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

Email Me GitHub

Experience

Hands-on product delivery and cross-functional execution.

May – Jul 2023

Web Dev Trainee

Yellow Apple Solutions · Surat, India

Built responsive product interfaces in HTML, CSS, and JavaScript that held up across desktop and mobile breakpoints.
Partnered with designers to translate mockups into production-ready UI and iterated quickly from feedback.
Triaged and fixed UX regressions in layouts and interactions to improve overall polish and consistency.

Education

Core academics with strong engineering outcomes.

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

Selected Projects

Production work and applied ML builds across web, infra, and experimentation.

MeetTilavat.com (Blog Platform)

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

Source

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

Current stack and tools used in day-to-day delivery.

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