Mohammed HuzaifahMohammed Huzaifah

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About Me

I'm Mohammed Huzaifah, a Computer Science student and ML Engineer who believes AI should solve real problems, not just look cool on paper. I love turning complex problems into elegant solutions - whether that's building AI platforms or contributing to open-source projects. My hands-on experience ranges from deep learning to MLOps, and I'm always excited to learn new tools and technologies...

Why work with me? I bring a unique blend of technical skills and practical thinking. I don't just build models; I build solutions that matter. My projects in healthcare and my active involvement in hackathons show I can deliver under pressure while keeping the end-user in mind. Currently looking for opportunities to create impact through AI - let's build something meaningful together!

Education

Bachelor of Engineering in Computer Science

Specialization: AI and Machine Learning

CGPA: 8.6

Interests

Latest advancements in AI & Generative Models

MLOps & GenAI Technologies

Football enthusiast and Real Madrid supporter

Hackathons & Collaborative Projects

Open source development & contributions

Technical Expertise

Core AI & Machine Learning

Large Language Models: Fine-tuning, RAG systems
Neural Networks: Transformers, CNNs, RNNs
Computer Vision: Object detection, segmentation
NLP: Text classification, sentiment analysis

Generative AI & Emerging Tech

Multi-modal Models: Text-to-image, voice synthesis
AI Agents: Tool-using AI, autonomous systems
Foundation Models: GPT, Claude, open-source
Vector DBs: Semantic search, embeddings

MLOps & Infrastructure

Deployment: Docker, Kubernetes, CI/CD
Model Serving: Real-time inference, monitoring
Cloud Platforms: AWS, Azure ML services
Version Control: Git, DVC for ML

Development & Data Engineering

Languages: Python, C++, Java, JavaScript
ML Frameworks: TensorFlow, PyTorch, Scikit-learn
Data Processing: Pandas, NumPy, Spark
Visualization: Matplotlib, Seaborn, Plotly

Featured Projects

Graph-RAG

A Graph RAG (Retrieval-Augmented Generation) application combining Large Language Models (LLMs) with knowledge graphs to enhance the accuracy and explainability of Retrieval-Augmented Generation.

OpenAIWeaviateDatabricksRDFLibPandas

Crawler - RAG Agent

An intelligent documentation crawler and RAG agent that transforms documentation websites into an interactive knowledge base. Built with Pydantic AI and Supabase, this system crawls documentation, indexes it in a vector database, and provides AI-powered answers to user queries using contextually relevant documentation chunks.

Crawl4AIOpenAISupabaseFastAPIPydantic

Vocal-Diagnose

VocalDiagnose uses AI to analyze voice patterns, enabling early disease detection with over 90% accuracy, revolutionizing accessible and cost-effective health screening.

GroqTensorFlowLibrosaKaggleMatplotlibRandomForest

KidsCare-Pro

AI-powered pediatric health solution for monitoring and predicting children's health conditions using advanced machine learning algorithms.

GroqTensorFlowAWSMatplotlib/SeabornLightGBM

Disease Diagnosis

High-accuracy disease prediction platform utilizing deep learning and computer vision for early detection and diagnosis.

PyTorchKnnTensorFlowMatplotlib/SeabornStreamlit

DocHub-AI

A RAG-based multi-agent AI platform revolutionizing access to government services with intelligent document assistance, scheme navigation, and seamless application support.

PythonLLamaTensorFlowFlaskBeautifulSoupAPI

Achievement Metrics

Tracking progress through numbers

LeetCode Problems

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GitHub Repos

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Hackathons

6

+2 this month

Projects

32

+8 this month

GitHub Contributions

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Repositories

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Followers

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Contributions

Hackathon Achievements

6

Attended

1

Won

2

Upcoming

Project Statistics

32

Total

8

Deployed

6

Featured