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Philipst77/README.md

Hi, I'm Philip πŸ‘‹

Im a Software Engineer passionate about Machine Learning, Artificial Intelligence, Algorithms, and Backend Development. I love working on challenging problems especially anything related to optimization, autonomous systems, and data-driven intelligence.


πŸ”­ Current Focus

  • Advanced Machine Learning and AI Systems
  • Algorithm Design, and Competitive, Programming (LeetCode enthusiast πŸš€)
  • Database Systems and Data Modeling
  • Building end-to-end AI powered applications

πŸš€ Technical Skills

  • Programming Languages: Python, Java, C, SQL, JavaScript, Typscript
  • AI/ML Frameworks: TensorFlow, Scikit Learn, OpenCV, Hugging Face Transformers
  • Databases:
    • SQL (MySQL, PostgreSQL)
    • NoSQL (MongoDB, Firebase)
    • Relational Algebra, 2NF/3NF Normalization, Schema Design
  • Web/App Development: Streamlit, Flask, Node.js (basics)
  • Tools: Git, GitHub, Docker, VSCode, Linux/WSL

πŸ“š Currently Learning

  • Deep Learning Architectures (CNNs, RNNs, Transformers)
  • System Design for scalable AI applications
  • Advanced SQL optimization - and indexing strategies
  • Reinforcement Learning basics

πŸ› οΈ Featured Projects

  • Spatial-Semantic Mamba (SS-Mamba)
    Developed a novel Mamba-based framework for whole-slide image (WSI) analysis that preserves 2D spatial structure and semantic relationships. Introduced 2D State Space Models (2D-SSM) with semantic patch ordering to address limitations of traditional MIL approaches.
    Results: Achieved state-of-the-art performance on Camelyon16 (95.1% AUC), TCGA-BRCA (89.1% AUC), and BRACS (85.8% AUC).
    πŸ“„ Graduate-level research project (unpublished manuscript / preprint)

  • Facial Recognition Project
    Built a real time facial recognition - system using OpenCV and Deep Learning. Implemented face detection and recognition pipelines with efficient matching algorithms.

  • Linear Regression Project
    Designed and trained a linear regression model from scratch to-predict trends based on real-world data. Focused on gradient descent optimization and loss minimization.

  • Neural Network Project
    Built a custom neural network model-without using high-level frameworks. Implemented forward pass backpropagation, and trained on classification datasets, Including Cosine Similarity checking and Euclidean Distance.

  • SQL Database Manager
    CLI tool built with Java and JDBC for library database management complete CRUD functionality, SQL queries and database normalization up to 3NF.

  • AutoSeedBot
    Autonomous ecofriendly robot designed for reforestation. Implemented sunlight detection for navigation and automated seed distribution using custom-coded 3D-printed hardware.


πŸ“ˆ GitHub Stats

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πŸ“« Let's Connect!


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  1. AI-ML-Projects-Showcase AI-ML-Projects-Showcase Public

    A comprehensive showcase of machine learning and data mining projects β€” featuring algorithms, applied AI models, and deep learning implementations. Includes real-time facial recognition (OpenCV + D…

    Jupyter Notebook

  2. spatial-semantic-mamba spatial-semantic-mamba Public

    Research paper and implementation for Spatial-Semantic Mamba (SS-Mamba): preserving spatial and semantic structure in whole-slide image analysis.

    Python

  3. Quantum_Computing Quantum_Computing Public

    A modular quantum computing simulator in C++17 with support for statevector simulation, quantum gates, and example algorithms (Grover, QFT, teleportation).

    1

  4. Computational-Finance-Quantitative-Modeling Computational-Finance-Quantitative-Modeling Public

    HTML