using chain-of-thought prompting to achieve high accuracy and broad coverage. The tool supports Northwestern faculty in CS321 (Programming Languages) for assignment preparation and is being applied in professor-led research projects to streamline the generation of rigorous test suites.