Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ whoami
Kenneth Loto – Full-Stack Developer
Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ ls -ap
./../about-me.txtconnect.json.envexperience.logfeatured-projects/
Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ cat about-me.txt
- name:
- Kenneth Loto
- role:
- Full-Stack Developer
- location:
- Leyte, Philippines
- bio:
- Building web apps and backend APIs with Next.js, NestJS, and TypeScript. Open to remote junior and entry-level roles worldwide.
Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ cat .env
LANGUAGES = TypeScript, JavaScript, PHP, Python, Dart
FRAMEWORKS = Next.js, NestJS, React, Laravel, Flutter
STYLING = TailwindCSS, Bootstrap, CSS, shadcn/ui
DATABASES = PostgreSQL, MySQL
ORM = Prisma, Drizzle
MACHINE_LEARNING = TensorFlow, TFLite
LIBRARIES = Recharts, MapLibre, Leaflet, Turf
DEPLOYMENT = Vercel, Docker, Render
TOOLS = Git, Zed
Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ cat experience.log
Full-Stack Developer
Independent ProjectsSep 2025 — Present
– Building production-grade web apps and APIs with Next.js, NestJS, TypeScript, and PostgreSQL, from database design to deployment.IT Intern
CViSNet Foundation Inc.Jan 2025 — Mar 2025
– Collaborated in a 4-person team to build a full-stack Event Management System in Laravel, implementing role-based access control.Mobile App & ML Developer
Undergraduate ThesisJune 2024 — Aug 2024
– Fine-tuned a MobileNetV2 model (92% accuracy) with TensorFlow/Keras and integrated it into a Flutter app for offline, on-device inference.Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ ls -ap featured-projects
./../dog-stool-classifier.mdsolar-shading-estimator-api.md
Kenneth@LAPTOP-F4NAR8GJ MINGW64 /c/Next.js/portfolio-lite (main)
$ cat dog-stool-classifier.md solar-shading-estimator-api.md
Solar Shading Estimator API
– A backend API that estimates realistic solar panel output by combining NASA POWER irradiance data with PVWatts baseline estimates and a shading model for nearby obstructions.
tags: nestjs, typescript, rest-api
Dog Stool Classifier
– A Flutter Android app using an on-device deep learning model to classify dog stool images into 5 health categories, with instant remedy suggestions, no internet required.
tags: flutter, tensorflow, machine learning