Facial Recognition Enabled ML Voice Assistant

• Designed and developed an AI-based voice assistant system with customized facial recognition capabilities using Python’s OpenCV library.

• Optimized the model’s performance by fine-tuning it to leverage a concatenation of previous verbal prompts as history, limiting it to a small integer value of 5, thereby achieving fast response times and exceptional conversation quality.

• Designed and developed a minimalist chat interface with simple HTML and JavaScript, utilizing AJAX and jQuery to facilitate efficient front-end and back-end communication.

• Gained valuable expertise in integrating computer vision techniques with NLP and leveraging server-side frameworks such as Flask to build end-to-end logic accessible via asynchronous request methods for a smooth user experience.

Brain-Computer Interface Research

• Conducted research with the Human-Computer Interaction team at the University of St. Andrews to evaluate the potential applications of Brain-Computer Interfaces (BCIs).

• Analyzed and compared various BCI technologies using key metrics such as neuronal recording scale, spatio-temporal signal resolution, and surgical invasiveness.

• Presented findings and earned a Distinction as part of my Scottish Baccalaureate in Science award, showcasing my aptitude for research in the field of BCIs.

RSA Encryption and Decryption Tool

• Created an RSA encryptor-decryptor tool using Python from scratch, leveraging my knowledge of modular arithmetic and asymmetric key encryption to encrypt user input messages and generate a corresponding private key for decryption by the recipient.

• Designed the project as an interactive educational tool to engage and instruct young students on the fundamentals of public key cryptography.