Projects

Quantum Computer Simulator

This project was a deep dive into quantum computation, where I developed a fully-functional, GPU-accelerated quantum statevector simulator entirely in Python. The main goal was to simulate quantum algorithms efficiently and support modern quantum programming standards, bridging the gap between theoretical design and practical implementation.

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Deep Q Snake with PyTorch

This project explores the application of Deep Q-Learning to classic game environments. Specifically, I implemented a Deep Q-Network (DQN) using PyTorch to train an AI agent capable of mastering the Snake game, a benchmark environment for reinforcement learning.

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Protein Folding Simulations on a Quantum Computer

This project explores the potential of quantum computing to address the complex problem of protein folding, a fundamental challenge in computational biology. Leveraging the capabilities of Qiskit’s protein folding module, we formulate the task as a combinatorial optimization problem, preserving critical topological constraints and hydrophobic-polar (HP) interactions.

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Quantum image encoding and processing

This project explores the potential of quantum computing for image encoding and processing, with a focus on efficient representations of grayscale, RGB, and thermal images using quantum image representations (QIRs). Quantum-enhanced imaging holds great promise for areas like low-light vision and biomedical analysis, where classical methods often struggle with resolution and noise.

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ASL alphabet learning application

This project focused on building an interactive desktop application to help users learn the American Sign Language (ASL) alphabet through real-time gesture recognition.

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