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.

Shravansay hello

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Smart Nutrition Companion & Barcode Scanner

NutriNova

Mobile AI, Computer Vision & Recommendation Engine

Overview & Purpose

NutriNova is a smart nutrition companion that simplifies nutrition for everyone: scan any packaged food to analyze its nutritional content, discover healthy alternatives for less nutritious options, and receive personalized food recommendations based on health goals.

Demo Video (YouTube)↗Download App (Expo)↓

System Implementation

Simplifying Nutrition for Everyday Living

NutriNova was born out of a simple realization — most people struggle to understand what's in the food they eat and how to make healthier daily choices. Whether decoding complex food labels or finding practical alternatives, NutriNova integrates camera OCR barcode scanning, a custom recommendation engine, and clean UI/UX to make nutrition simple, actionable, and accessible.

Metrics & Architecture

Production Results

Scan & Decode

Instant OCR barcode and nutritional label analysis

SCAN ANY PACKAGED FOOD ITEM TO ANALYZE INGREDIENTS AND DISCOVER HEALTHY ALTERNATIVES FOR PROCESSED OPTIONS IN SECONDS.

ML Advisor

Custom recommendation engine for dietary goals

ADAPTIVE RECOMMENDATIONS MAPPING HEALTHY, ACCESSIBLE FOOD ALTERNATIVES TAILORED TO USER PREFERENCES AND GOALS.

Technical Architecture

Mobile Scanner & Recommendation Architecture

Built with React Native and Expo, integrating computer vision OCR barcode scanning, large-scale food nutrition datasets, and custom ML recommendation algorithms.

Key Technologies

Image & Barcode Scanning (OCR / Barcode Tech)
Custom Machine Learning Recommendation Engine
React Native & Expo Cross-Platform Mobile
Nutrition Data Standards & Food Labeling APIs

Mobile Top View

Interactive Features

Developer Focus

Engineering Challenges & Innovations

Overcoming packaging diversity, structuring large-scale food composition datasets, and mapping practical alternatives that balance nutritional science with daily user habits.

Architecture Patterns

Accurate optical scanning across diverse packaging types
Large-scale food & nutrition dataset structuring
Practical, healthy food alternative scoring algorithms
Seamless feedback loops and accessible user experience