Sneha Patel — AI & Systems Engineer | Computer Vision, Machine Learning & IoT Developer Portfolio
I've spent the past few years going deep into computer vision, machine learning, and embedded hardware. From building a deepfake detection engine that hits 97.5% accuracy, to wiring up a Raspberry Pi waste sorter that classifies trash in real-time - I like working where code meets the physical world.
expertise
meets
purpose
Computer Vision & Visual Forensics
Custom deep learning pipelines for image classification, target detection, and digital forensics.
Fine-grained image classification models (ResNet, MobileNet, custom CNNs). Explainable AI integration using Grad-CAM attention heatmaps. Digital image forensics (Error Level Analysis ELA, high-frequency DCT GAN analysis). Adversarial protection techniques (FGSM noise mapping).
Machine Learning & Natural Language Processing
Advanced classification, recommendation systems, and semantic text analysis to drive business logic.
Personalized recommendation engines based on user profiles & preferences. Text pattern & behavioral sentiment analytics models. Advanced regression-based automated ranking tools. Graph databases (Neo4j, Cypher) to reveal hidden insights in relational data.
IoT & Hardware Automation
Physical prototypes integrating embedded devices, sensors, and actuators with intelligence at the edge.
Raspberry Pi & Arduino firmware development. Edge ML models optimized for low-resource processors via TensorFlow Lite. Sensor integrations (ultrasonic, PIR, telemetry feeds). Actuator coordination (servos, mechanical switches, relays).
Data Specialist Consultations
End-to-end data pipeline setups for collecting, cleaning, and formatting large datasets for analytical platforms.
Robust web-scraping agents with delay mapping to respect rules. Structured DataFrame processing and cleaning pipelines. API design & deployment using FastAPI, Streamlit, and Flask. Data extraction, enrichment, and verification checks.
GreenSort: Integrated IoT & Deep Learning for Real-Time Municipal Solid Waste Segregation
Written for SustainX 2026 — a multi-sensor IoT pipeline with edge-deployed ResNet achieving 90% mAP, ultrasonic telemetry, and dynamic route optimization for the Vadodara Municipal Corporation.
“We were genuinely impressed by the team's presentation and analytical logic. The supplier ranking agent showcased impressive depth, earning our high commendation and appreciation.”
“Her graph database integration mapped sentiment patterns our standard NLP pipeline couldn't detect. The Neo4j context pathways added a new dimension to our risk assessment.”
“Represented the institution in national-level championship, demonstrating exceptional autonomous robot design with real-time obstacle detection and path optimization.”
Tech Stack
Languages
- Python
- Java
- C
- C++
- JavaScript
- TypeScript
- SQL
- HTML/CSS
Frameworks
- Next.js
- FastAPI
- Flask
- React
- Node.js
- Express
- Tailwind CSS
Tools & Hardware
Let's Engineer
Something Intelligent
Whether you need a deepfake detection pipeline, an edge-AI hardware prototype, or a custom ML model — I bring research-grade precision to every project. Currently open to freelance, internships, and technical collaborations.
Have a project that needs vision, intelligence, or just solid engineering? I'm always up for a good conversation about hard problems. Let's see if we can build something meaningful together.