Rel Guzman

I build scalable software with a strong focus on UX/UI and architecture. With over 3 years of experience in full-stack development and an academic background in AI and deep learning, I bridge the gap between elegant design, robust engineering, and intelligent systems.

Email GitHub LinkedIn Behance

Tech Stack & Tools

TypeScript JavaScript Python React Next.js Node.js NestJS PostgreSQL MongoDB Docker AWS Figma
TypeScript JavaScript Python React Next.js Node.js NestJS PostgreSQL MongoDB Docker AWS Figma

Professional Experience

University Lecturer

Mar 2026 – Present

Univ. Tecnológica del Perú

  • Teaching core concepts of innovation and digital transformation across virtual and in-person classes.
  • Integrating AI tools, Python prototypes, and Figma to facilitate student ideation and prototyping.
  • Mentoring students in developing digital solutions applying Agile, Scrum, and Kanban methodologies.

Web Dev Instructor

Jan 2026 – Feb 2026

InfoUNSA

  • Designed and delivered hands-on web development sessions covering UI design, HTML, CSS, and prompting.
  • Integrated modern tools like Figma, VS Code, and Gemini into an end-to-end development workflow.

Web Developer

Nov 2024 – Present

NoCountry

  • Developed multiple platforms including a Healthcare Care Tracking Platform using React, TS, and Supabase.
  • Architected an AI-driven analytics SaaS (DataSense-AI) using FastAPI, Gemini API, and React.
  • Designed microfrontend architectures via Webpack Module Federation for e-commerce platforms.
  • Led frontend development and UX/UI design across FinTech, EdTech, and E-commerce domains.

Deep Learning Tutor

Jun 2023 & Jun 2024

Neuromatch Academy

  • Taught advanced Python and Jupyter sessions on LLM architectures and deep neural networks to global researchers.
  • Supervised and mentored students through complete machine learning research lifecycles.

PhD Researcher & Teaching

Mar 2019 – Mar 2023

University of Sydney

  • Developed a sequential optimization framework for adaptive Model Predictive Control (MPC) using Python.
  • Published high-impact research results in the field of Bayesian Optimization and Robotics.
  • Conducted laboratory tutorials in Data Science and Statistical Machine Learning.

Software & Operations

Oct 2016 – Present

Group RIGAL

  • Built an internal energy-consumption calculator using React and TypeScript.
  • Digitized accounting workflows and managed relational data using SQL databases.
  • Led the redesign of the corporate brand identity and UI assets using Figma.

Selected Work

A selection of my recent full-stack and design engineering projects.

TestimonialCMS

Modular CMS built under a monorepo structure. Features media ingestion pipelines (Cloudinary, YouTube API), granular RBAC, and a RESTful API for testimonial syndication.

Next.js TypeScript Figma

DataSense-AI

AI-driven analytics platform using Gemini API. Features a CSV ingestion pipeline, output guardrails to mitigate hallucinations, and a containerized full-stack architecture.

Python FastAPI React Docker

Care Tracking Platform

Healthcare tracking platform designed to monitor patient progress and medical staff workflows. Built with a robust React and TypeScript frontend, integrated with Supabase.

React TypeScript Supabase

Galaxy MFE

Microfrontend architecture encapsulating Host and Remote apps via Webpack Module Federation in Docker, ensuring system resilience with lazy loading and fallbacks.

React Webpack Microfrontends

Beautipol E-commerce

Full-stack web application designed with a strong focus on UI/UX. Implemented responsive interactive interfaces and integrated robust backend services for a seamless user experience.

Next.js TypeScript Tailwind

Pet Health Tracker

A comprehensive dashboard platform for monitoring pet health metrics, veterinary appointments, and medical history. Built with a scalable architecture and secure data persistence.

React Node.js PostgreSQL
View UI/UX Portfolio on Behance See more projects on GitHub

Education & Research

Degrees

PhD in Computer Science

2019 – 2023

University of Sydney (Sydney, Australia)

Thesis: A Sequential Optimisation Framework for Adaptive Model Predictive Control in Robotics (2023)

MSc in Computer Science

2014 – 2016

Universidad Nacional de San Agustín (Arequipa, Peru)

Specialization in Information Technologies.

Thesis: Semi-supervised Binary Classification Model using Linear Discriminant Analysis (2016)

Professional Degree in Systems Engineering

2013 – 2015

Universidad Nacional de San Agustín (Arequipa, Peru)

Thesis: Digital Image Enhancement to Classify Green Coffee Bean Defects (2015)

BSc in Systems Engineering

2008 – 2013

Universidad Nacional de San Agustín (Top quintile)

Selected Publications

  • Adaptive model predictive control by learning classifiers.

    Guzman, R., Oliveira, R., & Ramos, F. — L4DC (2022)

  • Bayesian optimisation for robust model predictive control under model parameter uncertainty.

    Guzman, R., Oliveira, R., & Ramos, F. — ICRA (2022)

  • Heteroscedastic Bayesian optimisation for stochastic model predictive control.

    Guzman, R., Oliveira, R., & Ramos, F. — IEEE RA-L (2021)

  • Predicting reactions to blog headlines.

    Guzman, R., Ochoa, E., Cruz, L., & Vera, E. — SIMBig (2016)