Skip to content
meettilavat.com

Meet Tilavat

Software engineer building dependable web products and systems.

I enjoy working end-to-end—from feature development to shipping and operations—with a focus on clarity, reliability, and automation.

Based in Gujarat, IndiaOpen to full-time roles
tilavatmeet2@gmail.com+91 99133 20031linkedin.com/in/meettilavatgithub.com/meettilavat

Experience

May – Jul 2023

Web Dev Trainee

Yellow Apple Solutions · Surat, India

  • Built responsive web interfaces with HTML5, CSS3, and JavaScript.
  • Collaborated with designers to ship user-friendly UI and tuned based on feedback.
  • Helped triage and resolve UX issues across breakpoints.

Education

2021 – 2024

Pandit Deendayal Energy University (PDEU)

B.Tech, Computer Engineering — CGPA 8.92

Gandhinagar, Gujarat, India

2018 – 2021

Marwadi University

Diploma, Computer Engineering — CGPA 9.00

Rajkot, Gujarat, India

Projects

MeetTilavat.com (Blog Platform)

Next.js, Tailwind CSS, Supabase, Tiptap, Docker, Jenkins

GitHub
  • Split public read-only site and a private admin editor for publishing posts.
  • Rich-text editor with images, tables, and Supabase Storage uploads.
  • Containerized builds with CI/CD automation for repeatable deploys.

Personal Blog (PHP/MySQL)

HTML, CSS, PHP, SQL, JavaScript, AWS

  • Full-stack blog with admin panel, CKEditor formatting, and MySQL persistence.
  • Deployed on AWS, handling server setup and asset uploads.

CPU Scheduling Simulator

HTML, CSS, JavaScript

  • Visualized multiple scheduling algorithms with interactive Gantt views.
  • Explainer pages plus JS-driven simulations.

Image Caption Generator

ResNet50, LSTM, Python, Streamlit, AWS/Azure

  • Trained on Flickr8k using ResNet50 feature extraction + LSTM decoding.
  • Deployed with Streamlit; experimented across AWS and Azure.

Diabetic Retinopathy Classification

CNN ensemble

  • Preprocessed fundus images (CLAHE, histogram EQ) and tested segmentation approaches.
  • Ensembled ResNet, VGG, Inception, and Xception for DR staging.

Predicting Engineering Student Performance

  • Modeled academic outcomes with RF, GBM, Logistic Regression, and CNN.
  • Used SHAP/LIME for explainability on a 12k+ student dataset.

Skills

Languages & Frameworks

JavaPythonC/C++JavaScriptPHPSQLHTML/CSSReactAngularNode.js

DevOps & Cloud

DockerKubernetesJenkinsAWSLinuxvast.aiGoogle Colab

Tools

GitGitHubVS CodeJetBrains IDEs

Languages (Spoken)

English (IELTS 8.0)GujaratiHindi

Other

Custom PC buildingHardware troubleshooting