Work History

Developed an interactive, web-based visualization tool using D3.js and React to educate non-technical users about browser fingerprinting and online privacy.

Implemented advanced fingerprinting techniques, enhancing the tool's capability to simulate real-world tracking scenarios.

Integrated gamification elements, resulting in a 40% increase in user engagement and knowledge retention.

Conducted a user study with a group of participants to evaluate the tool's effectiveness, achieving a 95% satisfaction rate.

Authored a comprehensive 13,000-word dissertation exploring the technical, ethical, and societal implications of browser fingerprinting.

Assisted in delivering lectures and lab sessions for undergraduate Computer Science courses, enhancing student understanding of complex concepts.

Conducted weekly office hours, providing one-on-one and small group tutoring, leading to a 15% increase in student performance.

Mentored first-year students, improving their adaptation to university-level studies and fostering a collaborative learning environment.

Designed and developed a Computer Vision system in Python to detect and analyze eye strain using real-time webcam input.

Trained a convolutional neural network (CNN) model with a 92% accuracy rate to monitor eye movement and implemented features for tracking ambient light and gestures signaling strain and tiredness.

Created a user-friendly interface with real-time feedback and a comprehensive notification system, resulting in a reduction in reported eye strain.

Developed an interactive, web-based visualization tool using D3.js and React to educate non-technical users about browser fingerprinting and online privacy.

Implemented advanced fingerprinting techniques, enhancing the tool's capability to simulate real-world tracking scenarios.

Integrated gamification elements, resulting in a 40% increase in user engagement and knowledge retention.

Conducted a user study with a group of participants to evaluate the tool's effectiveness, achieving a 95% satisfaction rate.

Authored a comprehensive 13,000-word dissertation exploring the technical, ethical, and societal implications of browser fingerprinting.

Designed and developed a Computer Vision system in Python to detect and analyze eye strain using real-time webcam input.

Trained a convolutional neural network (CNN) model with a 92% accuracy rate to monitor eye movement and implemented features for tracking ambient light and gestures signaling strain and tiredness.

Created a user-friendly interface with real-time feedback and a comprehensive notification system, resulting in a reduction in reported eye strain.

Built a scalable distributed systems simulator in Java, capable of modeling network latency and node failures.

Achieved 99.9% uptime in simulated high-load scenarios, demonstrating the system's robustness and reliability.

Utilized multi-threading and synchronization techniques to optimize performance and resource management.

Aim to develop an AI-driven personalized fitness recommendation system integrating wearable data, nutrition information, and exercise performance.

Plan to implement reinforcement learning algorithms to optimize training routines and minimize injury risks.

Explore the application of AI in predicting and preventing sports-related injuries, enhancing athlete performance and safety.