👋 Hey there! I'm Manimaran K
🎯 Aspiring Machine Learning & Quantum Computing Enthusiast
💻 B.Tech – Computer Science and Business Systems (CSBS) student
📍 Passionate about solving problems, building intelligent systems, and exploring the quantum world of computation.
🚀 About Me
- 🔥 I love coding, learning new technologies, and improving every day through daily commits and LeetCode challenges
- 💡 Currently mastering AI, Machine Learning, and Quantum Computing step by step
- 🧠 I believe in consistency — coding daily, learning constantly, and contributing to open source
- 🌱 Exploring data science, neural networks, blockchain systems, and quantum algorithms
🧪 Featured Projects
🔗 YieldSense — Solana-Based CLMM Infrastructure
📌 Blockchain · DeFi · Systems Engineering
🔗 https://github.com/Manimaran-tech/stable_yeildsense
- Built a Solana-based Concentrated Liquidity Market Maker (CLMM) system
- Implemented liquidity position logic, pool management, and fee calculations
- Focused on on-chain efficiency, security considerations, and scalable design
- Explored AMM math, PDA-based vault structures, and Solana program architecture
Tech: Solana, Rust, DeFi primitives, CLMM design
🛰️ Satellite Orbital Reentry Prediction using PINNs
📌 Machine Learning · Physics-Informed AI
🔗 https://github.com/Manimaran-tech/pinn-orbital-reentry-prediction
- Developed a Physics-Informed Neural Network (PINN) to model satellite orbital decay and reentry
- Embedded physical laws directly into the loss function for better generalization
- Bridges AI + aerospace systems for real-world space applications
Tech: Python, Pytorch, PINNs, Orbital Mechanics
📈 Stock Market Analysis using LSTM (NVDA Case Study)
📌 Deep Learning · Time Series Forecasting
🔗 https://github.com/Manimaran-tech/Stock_Analysis_NVDA
- Built an LSTM-based deep learning model for stock price trend analysis
- Performed data preprocessing, sequence modeling, and evaluation
- Focused on temporal dependencies in financial data
Tech: Python, TensorFlow/Keras, LSTM, Pandas, NumPy
📊 Machine Learning Projects using XGBoost
📌 Supervised Learning · Practical ML Pipelines
🔗 https://github.com/Manimaran-tech?tab=repositories
- Implemented multiple ML pipelines using XGBoost
- Worked on feature engineering, hyperparameter tuning, and model evaluation
- Emphasis on real-world ML workflows over toy problems
Tech: Python, XGBoost, Scikit-learn, Pandas
🧠 Tech Stack
🐍 Languages
⚙️ Tools & Platforms
🧠 Frameworks & Libraries
🎯 Learning Goals (2025–2026)
- Build a production-grade ML-powered Quantum Computing project
- Preparing for MLH Fellowship (2026)
- Contribute to Google Summer of Code (GSoC)
- Publish a research paper in AI + Quantum Computing
- Deepen expertise in Solana infrastructure and distributed systems
📬 Connect with Me
- 💼 LinkedIn: https://www.linkedin.com/in/manimaran-k-4703ab30b/
- 🧩 LeetCode: https://leetcode.com/u/Manimaran-tech/
- 📧 Email: manimaran230806@gmail.com