// AI & Robotics Research
Explore my collection of AI and robotics projects, ranging from autonomous robot manipulation to deep learning implementations and interactive algorithm visualizations. Each project represents a step forward in my journey to understand and develop intelligent systems.
Developed an autonomous robot system using ROS and Python for precise pick-and-place operations. Enhanced navigation accuracy in dynamic environments through implementation of particle filter algorithms for localization and mapping. This project was part of the DD2410 Introduction to Robotics course at KTH.
Comprehensive exploration of deep learning architectures and optimization algorithms. Implemented neural networks from scratch and applied them to real-world data science problems. Covered advanced topics including CNNs, RNNs, and attention mechanisms for various applications.
Interactive demonstrations of fundamental AI algorithms through engaging games. Features A* pathfinding, Minimax with alpha-beta pruning for 2048 AI, cellular automata for Conway's Game of Life, and backtracking algorithms for Sudoku solving with real-time visualizations.
Real-time visualization tool comparing different pathfinding algorithms including A*, Dijkstra, BFS, and DFS. Interactive grid allows users to create custom mazes and obstacles while observing algorithm behavior and performance metrics in real-time.
Implementation of core machine learning algorithms from scratch including SVM, Bayesian learning, decision trees, and ensemble methods. Focus on understanding the mathematical foundations and practical applications in classification and regression problems.
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