JL

Computer Science • UPR Río Piedras

Building software that

I'm Jonathan J. Lois Ortiz — a junior CS student obsessed with clean systems, machine learning, and products that actually help people.

Get in touch LinkedIn See my work
0+

Students tutored

0%

Model accuracy

0%

Cloud call reduction

0+

Active roles

About Me

I'm a junior Computer Science student passionate about Machine Learning and Software Engineering. I love tackling problems that blend data, design, and real-world impact — whether that's predicting game outcomes, redesigning a university platform, or optimizing cloud infrastructure.

I'm currently seeking internships and research opportunities where I can apply my technical skills and keep growing alongside experienced teams.

🎓

Education

B.S. Computer Science, UPR RP

📍

Location

San Juan, Puerto Rico

🔭

Focus

ML • Full-Stack • Cloud

✉
👥

LinkedIn

jonathan-josé-l

Education

🎓

B.S. in Computer Science

University of Puerto Rico, Río Piedras  ·  Aug 2023 – May 2027

Minor: Information Systems & Business Intelligence

Major GPA

3.7

Organizations

AECC

Data Structures Databases Artificial Intelligence Cybersecurity Big Data Business Intelligence Machine Learning Statistics

Experience

Project Lead Software Engineer

Oct 2025 – Present  ·  CRiiAS Título V, UPR

React TypeScript Django PostgreSQL
  • Currently developing a full-stack application using React + TypeScript on the frontend and Django REST Framework + PostgreSQL on the backend, replacing a legacy static site with a fully dynamic platform.
  • Implemented Google OAuth 2.0 via Django Allauth, enabling secure single-sign-on for students and staff using their institutional UPR Google accounts — eliminating password management entirely.
  • Built an in-person attendance tracking system allowing students to log check-ins in real time, replacing Jotform-based check-ins with a structured digital record linked to each student's profile.
  • Will build an admin analytics dashboard surfacing registration trends, session occupancy, and student activity — giving program coordinators real-time data visibility for the first time.

🔗 Live site link will be published once the platform is deployed to production.

CRiiAS site before redesign
Before
CRiiAS site after redesign
After
  • Delivered one-on-one and group tutoring sessions for courses spanning Data Structures, Calculus I and Discrete Mathematics.
  • Supported over 80 students in a single semester, consistently receiving high satisfaction ratings from program coordinators and students alike.
  • Developed original practice problem sets, exam guides, and concept summaries tailored to common student pain points identified through session feedback.
  • Coordinated with faculty to align tutoring content with course syllabi, ensuring students received targeted, exam-relevant support at the right time.
  • Contributed to a production Flutter mobile app used by active customers, implementing UI features, fixing bugs, and shipping code through a structured review and QA pipeline.
  • Integrated third-party messaging APIs and internal REST endpoints to build real-time communication workflows between drivers and dispatchers within the app.
  • Identified a critical inefficiency in cloud function invocation patterns and reduced daily Google Cloud function calls by 40% through caching strategies and request batching — directly lowering infrastructure costs.
  • Worked with Firebase Firestore and Firebase Auth to manage real-time data sync and user session state across the mobile client.
  • Processed and analyzed large-scale Aerosol Optical Depth (AOD) and PM10 particulate datasets sourced from remote sensing instruments and ground-level monitoring stations across Puerto Rico.
  • Used Pandas and NumPy to clean, merge, and transform raw sensor data into structured formats suitable for statistical analysis and publication-ready figures.
  • Wrote automated Python scripts to scrape external data sources, perform format conversions (NetCDF, CSV, Excel), and organize output files for reproducible research pipelines.

Projects

NBA Win % Prediction Model

A Random Forest regression model trained on per-team season stats to predict win percentage with high statistical confidence.

Python Scikit-learn Pandas NumPy
95% R² accuracy

Cloud Multiplayer Server

Deployed and self-managed a Java game server on Oracle Cloud Infrastructure — including VCN setup, security policy hardening, and upgrades.

Java Oracle Cloud Linux Networking
Java 17 → 21 upgrade

Skills

Languages

Python Java JavaScript TypeScript SQL Dart C

Frameworks & Tools

React Django Flutter Firebase PostgreSQL Git Linux

Machine Learning

Scikit-learn Pandas NumPy Matplotlib Random Forests Feature Eng.

Cloud & Infrastructure

Google Cloud Oracle Cloud Ubuntu VCN / Networking REST APIs

Let's work together

Open to new opportunities

I'm looking for internships, software engineering roles, and ML research collaborations. Don't hesitate to reach out.

jonathan.lois@upr.edu LinkedIn ↗