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MohammedAfthab18/README.md

👨‍💻 The Engineering Vault

I am a Software Engineer with 2 years of production experience at Webtrendz Technologies, specializing in cross-platform mobile architecture (Flutter) and highly scalable frontend ecosystems (React/TypeScript).

  • 🏗️ Currently engineering end-to-end multi-platform applications.
  • 🎓 B.Tech Computer Science & Engineering from SRM Institute (9.38 CGPA).
  • ⚡ Core Philosophy: Pixel-Perfect Rigor • Architecture First (BLoC/SOLID) • Offline Resiliency.
 Afthab's GitHub Stats

🛠️ The Arsenal


🚀 Featured Architecture

I focus on building resilient systems that handle complex state, offline synchronization, and massive scale.

🎓 Thiruvel Academy

Tech Stack: React TypeScript Laravel Firebase
Multi-tenant educational dashboard engineered with Clean Architecture. Implemented Zod validation and passwordless authentication for zero-friction exam taking.

💰 WT Books

Tech Stack: Flutter Node.js Hive DB Firestore
Strict offline-first financial ledger. Architected advanced background delta-syncing algorithms to seamlessly resolve Firestore data conflicts upon network restoration.

🛥️ Docklyne

Tech Stack: Flutter Firebase
Scaled a massive cross-platform marketplace for 72,000+ boats, handling dynamic pricing algorithms and fleet management with zero UI latency.


📜 Publications & Certifications

🧠 Publications

EEG Based Emotion Classification using Deep Learning Models
International Journal of Innovative Science and Research Technology (IJISRT) • Nov 2023

Benchmarked DNN, GRU, and LSTM architectures for EEG-based emotion classification with comparative confusion-matrix evaluation.
🔗 Read Paper

🏆 Global Certifications

  • Stanford University (Coursera)
    Supervised Machine Learning: Regression and Classification [ 100% ]
  • DeepLearning.AI
    Advanced Learning Algorithms [ 100% ]
  • DeepLearning.AI
    Unsupervised Learning, Recommenders, Reinforcement Learning [ 100% ]

🐍 Activity Graph

github contribution grid snake animation

"Design meets engineering."
Available for impact.

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  1. EEG-Driven-Emotion-Detection-and-Classification EEG-Driven-Emotion-Detection-and-Classification Public

    A project that uses EEG data to classify human emotions using machine learning techniques.

    Jupyter Notebook 21 1

  2. Image-segmentation-using-detectron2 Image-segmentation-using-detectron2 Public

    This computer vision project empowers you to excel in the fields of object detection and precise instance segmentation, offering a versatile toolkit for image analysis and understanding.

    Jupyter Notebook 7