
AI Engineer | Vision AI | Deep Learning
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swatah.ai
AI Engineer
June 15, 2026 – Present
NNRT
May 1, 2026 – Present
NNRT is a lightweight deep learning framework built from scratch in Python. It is designed to replicate core concepts of modern frameworks like PyTorch.
View Projectworkout-vision
April 15, 2026 – Present
Real time workout tracking system using computer vision that detects multiple exercises, counts reps, analyzes posture, and provides live visual feedback optimized for edge devices.
View Projectdepth-estimation-encoder-decoder
April 14, 2026 – Present
This project presents a custom Convolutional Neural Network (CNN) designed for monocular depth estimation using an encoder–decoder architecture. The model learns to predict depth maps from single RGB images, capturing spatial structure and scene geometry.
View Projectobject-detection
April 8, 2026 – Present
This repository demonstrates object detection using multiple deep learning models. Each model is trained and evaluated on the same dataset to compare accuracy, speed, and real-world performance.
View Projecthair-color-try-on
February 1, 2025 – February 11, 2025
Virtual Hair Colour Try-On System for Hair Makeovers is a deep learning-based application that allows users to experiment with different hair colours on their photos.
View Projectobject-detection-app
January 25, 2025 – February 1, 2025
Android-based Object Detection System for Visually Impaired using Flutter and YOLOv5
View ProjectEventVerse
August 10, 2023 – September 11, 2023
an event management platform helping organizers to organize events and find speakers
View ProjectCultural Fit Analysis
The candidate demonstrates a strong interest in AI/ML through numerous personal projects, indicating a passion for the field. The diversity of projects (computer vision, object detection, depth estimation, framework development) suggests a broad curiosity and willingness to explore different areas within AI. The current role as an AI Engineer aligns well with the target role, suggesting a good cultural fit for an AI-focused team.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a proactive approach to learning and application development.