- Created a custom dataset of 2,000+ labeled ASL hand signs using OpenCV and MediaPipe, captured via webcam and stored with Pandas for model training and analysis.

- Trained a neural network model using TensorFlow and Scikit-learn to classify ASL letters from live video, reaching 90%+ accuracy across multiple sessions and lighting conditions.

- Implemented a real-time recognition pipeline with multithreading to manage live video, prediction, and text-to-speech playback concurrently.

- Built an interactive interface that lets users adjust prediction thresholds, toggle feedback modes, and audibly relay accumulated signs using TTS libraries.

- Designed the system with extensibility in mind, enabling future support for additional gestures, dynamic phrase construction, or camera hardware input.

- Visit the website here!

- Built an interactive educational tool in Elm to visualize 23 algorithms including sorting, searching, tree traversals, graph search, and heap operations.

- Platform is actively used by UT-Arlington faculty in CS instruction, both in live lecture demos and self-paced study material.

- Followed functional programming principles (immutability, pure functions, modularity) to create a maintainable and testable codebase.

- Designed the UI for clarity and accessibility, with controls to pause, reset, and inspect each stage of algorithm execution.

- Used SVG rendering and custom animations to present each algorithm step-by-step.

- Built entirely with HTML, CSS, Elm, and SVG—no JavaScript—demonstrating Elm's power in pure functional web development.

- Visit the website here!

- Designed and implemented a web-based puzzle game where players must place queens on a colored, region-based board so that no two queens attack one other

- Created a unique board generation algorithm with a flood-fill technique, ensuring exactly one solution per puzzle

- Developed an interactive SVG-based UI using JavaScript to support queen placement, note-taking, save states, difficulty leveling, and more

- Built with FastAPI and Pydantic to serve dynamic puzzle data and validate all user inputs, leading to robust and secure API handling

- Utilized Postman to test and document API functionality; implemented rate limiting to protect endpoints from abuse and ensure consistent performance under load

- Fully containerized for deployment with a self-contained Docker setup that runs both the front-end and back-end locally or remotely

- Built a detailed walkthrough for creating a feedforward neural network from scratch using only Python and NumPy, with no external ML libraries.

- Trained the network on the MNIST handwritten digits dataset, achieving 95%+ classification accuracy through careful tuning and optimization.

- Explained core concepts like forward propagation, backpropagation, gradient descent, loss minimization, and activation functions in an accessible, code-first format.

- Included visualizations with Matplotlib to illustrate learning progress, including weight evolution, loss curves, and accuracy over epochs.

- Designed as a beginner-friendly resource to demystify neural networks and help others understand and implement them without high-level frameworks.

- Developed a security-focused REST API to manage a phonebook database, featuring rigorous input validation for names and international phone numbers using regular expressions

- Built with FastAPI, SQLite, and SQLAlchemy, utilizing parameterized queries to protect against SQL injection attacks

- Implemented JWT-based authentication and role-based authorization (read vs. read/write) with token expiration control

- Created a persistent audit log system that timestamps and tracks every user action in rolling `.csv` files for scalability and compliance

- Deployed in a self-contained Docker container with mounted volumes for data and logs; fully testable via an automated Postman collection

- GitHub repository kept private to maintain the integrity of the class project

- Built a compiler for the SPL (Simple Programming Language) using Scala, CUP (parser generator), and JFlex (lexer)

- Implemented a full pipeline: lexical analysis, recursive-descent parsing, type checking, and intermediate code generation

- Developed robust input validation rules from a formal grammar and integrated detailed error diagnostics

- Included a full symbol table with scope tracking and function call semantics for nested procedures and recursion

- Generated IR code (intermediate representation) with frame pointer management, memory allocation, static links, and control flow translation

- GitHub repository kept private to maintain the integrity of the class project

- Managed Java WebSocket connections and JSON strings to facilitate real-time, 2-4 player word search games

- Authored comprehensive JUnit test suties to automate verification of game logic via JUnit and Github Actions

- Mapped out detailed project requirements using Excel and designed system architecture with UML diagrams

- Developed responsive front-end interfaces in HTML & CSS, seamlessly integrated with a WebSocket-powered back end

- Utilized Maven for project management, developed the codebase using VS Code, and deployed the game on an online server

- Achieved a 61% reduction in storage by reducing the origianl 10,304-dimensional image vectors to 150 principal components

- Implemented PCA by computing the covariance matrix of the dataset, followed by eigenvalue decomposition to identify the top principal components

- Reconstructed facial images retained 98% visual similarity to the original data despite compression, as measured by the Structural Similarity Index (SSIM)

- Designed visualizations for the mean face, top eigenfaces, and reconstructed images, effectively communicating the primary steps in PCA

- Built a multipurpose Discord bot tailored for ACM @ UT Arlington (1400+ member server) using OpenAI's GPT-4.1 and the Discord API

- Offers real-time Q&A, AI image generation, and campus-specific academic resource navigation

- Integrates slash-commands (/resources, /ask, /draw, etc.) with persistent context support to streamline user interactions

- Deployed via Heroku using worker dynos and a GitHub-powered CI/CD pipeline; managed all secrets through encrypted config vars

- Added security by restricting bot responses to authorized servers only and blocking all direct-message interactions to prevent unauthorized usage

- Designed a user-friendly to-do list application with a built-in calendar view for task organization and scheduling

- Developed a FastAPI backend for managing tasks with a MongoDB database, supporting CRUD operations

- Integrated dynamic calendar rendering with automatic month navigation and date-specific task filtering

- Containerized the entire application using Docker for seamless deployment across multiple environments

- Engineered custom malloc and free implementations using four different allocation algorithms

- Integrated advanced memory management techniques, including splitting and coalescing blocks, to efficiently handle variable-sized memory requests and minimize fragmentation

- Benchmarked allocation algorithms, comparing performance against the standard system malloc to evaluate efficiency and charted results

- Employed debugging tools like GDB to troubleshoot memory leaks and ensure stability during extensive use cases

- Developed a file compression tool using Huffman coding, achieving efficient, lossless reduction in file sizes

- Programmed an XOR-based encryption system with user-defined keys for securing files

- Assembled algorithms and data structures, including min heaps, binary trees, and dynamic arrays

- Automated file naming with suffixes for clarity and ease of use

- Ensured robust memory management to maintain program stability and prevent memory leaks

- Created an interactive family tree visualization with a scalable and pannable canvas, intuitively allowing users to explore large family trees

- Integrated an SQLite database for efficient data storage, ensuring seamless retrieval and persistence of family member details and their relationships

- Designed a comprehensive graphical user interface (GUI) using Tkinter to manage and visualize familial relationships

- Leveraged data structures like dictionaries and lists to efficiently manage the hierarchy of family members and their interconnections

- Deployed a custom Ubuntu shell, enabling command-line interface operations, including command execution and redirection

- Designed a built-in command interpreter to handle essential shell commands such as `cd` and `exit`, improving usability and system control

- Utilized low-level system calls like `fork()`, `exec()`, and `wait()` to create a functional, multi-process environment within the shell

- Created a multi-page website using HTML, CSS to showcase my professional experience and projects

- Designed a dynamic landing page featuring highlights and easy navigation

- Created experience and portfolio pages showcasing my work/volunteer experience and programming projects, respectively

- Curated a gallery page displaying photographs I have personally taken, enhanced with consistent formatting regardless of photo size

- Built an interactive educational tool to demonstrate monoalphabetic and transposition ciphersb using Java's AWT and Swing libraries

- Implemented a dynamic, user-friendly GUI that allows users to input text and visualize how different ciphers encrypt and decrypt messages in real-time

- IIncorporated data structures such as HashMap, ArrayList, and matrices to efficiently map cipher keys, manage dynamic text data, and perform complex transposition ciphers

- Included detailed explanations and step-by-step visuals within the interface to enhance user understanding of encryption concepts