/ArshidAli84

Config files for my GitHub profile.

Interested to Work in the Field of Machine Learning, Power Systems and Research


  • 🔭 I’m currently working on 30-Ready-ML-Projects, a comprehensive repository showcasing practical machine learning applications across diverse domains, including smart grid and energy management.

  • 👯 My main research focus is on ML|DL|RL projects related to power and energy systems by learning Smart circuit breakers to avoid power system blackouts during natural disasters.

  • 🌱 I’m diving deep into Reinforcement Learning, exploring its applications in optimizing energy distribution within smart grids, ensuring efficiency and sustainability.

  • 👨‍💻 My projects span various applications in Machine Learning, Smart Grids, and Energy Management. Find them at My GitHub Profile.

  • 💬 Curious about Machine Learning, Smart Grids, and Energy Management? I'm passionate about discussing innovations and challenges in these fields.

  • 📫 Reach out to me at arshidali.yaho@gmail.com for collaborations, discussions, or inquiries.

Key Areas of Expertise:

Languages and Tools:

Arduino MATLAB MySQL Pandas Photoshop Python PyTorch Scikit-learn Seaborn TensorFlow

Top Languages

GitHub Stats

GitHub Streak

  • I leverage a comprehensive set of machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, NumPy, Pandas, Matplotlib, SciPy, and PyPI to build and deploy predictive models. These models are specifically designed for optimizing smart grid functionalities, energy forecasting, and anomaly detection within power systems.

Relevant Projects and Contributions:

1. Smart Grid Optimization using Reinforcement Learning:

  • Implementation of a Reinforcement Learning model for optimal energy distribution within smart grid networks, resulting in significant enhancements in energy efficiency and cost reduction.

2. Energy Forecasting with Machine Learning:

  • Developed predictive models employing time series analysis and machine learning algorithms to forecast energy consumption patterns, facilitating efficient resource allocation in energy management systems.

3. Anomaly Detection in Power Systems:

  • Created an anomaly detection system utilizing machine learning techniques to identify and mitigate faults or anomalies in power systems, ensuring grid stability and resilience.

Publications and Research Contributions:

  • Co-authored multiple papers published in leading conferences and journals, focusing on the convergence of AI, smart grid technologies, and energy management.

Let's connect and explore the fascinating realm of AI-driven solutions in smart grids and energy management!