This project is a visual tool created to help students understand how different sorting algorithms work by showing the step-by-step process in an interactive format. It animates popular methods like Bubble Sort, Merge Sort and Quick Sort, making it easier to see how data is organized and sorted. The tool is especially useful for students in courses like Analysis of Algorithms, where visual aids can enhance understanding. By making abstract concepts more tangible, it supports classroom learning and helps students grasp the logic behind sorting techniques more effectively. 

Checkout the demo here

Sourcecode at Github

BrainVisualizer is a 3D model of brain anatomy. When the user mouseovers, description of various parts of the brain are illustrated.

The tool was built to support deeper understanding of concepts for students.

Checkout the demo here

Sourcecode at Github

Interactive tool where users can control a robotic arm by adjusting its joint angles and see how those changes affect the arm’s position. It shows how each part of the arm connects using homogeneous transformations, helping users understand how the final position of the arm’s tip (the end effector) is calculated. Users can also move a 3D target point in space and watch how the robotic arm automatically adjusts its joints using inverse kinematics to reach that point 

Checkout the demo here

Sourcecode at Github

Interactive simulation environment designed to help users build, test, and visualize path planning algorithms using a simulated robot, such as the PR2. This tool provides a hands-on platform for understanding how motion planning algorithms operate in dynamic or constrained environments. Users can create custom test scenarios, observe algorithm behavior in real time, and gain insights into the strengths and limitations of different planning strategies.

This tool is ideal for a range of users—from students learning robotics concepts to researchers benchmarking algorithms, and developers prototyping autonomous navigation systems. It supports use cases such as curriculum development, algorithm debugging, and human-robot interaction studies by providing a safe, flexible, and visually rich environment to test and refine motion planning strategies

Visual tool built from scratch that shows how machine learning models learn and improve over time, without using any pre-made software libraries. It compares different learning strategies, such as AdaGrad and ADAM, by showing how they move through a landscape of errors to find the best solution. 

It is useful for students, even without technical background, who want to understand how machine learning training works in a clear and visual way. The tool helps make complex concepts easier to grasp, supports learning and experimentation, and shows why certain algorithms are better suited for specific tasks

Electromagnetic field visualizer which allows you to interact and manipulate 3D spinning charge particles and visualize the corresponding effects on electric and magnetic fields. 

It helped students to gain a good intuition on how electromagnetic fields look like and conform to maxwell equation which is otherwise challenging to understand in 2D

Visualization tool to help students with better grasp of computer engineering fundamentals 

Tool designed to detect plagiarism by analyzing the meaning behind written content, rather than just checking for exact word matches. Built entirely from scratch, it uses mathematical techniques to understand and compare the ideas expressed in different texts, such as articles from Wikipedia. 

It is especially useful for educators, students, or reviewers who want to identify copied content that may have been reworded. By focusing on the underlying meaning, the tool offers a smarter and more reliable way to uncover plagiarism