Who is Shravan Gupta?

Shravan Gupta is an AI & Machine Learning Engineer based in Mumbai, Maharashtra, India. He specializes in Generative AI, Large Language Models (LLMs), Autonomous Multi-Agent Networks, and Full-Stack Web Architecture.

What are Shravan Gupta's core technical skills and expertise?

Shravan Gupta's technical expertise spans Generative AI, Large Language Models, Autonomous Agents, LangGraph, Model Context Protocol (MCP), RAG Pipelines, Vector Databases, Computer Vision, Python, PyTorch, FastAPI, Next.js, React 19, and TypeScript.

What research papers has Shravan Gupta authored?

Shravan Gupta authored and presented two peer-reviewed academic papers: 'Toward a Sustainable Future for Generative AI Technologies' (researching data center telemetry and sustainable foundation model computing) and 'AI-Based Intelligent Examination Invigilation Using Face Recognition and Behaviour Analysis from CCTV Surveillance' (addressing computer vision and multi-object tracking).

What notable engineering projects has Shravan Gupta developed?

Key production platforms built by Shravan Gupta include ML Doctor (mldoct, an enterprise PyTorch AST linter, C++ GPU VRAM watchdog, and ML loss diagnostics package on PyPI), BrandStudio (an autonomous multimodal AI social publishing bus), Outskill (an autonomous AI curriculum synthesis engine), and Yellow Crest (an industrial PMC platform with 60fps web telemetry and hardened security).

Where is Shravan Gupta's official portfolio hosted?

Shravan Gupta's official engineering portfolio and research showcase is located at https://shravangupta.dev.

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Plant Care & Disease Detection

GreenThumb AI

Computer Vision & Botanical Disease AI

Overview & Purpose

Plant identification and mobile vision leaf disease detection engine providing immediate diagnostic care plans, botanical treatment guides, and watering reminders.

Source Code↗

System Implementation

Intelligent Botanical Health Diagnostics

GreenThumb AI brings botanical laboratory diagnostics to smartphone cameras. By analyzing leaf discoloration, spotting, and stem geometry, the application identifies blight, rust, and pest infestations within seconds.

Metrics & Architecture

Production Results

Plant Vision

Mobile leaf disease detection and species ID

CLASSIFIES 1,000+ BOTANICAL SPECIES AND LEAF PATHOGENS WITH CONFIDENCE SCORING AND TREATMENT ADVICE.

AI Advisory

Botanic disease treatment & care schedules

CUSTOMIZED SOIL, SUNLIGHT, AND HUMIDITY RECOMMENDATIONS TAILORED TO INDOOR AND GARDEN FLORA.

Technical Architecture

Mobile Disease Classifier

Lightweight convolutional neural network optimized for on-device mobile inference with low battery consumption.

Key Technologies

TensorFlow Lite / PyTorch Mobile Model
React Native Cross-Platform UI
Tailwind CSS Responsive Styling
FastAPI Cloud Sync Backend

Mobile Top View

Interactive Features

Developer Focus

On-Device Neural Vision

Local caching of common regional plant diseases allowing offline diagnosis in remote greenhouses and farmland.

Architecture Patterns

Edge model inference with fallback
Visual bounding box disease highlights
Offline care schedule persistence
Sensor-informed watering reminders